
<bib>
<comment>
This file was created by the TYPO3 extension publications
--- Timezone: CEST
Creation date: 2026-04-22
Creation time: 06:43:35
--- Number of references
105
</comment>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>SKGT:WSRE25</citeid>
<title>Teaching Software Quality with Adaptive Source Code Feedback</title>
<year>2025</year>
<month>4</month>
<booktitle>Proc. German Workshop on Software-Reengineering and Evolution (WSRE)</booktitle>
<publisher>Gesellschaft für Informatik</publisher>
<pages>10-12</pages>
<tags>SoftVarE</tags>
<authors>
<person>
<fn>Rahel</fn>
<sn>Sundermann</sn>
</person>
<person>
<fn>Sebastian</fn>
<sn>Krieter</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Thomas</fn>
<sn>Thüm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<title>Calculating Optimal Corrections for Unsolvable Planning Problems</title>
<year>2025</year>
<booktitle>Proceedings of the 28th European Conference on Artificial Intelligence (ECAI 2025)</booktitle>
<publisher>IOS Press</publisher>
<file_url>t3://file?uid=532911</file_url>
<authors>
<person>
<fn>Michael</fn>
<sn>Welt</sn>
</person>
<person>
<fn>Alexander</fn>
<sn>Lodemann</sn>
</person>
<person>
<fn>Conny</fn>
<sn>Olz</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>SaWG23</citeid>
<title>Challenges on Deriving Planning Problems from Ontologies</title>
<abstract>The integration of automated planning and ontologies can benefit systems in aspects like additional expressivity and the handling of huge domains. However, the mapping between these techniques might not be straightforward.
This work identifies some of the core challenges on the mapping of domain-specific ontologies into planning problems. Here, we identify challenges from both, the lenses of automated planning and domain-specific requirements. This work is intended to raise the discussion on these challenges and motivate future work on this direction.</abstract>
<year>2023</year>
<booktitle>Proceedings of the PLanning And onTology wOrkshop (PLATO)</booktitle>
<authors>
<person>
<fn>Milene</fn>
<sn>Santos-Teixeira</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Welt</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GrGl23</citeid>
<title>Comparative Research in Stream Reasoning</title>
<abstract>The diverse research efforts in recent years in the area of stream reasoning (SR) led to a wide range of SR engines. However, the lack of standardization and the diverse choices in SR (e.g., tuple-driven vs.\ time-driven engines, streaming all results vs.\ newly derived ones\mbox, łdots) mean that real comparability among the engines is hardly given. A first step towards achieving comparability and standardization is the RSP-QL model, implemented in the RSP4J framework, which allows for describing and formalizing the semantics of SR engines. To further advance the state of the art in comparative research of stream reasoning, we present the results of a survey to quantify the in-use importance of several key performance indicators (KPIs) and features and compare SR engines along these KPIs with the CityBench and the CSRBench oracle. Our analysis shows that the two RSP4J implementations C-SPARQL2.0 and YASPER outperform the well-known C-SPARQL implementation in terms of performance and configurability. Our comparison against a naive SR extension of the incremental reasoning engine RDFox shows that SR engines still have potential for improvement. To avoid a costly integration of engines into several different benchmarking environments, we finally present a unifying interface, already aligned with the CityBench and CSRBench, for benchmarking SR engines.</abstract>
<year>2023</year>
<booktitle>Proceedings of the 20th European Semantic Web Conference (ESWC 2023)</booktitle>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<note>best paper nominee</note>
<annotation>best paper nominee</annotation>
<authors>
<person>
<fn>Nathan</fn>
<sn>Gruber</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>WeGS23</citeid>
<title>Computing Minimal Unsolvable and Maximal Solvable Abstractions of Planning Problems via Hitting Set Trees</title>
<abstract>The unsolvability of planning problems is frequently associated with errors on the representation of the domain. Knowledge engineers often struggle to understand the underlying conditions of why a planning problem cannot be solved and which changes might be needed to reach a solution. In this work, we discuss theoretical foundations and algorithms that can be used to calculate minimal parts, called abstractions, of the planning problem that preserve the unsolvability. Additionally, our approach provides minimal sets of facts that repair the planning problem by rendering it solvable when removed. Both together can point to the source of the problem and give a clear focus on which parts of the planning specification are problematic. In particular, our proposed method can be used to debug planning problems that are unsolvable due to ill-modeled effects or over-restricted preconditions. Furthermore, we show that sets of facts inducing minimal unsolvable abstractions and repairs are related by diametrical hitting set properties, which allows us to exploit hitting set tree data structures for a goal-directed computation of these sets.</abstract>
<year>2023</year>
<booktitle>Proceedings of the Workshop on Knowledge Engineering for Planning and Scheduling (KEPS 2023)</booktitle>
<authors>
<person>
<fn>Michael</fn>
<sn>Welt</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Milene</fn>
<sn>Santos-Teixeira</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>IlGl22a</citeid>
<title>Computing Concept Referring Expressions for Queries on Horn ALC Ontologies</title>
<abstract>Classical instance queries over an ontology only consider explicitly named individuals. Concept referring expressions (CREs) also allow for returning answers in the form of concepts that describe implicitly given individuals in terms of their relation to an explicitly named one. Existing approaches, e.g., based on tree automata, can neither be integrated into state-of-the-art OWL reasoners nor are they directly amenable for an efficient implementation. To address this, we devise a novel algorithm that uses highly optimized OWL reasoners as a black box. In addition to the standard criteria of singularity and certainty for CREs, we devise and consider the criterion of uniqueness of CREs for Horn ALC ontologies. The evaluation of our prototypical implementation shows that computing CREs for the most general concept (top) can be done in less than one minute for ontologies with thousands of individuals and concepts.</abstract>
<year>2022</year>
<booktitle>Proceedings of the 31st International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2022)</booktitle>
<publisher>Morgan Kaufmann</publisher>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations, Concept Referring Expressions</keywords>
<tags>AutomatedReasoning</tags>
<file_url>t3://file?uid=455865</file_url>
<authors>
<person>
<fn>Moritz</fn>
<sn>Illich</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>IlGl22b</citeid>
<title>Computing Concept Referring Expressions with Standard OWL Reasoners</title>
<abstract>Classical instance queries over an ontology only consider explicitly named individuals. Concept referring expressions (CREs) also allow for returning answers in the form of concepts that describe implicitly given individuals in terms of their relation to an explicitly named one. Existing approaches, e.g., based on tree automata, can neither be integrated into state-of-the-art OWL reasoners nor are they directly amenable for an efficient implementation. To address this, we devise a novel algorithm that uses highly optimized OWL reasoners as a black box. In addition to the standard criteria of singularity and certainty for CREs, we devise and consider the criterion of uniqueness of CREs for Horn ALC ontologies. The evaluation of our prototypical implementation shows that computing CREs for the most general concept can be done in less than one minute for ontologies with thousands of individuals and concepts.</abstract>
<year>2022</year>
<booktitle>Proceedings of the 35th International Workshop on Description Logics
(DL 2022)</booktitle>
<volume>3263</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<editor>Ofer Arieli and
Martin Homola and
Jean Christoph Jung and
Marie-Laure Mugnier</editor>
<file_url>https://ceur-ws.org/Vol-3263/paper-14.pdf</file_url>
<authors>
<person>
<fn>Moritz</fn>
<sn>Illich</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlKW22</citeid>
<title>Concept Abduction for Description Logics</title>
<abstract>We present two alternative algorithms for computing (all or some) solutions to the concept abduction problem: one algorithm is based on Reiter's hitting set tree algorithm, whereas the other one relies on a SAT encoding. In contrast to previous work, the algorithms do not rely on a refutation-based calculus and, hence, can be used also with efficient reasoners for tractable DLs such as $\mathcalEL$ and its extensions. An adaptation to other forms of (logic-based) abduction, e.g., to ABox abduction, is also possible. </abstract>
<year>2022</year>
<booktitle>Proceedings of the 35th International Workshop on Description Logics
(DL 2022)</booktitle>
<volume>3263</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<editor>Ofer Arieli and
Martin Homola and
Jean Christoph Jung and
Marie-Laure Mugnier</editor>
<file_url>https://ceur-ws.org/Vol-3263/paper-11.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Welt</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>DGMT22</citeid>
<title>Current and Future Challenges in Knowledge Representation and Reasoning
(Dagstuhl Seminar 22282)</title>
<abstract>The area of Knowledge Representation and Reasoning (KR) is a central area in Artificial Intelligence that deals with the explicit, declarative representation of knowledge along with inference procedures for deriving further, implicit information from this knowledge. The goal of this Perspectives Seminar was to assess the area of KR, including its history, current state, and future prospects, and from this assessment to provide suggestions and recommendations for advancing the field, increasing participation in the area, and furthering links with related areas. Over the course of 5 days, 25 participants from a cross-section of subareas in KR and areas adjacent to KR met to discuss these topics. The workshop was composed of a number of invited talks and panels for reviewing the history and state of the art of KR, along with several working groups and general open discussions. In common with other Perspectives Workshops, a Manifesto will be produced; as well, recommendations contained in the manifesto will be also forwarded to the steering committee of the Principles of Knowledge Representation and Reasoning conference series for their consideration.</abstract>
<year>2022</year>
<DOI>10.4230/DagRep.12.7.62</DOI>
<journal>Dagstuhl Reports</journal>
<volume>12</volume>
<pages>62—79</pages>
<number>7</number>
<file_url>https://doi.org/10.4230/DagRep.12.7.62</file_url>
<authors>
<person>
<fn>James P.</fn>
<sn>Delgrande</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Thomas</fn>
<sn>Meyer</sn>
</person>
<person>
<fn>Miroslaw</fn>
<sn>Truszczynski</sn>
</person>
<person>
<fn>Milene Santos</fn>
<sn>Teixeira</sn>
</person>
<person>
<fn>Frank</fn>
<sn>Wolter</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlKa22</citeid>
<title>SAT-Based Axiom Pinpointing Revisited</title>
<abstract>Propositional SAT solvers have been a popular way of computing justifications for ontological entailment– minimal subsets of axioms of the ontologies that entail a given conclusion. Most SAT encodings proposed for Description Logics (DLs), translate the inferences obtained by a consequence-based procedure to propositional Horn clauses, using which entailments from subsets of axioms can be effectively checked, and use modified SAT solvers to systematically search over these subsets. To avoid repeated discovery of subsets with already checked entailment, the modified SAT solvers add special blocking clauses that prevent generating truth assignments corresponding to these subsets, the number of which can be exponential, even if the number of justifications is small. In this paper, we propose alternative SAT encodings that avoid generation of unnecessary blocking clauses. Unlike the previous methods, the inferences are used not only for checking entailment from subsets of axioms, but also, as a part of the encoding, to ensure that the SAT solver generates truth assignments corresponding only to justifications.</abstract>
<year>2022</year>
<booktitle>Proceedings of the 35th International Workshop on Description Logics
(DL 2022)</booktitle>
<volume>3263</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<editor>Ofer Arieli and
Martin Homola and
Jean Christoph Jung and
Marie-Laure Mugnier</editor>
<file_url>https://ceur-ws.org/Vol-3263/paper-10.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>BBKS21</citeid>
<title>Do It Yourself, but Not Alone: Companion-Technology for Home Improvement
— Bringing a Planning-Based Interactive DIY Assistant to Life</title>
<abstract>We report on the technology transfer project “Do it yourself, but not alone: Companion-Technology for Home Improvement” that was carried out by Ulm University in cooperation with Robert Bosch GmbH. We developed a prototypical assistance system that assists a Do It Yourself (DIY) handyman in carrying out DIY projects. The assistant, based on various AI and dialog management capabilities, generates a sequence of detailed instructions that users may just follow or adapt according to their individual preferences. It features explanation capabilities as well as pro-active support based on communication with the user as well as with the involved tools. We report on the project’s main achievements, including the findings of various empirical studies conducted in various development stages of the prototype.</abstract>
<year>2021</year>
<DOI>10.1007/s13218-021-00721-x</DOI>
<journal>Künstliche Intell.</journal>
<volume>35</volume>
<pages>367—375</pages>
<number>3</number>
<file_url>https://doi.org/10.1007/s13218-021-00721-x</file_url>
<authors>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Dietrich</fn>
<sn>Manstetten</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dambier</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dorna</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>Bercher2021DIY</citeid>
<title>Do It Yourself, but Not Alone: Companion-Technology for Home Improvement – Bringing a Planning-Based Interactive DIY Assistant to Life</title>
<abstract>We report on the technology transfer project “Do it yourself, but not alone: Companion-Technology for Home Improvement” that was carried out by Ulm University in cooperation with Robert Bosch GmbH. We developed a prototypical assistance system that assists a Do It Yourself (DIY) handyman in carrying out DIY projects. The assistant, based on various AI and dialog management capabilities, generates a sequence of detailed instructions that users may just follow or adapt according to their individual preferences. It features explanation capabilities as well as pro-active support based on communication with
the user as well as with the involved tools. We report on the project’s main achievements, including the findings of various empirical studies conducted in various development stages of the prototype.</abstract>
<year>2021</year>
<journal>Künstliche Intelligenz – Special Issue on NLP and Semantics</journal>
<web_url2>https://rdcu.be/cmGwb</web_url2>
<file_url>http://link.springer.com/article/10.1007/s13218-021-00721-x</file_url>
<authors>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Dietrich</fn>
<sn>Manstetten</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dambier</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dorna</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>WeLG21a</citeid>
<title>HDT Bitmap Triple Indices for Efficient RDF Data Exploration</title>
<abstract>The exploration of large, unknown RDF data sets is difficult even for users who are familiar with Semantic Web technologies as, e.g., the SPARQL query language. The concept of faceted navigation offers a user-friendly exploration method through filters that are chosen such that no empty result sets occur. However, especially for large data sets, computing such filters is resource intensive and may cause considerable delays in the user interaction. One possibility for improving the performance is the generation of indices for partial solutions. In this paper, we propose and evaluate indices in form of the Bitmap Triple (BT) data structure, generated over the Header-Dictionary-Triples (HDT) RDF compression format. We show that the resulting indices can be utilized to efficiently compute the required exploratory operations for data sets with up to 150 million triples. In the experiments, the BT indices exhibit a stable performance and outperform other deployed approaches in four out of five compared operations.</abstract>
<status>1</status>
<year>2021</year>
<booktitle>Proceedings of the 18th European Semantic Web Conference (ESWC 2021)</booktitle>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<tags>AutomatedReasoning, KnowledgeModelling</tags>
<authors>
<person>
<fn>Maximilian</fn>
<sn>Wenzel</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>QuAG21a</citeid>
<title>Ontology-Based Map Data Quality Assurance</title>
<abstract>A lane-level, high-definition (HD) digital map is needed for autonomous cars to provide safety and security to the passengers. However, it continues to prove very difficult to produce error-free maps. To avoid the deactivation of autonomous driving (AD) mode caused by map errors, ensuring map data quality is a crucial task. We propose an ontology-based workflow for HD map data quality assurance, including semantic enrichment, violation detection, and violation handling. Evaluations show that our approach can successfully check the quality of map data and suggests that violation handling is even feasible on-the-fly in the car (on-board), avoiding the autonomous driving mode's deactivation.</abstract>
<year>2021</year>
<booktitle>Proceedings of the 18th European Semantic Web Conference (ESWC 2021)</booktitle>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<tags>AutomatedReasoning
KnowledgeModelling</tags>
<authors>
<person>
<fn>Haonan</fn>
<sn>Qiu</sn>
</person>
<person>
<fn>Adel</fn>
<sn>Ayara</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>StGl21a</citeid>
<title>Parallelised ABox Reasoning and Query Answering with Expressive Description Logics</title>
<abstract>Automated reasoning support is an important aspect of logic-based knowledge representation. The development of specialised procedures and sophisticated optimisation techniques significantly improved the performance even for complex reasoning tasks such as conjunctive query answering. Reasoning and query answering over knowledge bases with a large number of facts and expressive schemata remains, however, challenging.
We propose a novel approach where the reasoning over assertional knowledge is split into small, similarly sized work packages to enable a parallelised processing with tableau algorithms, which are dominantly used for reasoning with more expressive Description Logics. To retain completeness in the presence of expressive schemata, we propose a specifically designed cache that allows for controlling and synchronising the interaction between the constructed partial models. We further report on encouraging performance improvements for the implementation of the techniques in the tableau-based reasoning system Konclude.</abstract>
<year>2021</year>
<booktitle>Proceedings of the 18th European Semantic Web Conference (ESWC 2021)</booktitle>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<tags>AutomatedReasoning
KnowledgeModelling
SemanticTechnologies</tags>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>StGL21b</citeid>
<title>Query Answering and Scaling Extensions of Konclude</title>
<abstract>Konclude is a well-performing reasoner for ontologies formulated via the Web Ontology Language. In this paper, we give an overview of new or extended optimizations that lead to additional improvements. We further describe new (functional) extensions and capabilities (such as query answering) that are ready for first practical use-cases. Last but not least, we show some evaluations and comparisons for the new version of Konclude.</abstract>
<year>2021</year>
<booktitle>Proceedings of the Semantic Reasoning Evaluation Challenge (SemREC
2021)</booktitle>
<volume>3123</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<editor>Gunjan Singh and
Raghava Mutharaju and
Pavan Kapanipathi</editor>
<pages>37—43</pages>
<file_url>https://ceur-ws.org/Vol-3123/paper5.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>QiAG20a</citeid>
<title>A Knowledge Architecture Layer for Map Data in Autonomous Vehicles</title>
<year>2020</year>
<booktitle>Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems (ITSC 2020)</booktitle>
<publisher>IEEE</publisher>
<tags>AutomatedReasoning,KnowledgeModelling</tags>
<file_url>t3://file?uid=431045</file_url>
<note>Best Paper Nomination</note>
<authors>
<person>
<fn>Haonan</fn>
<sn>Qiu</sn>
</person>
<person>
<fn>Adel</fn>
<sn>Ayara</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>QiAG20c</citeid>
<title>A Knowledge-Spatial Architecture for Processing Dynamic Maps in Automated Driving</title>
<year>2020</year>
<booktitle>Proceedings of the ISWC 2020 Posters & Demonstrations Track</booktitle>
<volume>2721</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<keywords>Semantic Web</keywords>
<tags>AutomatedReasoning, KnowledgeModelling</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2020/QiAG20c.pdf</file_url>
<authors>
<person>
<fn>Haonan</fn>
<sn>Qiu</sn>
</person>
<person>
<fn>Adel</fn>
<sn>Ayara</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Behnke2020DIYAssistant</citeid>
<title>New Developments for Robert – Assisting Novice Users Even Better in DIY Projects</title>
<year>2020</year>
<booktitle>Proceedings of the 30th International Conference on Automated Planning and Scheduling (ICAPS 2020)</booktitle>
<publisher>AAAI Press</publisher>
<pages>343--347</pages>
<keywords>SFB-T3,Planning</keywords>
<tags>SFB-T3,Planning,KnowledgeModelling</tags>
<web_url>https://aaai.org/ojs/index.php/ICAPS/article/view/6679/6533 - - "Link to the AAAI Paper Version"</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2020/Behnke2020DIYAssistant.pdf</file_url>
<authors>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Kristof</fn>
<sn>Mickeleit</sn>
</person>
<person>
<fn>Timo</fn>
<sn>Häge</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dorna</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dambier</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>QiAG20b</citeid>
<title>Ontology-based Processing of Dynamic Maps in Automated Driving</title>
<year>2020</year>
<booktitle>Proceedings of the 12th International Conference on Knowledge Engineering and Ontology Development (KEOD 2020)</booktitle>
<publisher>SciTePress</publisher>
<tags>AutomatedReasoning,KnowledgeModelling</tags>
<file_url>t3://file?uid=431048</file_url>
<authors>
<person>
<fn>Haonan</fn>
<sn>Qiu</sn>
</person>
<person>
<fn>Adel</fn>
<sn>Ayara</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Kraus2020ICMI</citeid>
<title>Was that successful? On Integrating Proactive Meta-Dialogue in a DIY-Assistant System using Multimodal Cues</title>
<abstract>Effectively supporting novices during performance of
complex tasks, e.g. do-it-yourself (DIY) projects, requires intelligent
assistants to be more than mere instructors. In order to be accepted as
a competent and trustworthy cooperation partner, they need to be able to
actively participate in the project and engage in helpful conversations
with users when assistance is necessary. Therefore, a new proactive
version of the DIY-assistant \textsc{Robert} is presented in this paper.
It extends the previous prototype by including the capability to
initiate reflective meta-dialogues using multimodal cues. Two different
strategies for reflective dialogue are implemented: A progress-based
strategy initiates a reflective dialogue about previous experience with
the assistance for encouraging the self-appraisal of the user. An
activity-based strategy is applied for providing timely, task-dependent
support. Therefore, user activities with a connected drill driver are
tracked that trigger dialogues in order to reflect on the current task
and to prevent task failure. An experimental study comparing the
proactive assistant against the baseline version shows that proactive
meta-dialogue is able to build user trust significantly better than a
solely reactive system. Besides, the results provide interesting
insights for the development of proactive dialogue assistants.</abstract>
<year>2020</year>
<booktitle>Proceedings of 22nd ACM International Conference on Multimodal Interaction (ICMI 2020)</booktitle>
<publisher>ACM</publisher>
<tags>SFB-T3</tags>
<web_url>https://dl.acm.org/doi/pdf/10.1145/3382507.3418818 - - "Link to the Conference Paper"</web_url>
<file_url>t3://file?uid=431053</file_url>
<authors>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dorna</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dambier</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inbook</bibtype>
<citeid>Kraus2019CloudCompanion</citeid>
<title>9th International Workshop on Spoken Dialogue Systems</title>
<abstract>Companion systems are cooperative, cognitive systems aiming at assist-ing a user in everyday situations. Therefore, these systems require a high level ofavailability. One option to meet this requirement is to use a web-deployable archi-tecture. In this demo paper, we present a multimodal cloud-based dialogue frame-work for the development of a distributed, web-based companion system. The pro-posed framework is intended to provide an efficient, easily extensible, and scalableapproach for these kinds of systems and will be demonstrated in a do-it-yourselfassistance scenario.</abstract>
<year>2019</year>
<publisher>Springer</publisher>
<chapter>A Multimodal Dialogue Framework for Cloud-Based Companion Systems</chapter>
<series>Lecture Notes in Electrical Engineering</series>
<editor>Rafael Banchs and Luis Fernando D'Haro and Haizhou Li</editor>
<tags>SFB-T3,Planning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2019/Kraus2019CloudCompanion.pdf</file_url>
<authors>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>10.1007/978-3-030-30793-6_34</citeid>
<title>Absorption-Based Query Answering for Expressive Description Logics</title>
<abstract>Conjunctive query answering is an important reasoning task for logic-based knowledge representation formalisms, such as Description Logics, to query for instance data that is related in certain ways. Although many knowledge bases use language features of more expressive Description Logics, there are hardly any systems that support full conjunctive query answering for these logics. In fact, existing systems usually impose restrictions on the queries or only compute incomplete results.</abstract>
<year>2019</year>
<isbn>978-3-030-30793-6</isbn>
<booktitle>Proceedings of the 18th International Semantic Web Conference (ISWC 2019) Band 11778 aus Lecture Notes in Computer Science</booktitle>
<publisher>Springer International Publishing</publisher>
<address>Cham</address>
<editor>Chiara Ghidini, Olaf Hartig, Maria Maleshkova, Vojtěch Svátek,Isabel Cruz, Aidan Hogan</editor>
<pages>593--611</pages>
<web_url>https://link.springer.com/chapter/10.1007%2F978-3-030-30793-6_34</web_url>
<file_url>t3://file?uid=429519</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>DBLP:conf/dlog/SteigmillerG19</citeid>
<title>Absorption-Based Query Entailment Checking for Expressive Description
Logics</title>
<year>2019</year>
<booktitle>Proceedings of the 32nd International Workshop on Description Logics (DL 2019) Band 2373 aus CEUR Workshop Proceedings</booktitle>
<publisher>CEUR-WS.org</publisher>
<web_url>http://ceur-ws.org/Vol-2373/paper-25.pdf</web_url>
<file_url>http://ceur-ws.org/Vol-2373/paper-25.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>Behnke2019bosch</citeid>
<title>Alice in DIY wonderland or: Instructing novice users on how to use tools in DIY projects</title>
<abstract>We present the interactive assistant Robert that provides situation-adaptive support in the realisation of do-it-yourself (DIY) home improvement projects.
Robert assists its users by providing comprehensive step-by-step instructions for completing the DIY project.
Each instruction is illustrated with detailed graphics, written and spoken text, as well as with videos.
They explain how the steps of the project have to be prepared and assembled and give precise instructions on how to operate the required electric devices.
The step-by-step instructions are generated by a hierarchical planner, which enables Robert to adapt to a multitude of environments easily.
Parts of the underlying model are derived from an ontology storing information about the available devices and resources.
A dialogue manager capable of natural language interaction is responsible for hands-free interaction.
We explain the required background technology and present preliminary results of an empirical evaluation.</abstract>
<year>2019</year>
<DOI>10.3233/AIC-180604</DOI>
<journal>AI Communications</journal>
<volume>32</volume>
<publisher>IOS Press</publisher>
<pages>31-57</pages>
<number>1</number>
<tags>SFB-T3,Planning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2019/Behnke2019bosch.pdf</file_url>
<note>The final publication is available at IOS Press through http://dx.doi.org/10.3233/AIC-180604</note>
<annotation>The final publication is available at IOS Press through http://dx.doi.org/10.3233/AIC-180604</annotation>
<authors>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Mario</fn>
<sn>Schmautz</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dorna</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dambier</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>SQAG19a</citeid>
<title>An Ontological Model for Map Data in Automotive Systems</title>
<year>2019</year>
<booktitle>Proceedings of the 2nd IEEE International Conference on Artificial Intelligence and Knowledge Engineering (AIKE 2019)</booktitle>
<publisher>IEEE</publisher>
<pages>140--147</pages>
<tags>AutomatedReasoning,KnowledgeModelling</tags>
<web_url>https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8791704 - - "Link to conference paper"</web_url>
<file_url>t3://file?uid=431057</file_url>
<authors>
<person>
<fn>Yogita</fn>
<sn>Suryawanshi</sn>
</person>
<person>
<fn>Haonan</fn>
<sn>Qiu</sn>
</person>
<person>
<fn>Adel</fn>
<sn>Ayara</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>DBLP:conf/rweb/GlimmK19</citeid>
<title>Classical Algorithms for Reasoning and Explanation in Description
Logics</title>
<year>2019</year>
<DOI>10.1007/978-3-030-31423-1_1</DOI>
<booktitle>Reasoning Web. Explainable Artificial Intelligence - 15th International Summer School</booktitle>
<volume>11810</volume>
<publisher>Springer</publisher>
<series>Lecture Notes in Computer Science</series>
<editor>Markus Krötzsch and Daria Stepanova</editor>
<pages>1-64</pages>
<tags>KnowledgeModeling</tags>
<web_url>https://doi.org/10.1007/978-3-030-31423-1\_1</web_url>
<file_url>t3://file?uid=420338</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Kraus2018CompanionCloudDemo</citeid>
<title>A Multimodal Dialogue Framework for Cloud-Based Companion Systems</title>
<abstract>Abstract Companion systems are cooperative, cognitive systems aiming at assisting a user in everyday situations. Therefore, these systems require a high level of availability. One option to meet this requirement is to use a web-deployable architecture. In this demo paper, we present a multimodal cloud-based dialogue framework for the development of a distributed, web-based companion system. The proposed framework is intended to provide an efficient, easily extensible, and scalable approach for this kind of systems and will be demonstrated in a do-it-yourself assistance scenario.</abstract>
<year>2018</year>
<booktitle>Proc. of the 10th International Workshop on Spoken Dialog Systems Technology (IWSDS 2018)</booktitle>
<tags>SFB-TRR-62,SFB-T3,Planning,KnowledgeModeling</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2018/Kraus2018CompanionCloudDemo.pdf</file_url>
<authors>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>PSH2018</citeid>
<title>Applying a Model of Text Comprehension to Automated Verbalizations of EL Derivations</title>
<year>2018</year>
<booktitle>Proceedings of DL 2018, CEUR Workshop Proceedings Vol. 2211</booktitle>
<tags>SFB-TRR-62,SFB-T3</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2018/PerlethSchillerGlimmDL2018.pdf</file_url>
<authors>
<person>
<fn>Tanja</fn>
<sn>Perleth</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>BrGl18a</citeid>
<title>Embracing Change by Abstraction Materialization Maintenance for Large ABoxes</title>
<abstract>Abstraction Refinement is a recently introduced technique which allows for reducing materialization of an ontology with a large ABox to materialization of a smaller (compressed) 'abstraction' of this ontology. In this paper, we show how Abstraction Refinement can be adopted for incremental ABox materialization by combining it with the well-known DRed algorithm for materialization maintenance. Such a combination is non-trivial and to preserve soundness and completeness, already Horn ALCHI requires more complex abstractions. Nevertheless, we show that significant benefits can be obtained for synthetic and real-world ontologies.</abstract>
<year>2018</year>
<booktitle>Proceedings of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018)</booktitle>
<publisher>AAAI Press</publisher>
<tags>AutomatedReasoning</tags>
<web_url>www.ijcai.org</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2018/BrGl18a.pdf</file_url>
<authors>
<person>
<fn>Markus</fn>
<sn>Brenner</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>schillerEtAlMCI2018</citeid>
<title>Evaluating Knowledge-Based Assistance for DIY</title>
<abstract>We report on the development of a companion system incorporating hierarchical planning, ontology-based knowledge modeling and multimodal cloud-based dialog. As an application scenario, we consider the domain of do-it-yourself (DIY) home improvement involving the use of power tools. To test and – if necessary – adjust the developed techniques, user studies are conducted throughout the development phase. We present fundamental considerations and open questions encountered when testing the implemented prototype with potential users and report first observations from a current study.</abstract>
<year>2018</year>
<booktitle>Proceedings of MCI Workshop "Digital Companion"</booktitle>
<pages>925--930</pages>
<tags>SFB-TRR-62,SFB-T3</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2018/MCI-WS19-schillerEtAl2018.pdf</file_url>
<authors>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dorna</sn>
</person>
<person>
<fn>Felix</fn>
<sn>Richter</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Behnke2018HomeImprovementSystem</citeid>
<title>Instructing Novice Users on How to Use Tools in DIY Projects</title>
<abstract>Novice users require assistance when performing handicraft tasks. Adequate instruction ensures task completion and conveys knowledge and abilities required to perform the task.  We present an assistant teaching novice users how to operate electronic tools, such as drills, saws, and sanders, in the context of Do-It-Yourself (DIY) home improvement projects. First, the actions that need to be performed for the project are determined by a planner.  Second, a dialogue manager capable of natural language interaction presents these actions as instructions to the user. Third, questions on these actions and involved objects are answered by generating appropriate ontology-based explanations.</abstract>
<year>2018</year>
<DOI>10.24963/ijcai.2018/844</DOI>
<booktitle>Proceedings of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018)</booktitle>
<publisher>IJCAI</publisher>
<pages>5805--5807</pages>
<tags>SFB-T3</tags>
<web_url>www.ijcai.org</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2018/Behnke2018DIY.pdf</file_url>
<authors>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Mario</fn>
<sn>Schmautz</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dorna</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Schiller17CouplingKnowledge</citeid>
<title>A Paradigm for Coupling Procedural and Conceptual Knowledge in Companion Systems</title>
<abstract>Companion systems are technical systems that adjust their functionality to the needs and the situation of an individual user. Consequently, companion systems are strongly knowledge-based. We propose a modelling paradigm for integrating procedural and conceptual knowledge which is targeted at companion systems that require a combination of planning and reasoning capabilities. The presented methodology couples the hierarchical task network (HTN) planning formalism with an ontology-based knowledge representation, thereby minimising redundancies in modelling and enabling the use of state-of-the-art reasoning and planning tools on the shared knowledge model. The approach is applied within a prototype of a companion system that assists novice users in the do-it-yourself (DIY) domain with the planning and execution of home improvement projects involving the use of power tools.</abstract>
<year>2017</year>
<DOI>10.1109/COMPANION.2017.8287072</DOI>
<booktitle>Proceedings of the 2nd International Conference on Companion Technology (ICCT 2017)</booktitle>
<publisher>IEEE</publisher>
<tags>SFB-TRR-62,SFB-T3,Planning,KnowledgeModeling</tags>
<web_url>http://ieeexplore.ieee.org/document/8287072/</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/SBSBKDMGB-ICCT2017.pdf</file_url>
<authors>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Mario</fn>
<sn>Schmautz</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Michael</fn>
<sn>Dorna</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>BrGl17a</citeid>
<title>Incremental Materialization Update via Abstraction Refinement</title>
<year>2017</year>
<booktitle>Proceedings of the 30th International Workshop on Description Logics (DL 2017)</booktitle>
<volume>1879</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-1879/paper19.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/GlBr17a.pdf</file_url>
<authors>
<person>
<fn>Markus</fn>
<sn>Brenner</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Ulmschneider.2017</citeid>
<title>Knowledge Graph: Semantic Representation and Assessment of Innovation Ecosystems</title>
<abstract>Innovative capacity is highly dependent upon knowledge and the possession of unique competences can be an important source of enduring strategic advantage. Hence, being able to identify, locate, measure, and assess competence occupants can be a decisive competitive edge. In this work, we introduce a framework that assists with performing such tasks. To achieve this, NLP-, rule-based, and machine learning techniques are employed to process raw data such as academic publications or patents. The framework gains normalized person and organization profiles and compiles identified entities (such as persons, organizations, or locations) into dedicated objects disambiguating and unifying where needed. The objects are then mapped with conceptual systems and stored along with identified semantic relations in a Knowledge Graph, which is constituted by RDF triples. An OWL reasoner allows for answering complex business queries, and in particular, to analyze and evaluate competences on multiple aggregation levels (i.e., single vs. collective) and dimensions (e.g., region, technological field of interest, time). In order to prove the general applicability of the framework and to illustrate how to solve concrete business cases from the automotive domain, it is evaluated with different datasets.</abstract>
<year>2017</year>
<isbn>978-3-319-69547-1</isbn>
<DOI>10.1007/978-3-319-69548-8_15</DOI>
<booktitle>Proceedings of the 8th International Conference on Knowledge Engineering and Semantic Web (KESW 2017)</booktitle>
<publisher>Springer</publisher>
<address>Berlin, Germany</address>
<series>Communications in Computer and Information Science (CCIS)</series>
<editor>Rozewski, Przemyslaw and Lange, Christoph</editor>
<pages>211--226</pages>
<keywords>Competence Analysis;Competence Assessment;Competence Detection;Computational Linguistics;Corporate Strategy;Data Mining;Decision Making;Expert Matching;Expert Mining;Information Extraction;Information Retrieval;Innovation Ecosystem;Knowledge Graph;Knowledge Representation;Machine Learning;Name Disambiguation;Name Normalization;Natural Language Processing;Ontology;Patent Analysis;Question Answering;Reasoning;Semantic Analysis;Semantic Technologies</keywords>
<tags>AutomatedReasoning,KnowledgeModelling</tags>
<web_url>https://link.springer.com/chapter/10.1007/978-3-319-69548-8_15</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/UlGl17a.pdf</file_url>
<authors>
<person>
<fn>Klaus</fn>
<sn>Ulmschneider</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>conference</bibtype>
<citeid>GliKazTra:17:Abstraction:Horn:SHOIF:AAAI</citeid>
<title>Ontology Materialization by Abstraction Refinement in Horn SHOIF</title>
<abstract>Abstraction refinement is a recently introduced technique using which reasoning over large ABoxes is reduced to reasoning over small abstract ABoxes. Although the approach is sound for any classical Description Logic such as {SROIQ}, it is complete only for Horn {ALCHOI}. In this paper, we propose an extension of this method that is now complete for Horn {SHOIF} and also handles role- and equality-materialization. To show completeness, we use a tailored set of materialization rules that loosely decouple the ABox from the TBox. An empirical evaluation demonstrates that, despite the new features, the abstractions are still significantly smaller than the original ontologies and the materialization can be computed efficiently.</abstract>
<year>2017</year>
<booktitle>Proceedings of the 31st AAAI Conference on Artificial Intelligence</booktitle>
<publisher>AAAI Press</publisher>
<editor>Satinder P. Singh and Shaul Markovitch</editor>
<pages>1114--1120</pages>
<event_name>31st AAAI Conference on Artificial Intelligence</event_name>
<event_place>San Francisco, California, USA</event_place>
<tags>AutomatedReasoning</tags>
<web_url>http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14726</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/GlKT17a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Trung-Kien</fn>
<sn>Tran</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>MaKG17a</citeid>
<title>QSMat: Query-Based Materialization for Efficient RDF Stream Processing</title>
<abstract>This paper presents a novel approach, QSMat, for efficient RDF data stream querying with flexible query-based materialization. Previous work accelerates either the maintenance of a stream window materialization or the evaluation of a query over the stream. QSMat exploits knowledge of a given query and entailment rule-set to accelerate window materialization by avoiding inferences that provably do not affect the evaluation of the query. We prove that stream querying over the resulting partial window materializations with QSMat is sound and complete with regard to the query. A comparative experimental performance evaluation based on the Berlin SPARQL benchmark and with selected representative systems for stream reasoning shows that QSMat can significantly reduce window materialization size, reasoning overhead, and thus stream query evaluation time.</abstract>
<year>2017</year>
<DOI>10.1007/978-3-319-69548-8_12</DOI>
<booktitle>Proceedings of the 8th International Conference on Knowledge Engineering and Semantic Web (KESW 2017)</booktitle>
<volume>786</volume>
<publisher>Springer-Verlag</publisher>
<series>Communications in Computer and Information Science</series>
<pages>159-174</pages>
<tags>AutomatedReasoning</tags>
<web_url>https://link.springer.com/chapter/10.1007/978-3-319-69548-8_12</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/MaKG17a.pdf</file_url>
<authors>
<person>
<fn>Christian</fn>
<sn>Mathieu</sn>
</person>
<person>
<fn>Matthias</fn>
<sn>Klusch</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlKT17b</citeid>
<title>Scalable Reasoning by Abstraction in DL-Lite</title>
<year>2017</year>
<booktitle>Proceedings of the 30th International Workshop on Description Logics (DL 2017)</booktitle>
<volume>1879</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-1879/paper57.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/GlKT17b.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Trung-Kien</fn>
<sn>Tran</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Behnke2017Sloth</citeid>
<title>SLOTH - the Interactive Workout Planner</title>
<abstract>We present the mixed-initiative planning system SLOTH, which is designed to assist users in planning a fitness workout. Mixed-initiative planning systems are especially useful for companion systems, as they allow the seamless integration of the complex  cognitive ability of planning into ambient assistance systems. This is achieved by integrating the user directly into the process of plan generation and  thereby allowing him to specify these objectives and to be assisted
in generating a plan that not only achieves his objectives, but at the  same time also fits his preferences. We present the capabilities that  are integrated into SLOTH and discuss the design choices and considerata that have to be taken into account when constructing a mixed-initiative planning system.</abstract>
<year>2017</year>
<DOI>10.1109/COMPANION.2017.8287077</DOI>
<booktitle>Proceedings of the 2nd International Conference on Companion Technology (ICCT 2017)</booktitle>
<publisher>IEEE</publisher>
<tags>SFB-TRR-62,Planning</tags>
<web_url>http://ieeexplore.ieee.org/document/8287077/</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/Behnke2017Sloth.pdf</file_url>
<authors>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Florian</fn>
<sn>Nielsen</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Matthias</fn>
<sn>Kraus</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>ScSG17a</citeid>
<title>Testing the Adequacy of Automated Explanations of EL Subsumptions</title>
<year>2017</year>
<booktitle>Proceedings of the 30th International Workshop on Description Logics (DL 2017)</booktitle>
<volume>1879</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<tags>AutomatedReasoning,KnowledgeModelling</tags>
<web_url>http://ceur-ws.org/Vol-1879/paper43.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/ScSG17a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Florian</fn>
<sn>Schiller</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>PMGG17a</citeid>
<title>The OWL Reasoner Evaluation (ORE) 2015 Competition Report</title>
<abstract>The OWL Reasoner Evaluation competition is an annual competition (with an associated workshop) that pits OWL 2 compliant reasoners against each other on various standard reasoning tasks over naturally occurring problems. The 2015 competition was the third of its sort and had 14 reasoners competing in six tracks comprising three tasks (consistency, classification, and realisation) over two profiles (OWL 2 DL and EL). In this paper, we discuss the design, execution and results of the 2015 competition with particular attention to lessons learned for benchmarking, comparative experiments, and future competitions.</abstract>
<year>2017</year>
<DOI>10.1007/s10817-017-9406-8</DOI>
<journal>Journal of Automated Reasoning (JAR)</journal>
<volume>59</volume>
<pages>455-482</pages>
<number>4</number>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>https://doi.org/10.1007/s10817-017-9406-8</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/PMGG17a.pdf</file_url>
<authors>
<person>
<fn>Bijan</fn>
<sn>Parsia</sn>
</person>
<person>
<fn>Nicolas</fn>
<sn>Matentzoglu</sn>
</person>
<person>
<fn>Rafael S.</fn>
<sn>Goncalves</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inbook</bibtype>
<citeid>Behnke2017CompBookMIP</citeid>
<title>To Plan for the User Is to Plan With the User -- Integrating User Interaction Into the Planning Process</title>
<abstract>Settings where systems and users work together to solve problems collaboratively are among the most challenging applications of Companion-Technology. So far we have seen how planning technology can be exploited to realize Companion-Systems that adapt flexibly to changes in the user’s situation and environment and provide detailed help for users to realize their goals. However, such systems lack the capability to generate their plans in cooperation with the user. In this chapter we go one step further and describe how to involve the user directly into the planning process. This enables users to integrate their wishes and preferences into plans and helps the system to produce individual plans, which in turn let the Companion-System gain acceptance and trust from the user.
Such a Companion-System must be able to manage diverse interactions with a human user. A so-called mixed-initiative planning system integrates several Companion-Technologies which are described in this chapter. For example, a—not yet final—plan, including its flaws and solutions, must be presented to the user to provide a basis for her or his decision. We describe how a dialog manager can be constructed such that it can handle all communication with a user. Naturally, the dialog manager and the planner must use coherent models. We show how an ontology can be exploited to achieve such models. Finally, we show how the causal information included in plans can be used to answer the questions a user might have about a plan.
The given capabilities of a system to integrate user decisions and to explain its own decisions to the user in an appropriate way are essential for systems that interact with human users.</abstract>
<year>2017</year>
<DOI>10.1007/978-3-319-43665-4_7</DOI>
<booktitle>Companion Technology -- A Paradigm Shift in Human-Technology Interaction</booktitle>
<publisher>Springer</publisher>
<chapter>7</chapter>
<series>Cognitive Technologies</series>
<editor>Susanne Biundo and Andreas Wendemuth</editor>
<pages>123--144</pages>
<tags>SFB-TRR-62,Planning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2017/Behnke2017CompBookMIP.pdf</file_url>
<authors>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Florian</fn>
<sn>Nielsen</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Denis</fn>
<sn>Ponomaryov</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>GlSt2016a</citeid>
<title>15 Years of Semantic Web: An Incomplete Survey</title>
<year>2016</year>
<issn>0933-1875</issn>
<DOI>10.1007/s13218-016-0424-1</DOI>
<journal>KI - Künstliche Intelligenz</journal>
<volume>30</volume>
<pages>117--130</pages>
<number>2</number>
<keywords>Reasoning, Description Logics, Semantic Web</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://dx.doi.org/10.1007/s13218-016-0424-1</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2016/GlSt2016a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Heiner</fn>
<sn>Stuckenschmidt</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>ZhQG16a</citeid>
<title>Exploring Parallel Tractability of Ontology Materialization</title>
<abstract>Materialization is an important reasoning service for applications built on the Web Ontology Language (OWL). To make materialization efficient in practice, current research focuses on deciding tractability of an ontology language and designing parallel reasoning algorithms. However, some well-known large-scale ontologies, such as YAGO, have been shown to have good performance for parallel reasoning, but they are expressed in ontology languages that are not parallelly tractable, i.e., the reasoning is inherently sequential in the worst case. This motivates us to study the problem of parallel tractability of ontology materialization from a theoretical perspective. That is, we aim to identify the ontologies for which materialization is parallelly tractable, i.e., in NC complexity. In this work, we focus on datalog rewritable ontology languages. We identify several classes of datalog rewritable ontologies (called parallelly tractable classes) such that materialization over them is parallelly tractable. We further investigate the parallel tractability of materialization of a datalog rewritable OWL fragment DHL (Description Horn Logic) and an extension of DHL that allows complex role inclusion axioms. Based on the above results, we analyze real-world datasets and show that many ontologies expressed in DHL or its extension belong to the parallelly tractable classes.</abstract>
<year>2016</year>
<DOI>10.3233/978-1-61499-672-9-73</DOI>
<booktitle>Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI 2016)</booktitle>
<volume>285</volume>
<publisher>IOS Press</publisher>
<series>Frontiers in Artificial Intelligence and Applications</series>
<pages>73-81</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations,Materialization, Materialisation, Paralellisation, Paralellization</keywords>
<tags>AutomatedReasoning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2016/ZhQG16a.pdf</file_url>
<authors>
<person>
<fn>Zhangquan</fn>
<sn>Zhou</sn>
</person>
<person>
<fn>Guilin</fn>
<sn>Qi</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>Glim2016a</citeid>
<title>Interview with Prof. Dr. Ian Horrocks, Professor at the Department of Computer Science of the University of Oxford</title>
<year>2016</year>
<issn>0933-1875</issn>
<DOI>10.1007/s13218-016-0428-x</DOI>
<journal>KI - Künstliche Intelligenz</journal>
<volume>30</volume>
<pages>201--203</pages>
<number>2</number>
<keywords>Reasoning, Description Logics, Semantic Web</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://dx.doi.org/10.1007/s13218-016-0428-x</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2016/Glim2016a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlKT16a</citeid>
<title>Ontology Materialization by Abstraction Refinement in Horn SHOIF</title>
<year>2016</year>
<booktitle>Proceedings of the 29th International Workshop on Description Logics (DL 2016)</booktitle>
<volume>1577</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-1577/invited_paper_1.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2016/GlKT16a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Trung-Kien</fn>
<sn>Tran</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlKT16b</citeid>
<title>Scalable Reasoning by Abstraction Beyond DL-Lite</title>
<year>2016</year>
<booktitle>Proceedings of the 10th International Conference on Web Reasoning and Rule Systems (RR 2016)</booktitle>
<volume>9898</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<editor>Magdalena Ortiz and Stefan Schlobach</editor>
<pages>77--93</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations, Materialization, Materialisation, Abstraction</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://dx.doi.org/10.1007/978-3-319-45276-0_7</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2016/GlKT16b.pdf</file_url>
<note>Best Student Paper Award</note>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Trung-Kien</fn>
<sn>Tran</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Ulmschneider.2016</citeid>
<title>Semantic Exploitation of Implicit Patent Information</title>
<abstract>In recent years patents have become increasingly important for businesses to protect their intellectual capital and as a valuable source of information. Patent information is, however, not employed to its full potential and the interpretation of structured and unstructured patent information in large volumes remains a challenge. We address this by proposing an integrated interdisciplinary approach that uses natural language processing and machine learning techniques to formalize multilingual patent information in an ontology. The ontology further contains patent and domain specific knowledge, which allows for aligning patents with technological fields of interest and other business-related artifacts. Our empirical evaluation shows that for categorizing patents according to well-known technological fields of interest, the approach achieves high accuracy with selected feature sets compared to related work focussing on monolingual patents. We further show that combining OWL RL reasoning with SPARQL querying over the patent knowledge base allows for answering complex business queries and illustrate this with real-world use cases from the automotive domain.</abstract>
<year>2016</year>
<isbn>9781509042395</isbn>
<DOI>10.1109/SSCI.2016.7849943</DOI>
<booktitle>Proceedings of the 7th IEEE Symposium Series on Computational Intelligence (SSCI'16)</booktitle>
<publisher>IEEE Computer Society</publisher>
<address>Red Hook, United States</address>
<editor>Jin, Yaochu and Kollias, Stefanos</editor>
<pages>1-8</pages>
<keywords>Computational Intelligence;Computational Linguistics;Corporate Strategy;Data Mining;Decision Making;Information Extraction;Information Retrieval;Knowledge Graph;Knowledge Representation;Machine Learning;Natural Language Processing;Patent Analysis;Reasoning;Semantic Analysis;Semantic Technologies</keywords>
<tags>AutomatedReasoning,KnowledgeModelling</tags>
<web_url>http://ieeexplore.ieee.org/document/7849943/</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2016/UlGl16a.pdf</file_url>
<authors>
<person>
<fn>Klaus</fn>
<sn>Ulmschneider</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>GlSt2016b</citeid>
<title>Special Issue on Semantic Web</title>
<year>2016</year>
<issn>1610-1987</issn>
<DOI>10.1007/s13218-016-0430-3</DOI>
<journal>KI - Künstliche Intelligenz</journal>
<volume>30</volume>
<pages>113--115</pages>
<number>2</number>
<keywords>Reasoning, Description Logics, Semantic Web</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://dx.doi.org/10.1007/s13218-016-0430-3</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2016/GlSt2016b.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Heiner</fn>
<sn>Stuckenschmidt</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>PMGG16a</citeid>
<title>The OWL Reasoner Evaluation (ORE) 2015 Resources</title>
<year>2016</year>
<booktitle>Proceedings of the 15th International Semantic Web Conference (ISWC 2016)</booktitle>
<volume>9982</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<editor>Paul T. Groth and Elena Simperl and Alasdair J. G. Gray and Marta Sabou and Markus Krötzsch and Freddy Lécué and Fabian Flöck and Yolanda Gil</editor>
<pages>159--167</pages>
<keywords>Benchmarking, Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://link.springer.com/chapter/10.1007%2F978-3-319-46547-0_17</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2016/PMGG16a.pdf</file_url>
<note>Best Resource Track Paper Award</note>
<authors>
<person>
<fn>Bijan</fn>
<sn>Parsia</sn>
</person>
<person>
<fn>Nicolas</fn>
<sn>Matentzoglu</sn>
</person>
<person>
<fn>Rafael S.</fn>
<sn>Goncalves</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>BrGl15a</citeid>
<title>Breaking the Black Box - Using Background Knowledge for Efficient Stream Reasoning</title>
<abstract>Current approaches to stream reasoning neglect knowledge about the system as a whole. We present first steps towards self-describing streams by outlining a possible definition of the data produced by differ- ent streams. We give an outlook on future paths and how such descrip- tions can be used to improve reasoning about the streamed data.</abstract>
<year>2015</year>
<month>9</month>
<booktitle>Proceedings of the International Symposium on Companion Technology (ISCT 2015)</booktitle>
<tags>SFB-TRR-62,AutomatedReasoning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/BrGl15a.pdf</file_url>
<authors>
<person>
<fn>Markus</fn>
<sn>Brenner</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Behnke15MIPDiscussion</citeid>
<title>A Unified Knowledge Base for Companion-Systems - A Case Study in Mixed-Initiative Planning</title>
<abstract>Companion systems aim to extend the abilities of ordinary technical systems, for instance by modeling the user's situation, by recognizing the user's intentions, and by being able to interact with the user and to adapt to her/him. Such a system depends on planning capabilities to determine which actions are necessary to achieve a particular goal. In many situations it may not be appropriate for a companion system to develop plans on its own, but instead it has to integrate the user while creating the plan, i.e., it needs to be mixed-initiative. Based on earlier work, we demonstrate how a central knowledge base for a mixed-initiative planning system can be designed. We outline various benefts our approach brings  to bear within a companion system. Lastly, we present several requests a user might issue towards the mixed-initiative planning system and how they can be answered by harnessing the knowledge base.</abstract>
<year>2015</year>
<booktitle>Proceedings of the First International Symposium on Companion Technology (ISCT 2015)</booktitle>
<pages>43--48</pages>
<event_name>First International Symposium on Companion Technology (ISCT 2015)</event_name>
<event_place>Ulm, Germany</event_place>
<tags>SFB-TRR-62,Planning,AutomatedReasoning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/Behnke15MIPDiscussion.pdf</file_url>
<authors>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Denis</fn>
<sn>Ponomaryov</sn>
</person>
<person>
<fn>Florian</fn>
<sn>Nothdurft</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Wolfgang</fn>
<sn>Minker</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>Behnke2015Coherence</citeid>
<title>Coherence Across Components in Cognitive Systems – One Ontology to Rule Them All</title>
<abstract>The integration of the various specialized components of cognitive systems poses a challenge, in particular for those architectures that combine planning, inference, and human-computer interaction (HCI). An approach is presented that exploits a single source of common knowledge contained in an ontology. Based upon the knowledge contained in it, specialized domain models for the cognitive systems’ components can be generated automatically. Our integration targets planning in the form of hierarchical planning, being well-suited for HCI as it mimics planning done by humans. We show how the hierarchical structures of such planning domains can be (partially) inferred from declarative background knowledge. The same ontology furnishes the structure of the interaction between the cognitive system and the user. First, explanations of plans presented to users are enhanced by ontology explanations. Second, a dialog domain is created from the ontology coherent with the planning domain. We demonstrate the application of our technique in a fitness training scenario.</abstract>
<year>2015</year>
<booktitle>Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2015)</booktitle>
<publisher>AAAI Press</publisher>
<pages>1442-1449</pages>
<event_name>IJCAI 2015</event_name>
<event_place>Buenos Aires</event_place>
<tags>SFB-TRR-62,Planning,AutomatedReasoning</tags>
<web_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/Behnke15IJCAI-poster.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/BPSB15a.pdf</file_url>
<authors>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Denis</fn>
<sn>Ponomaryov</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Florian</fn>
<sn>Nothdurft</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>StGL15a</citeid>
<title>Completion Graph Caching for Expressive Description Logics</title>
<year>2015</year>
<booktitle>Proceedings of the 28th International Workshop on Description Logics (DL 2015)</booktitle>
<publisher>CEUR Workshop Proceedings</publisher>
<tags>AutomatedReasoning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/StGL15a.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>BBBGPS2015OntologiesAndPlanning</citeid>
<title>Integrating Ontologies and Planning for Cognitive Systems</title>
<abstract>We present an approach for integrating ontological reasoning and planning within cognitive systems. Patterns and mechanisms that suitably link planning domains and interrelated knowledge in an ontology are devised. In particular, this enables the use of (standard) ontology reasoning for extending a (hierarchical) planning domain. Furthermore, explanations of plans generated by a cognitive system benefit from additional explanations relying on background knowledge in the ontology and inference. An application of this approach in the domain of fitness training is presented.</abstract>
<year>2015</year>
<booktitle>Proceedings of the 28th International Workshop on Description Logics (DL 2015)</booktitle>
<publisher>CEUR Workshop Proceedings</publisher>
<tags>AutomatedReasoning, Planning, SFB-TRR-62</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/BBBG15a.pdf</file_url>
<authors>
<person>
<fn>Gregor</fn>
<sn>Behnke</sn>
</person>
<person>
<fn>Pascal</fn>
<sn>Bercher</sn>
</person>
<person>
<fn>Susanne</fn>
<sn>Biundo</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Denis</fn>
<sn>Ponomaryov</sn>
</person>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GKKS14a</citeid>
<title>Lower and Upper Bounds for SPARQL Queries over OWL Ontologies</title>
<year>2015</year>
<booktitle>Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI 2015)</booktitle>
<publisher>AAAI Press</publisher>
<keywords>Description Logics, Query Answering, Semantic Web, SPARQL</keywords>
<tags>AutomatedReasoning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/GKKS15a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Ilianna</fn>
<sn>Kollia</sn>
</person>
<person>
<fn>Giorgos</fn>
<sn>Stamou</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GKKS15b</citeid>
<title>Lower and Upper Bounds for SPARQL Queries over OWL Ontologies</title>
<year>2015</year>
<booktitle>Proceedings of the 28th International Workshop on Description Logics (DL 2015)</booktitle>
<publisher>CEUR Workshop Proceedings</publisher>
<keywords>Description Logics, Query Answering, Semantic Web, SPARQL</keywords>
<tags>AutomatedReasoning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/GKKS15a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Ilianna</fn>
<sn>Kollia</sn>
</person>
<person>
<fn>Giorgos</fn>
<sn>Stamou</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>UMGM15a</citeid>
<title>On Maintaining Semantic Networks: Challenges, Algorithms, Use Cases</title>
<year>2015</year>
<DOI>10.1108/IJWIS-04-2015-0014</DOI>
<journal>International Journal of Web Information Systems</journal>
<volume>11</volume>
<pages>291-326</pages>
<number>3</number>
<tags>AutomatedReasoning</tags>
<web_url>http://dx.doi.org/10.1108/IJWIS-04-2015-0014</web_url>
<authors>
<person>
<fn>Klaus</fn>
<sn>Ulmschneider</sn>
</person>
<person>
<fn>Bernd</fn>
<sn>Michelberger</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Bela</fn>
<sn>Mutschler</sn>
</person>
<person>
<fn>Manfred</fn>
<sn>Reichert</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>StGl15b</citeid>
<title>Pay-As-You-Go Description Logic Reasoning by Coupling Tableau and Saturation Procedures</title>
<year>2015</year>
<DOI>10.1613/jair.4897</DOI>
<journal>Journal of Artificial Intelligence Research</journal>
<volume>54</volume>
<pages>535--592</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>SFB-TRR-62,AutomatedReasoning</tags>
<web_url>http://jair.org/media/4897/live-4897-9009-jair.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/StGl15b.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>DBLP:conf/semweb/ParsiaMGGS15</citeid>
<title>The OWL Reasoner Evaluation (ORE) 2015 Competition Report</title>
<year>2015</year>
<booktitle>Proceedings of the 11th International Workshop on Scalable Semantic Web Knowledge Base Systems co-located with 14th International Semantic Web Conference (ISWC 2015)</booktitle>
<volume>1457</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<editor>Thorsten Liebig and Achille Fokoue</editor>
<pages>2-15</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2015/PMGG15a.pdf</file_url>
<authors>
<person>
<fn>Bijan</fn>
<sn>Parsia</sn>
</person>
<person>
<fn>Nicolas</fn>
<sn>Matentzoglu</sn>
</person>
<person>
<fn>Rafael S.</fn>
<sn>Goncalves</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GKLT14a</citeid>
<title>Abstraction Refinement for Ontology Materialization</title>
<year>2014</year>
<booktitle>Proceedings of the 27th International Workshop on Description Logics (DL 2014)</booktitle>
<volume>1193</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<pages>180-195</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-1193/paper_6.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2014/GKLT14a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
<person>
<fn>Trung-Kien</fn>
<sn>Tran</sn>
</person>
<person>
<fn>Vincent</fn>
<sn>Vialard</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GKLT14b</citeid>
<title>Abstraction Refinement for Ontology Materialization</title>
<year>2014</year>
<DOI>10.1007/978-3-319-11915-1_12</DOI>
<booktitle>Proceedings of the 13th International Semantic Web Conference (ISWC 2014)</booktitle>
<volume>8797</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<pages>180-195</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://link.springer.com/chapter/10.1007%2F978-3-319-11915-1_12</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2014/GKLT14b.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
<person>
<fn>Trung-Kien</fn>
<sn>Tran</sn>
</person>
<person>
<fn>Vincent</fn>
<sn>Vialard</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>StGL14a</citeid>
<title>Coupling Tableau Algorithms for Expressive Description Logics with Completion-based Saturation Procedures</title>
<year>2014</year>
<DOI>10.1007/978-3-319-08587-6_35</DOI>
<booktitle>Proceedings of the 7th International Joint Conference on Automated Reasoning (IJCAR 2014)</booktitle>
<volume>8562</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<editor>Stéphane Demri, Deepak Kapur and Christoph Weidenbach</editor>
<pages>449-463</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://link.springer.com/chapter/10.1007/978-3-319-08587-6_35#</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2014/StGL14a.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>GHMS14a</citeid>
<title>HermiT: An OWL 2 Reasoner</title>
<year>2014</year>
<DOI>10.1007/s10817-014-9305-1</DOI>
<journal>Journal of Automated Reasoning (JAR)</journal>
<volume>53</volume>
<pages>245-269</pages>
<number>3</number>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://link.springer.com/article/10.1007%2Fs10817-014-9305-1</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2014/GHMS14a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Ian</fn>
<sn>Horrocks</sn>
</person>
<person>
<fn>Boris</fn>
<sn>Motik</sn>
</person>
<person>
<fn>Giorgos</fn>
<sn>Stoilos</sn>
</person>
<person>
<fn>Zhe</fn>
<sn>Wang</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>StLG14a</citeid>
<title>Konclude: System Description</title>
<year>2014</year>
<journal>Journal of Web Semantics: Science, Services and Agents on the World Wide Web</journal>
<volume>27</volume>
<number>1</number>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://www.websemanticsjournal.org/index.php/ps/article/view/366/388</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2014/StLG14a.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>MUGM14a</citeid>
<title>Maintaining Semantic Networks: Challenges and Algorithms</title>
<year>2014</year>
<booktitle>Proceedings of the 16th International Conference on Information Integration and Web-Based Applications &amp; Services (iiWAS 2014)</booktitle>
<publisher>ACM</publisher>
<series>ACM International Conference Proceedings</series>
<keywords>Semantic Networks</keywords>
<tags>AutomatedReasoning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2014/MUGM14a.pdf</file_url>
<authors>
<person>
<fn>Bernd</fn>
<sn>Michelberger</sn>
</person>
<person>
<fn>Klaus</fn>
<sn>Ulmschneider</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Bela</fn>
<sn>Mutschler</sn>
</person>
<person>
<fn>Manfred</fn>
<sn>Reichert</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>StGL14b</citeid>
<title>Optimised Absorption for Expressive Description Logics</title>
<year>2014</year>
<booktitle>Proceedings of the 27th International Workshop on Description Logics (DL 2014)</booktitle>
<volume>1193</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<editor>Meghyn Bienvenu, Magdalena Ortiz, Riccardo Rosati, and Mantas Simkus</editor>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-1193/paper_49.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2014/StGL14b.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>StGL14c</citeid>
<title>Reasoning with Nominal Schemas through Absorption</title>
<abstract>Nominal schemas have recently been introduced as a new approach for the integration of DL-safe rules into the Description Logic framework. The efficient processing of knowledge bases with nominal schemas remains, however, challenging. We address this by extending the well-known optimisation of absorption as well as the standard tableau calculus to directly handle the (absorbed) nominal schema axioms. We implement the resulting extension of standard tableau calculi in a novel reasoning system and we integrate further optimisations. In our empirical evaluation, we show the effect of these optimisations and we find that the proposed approach performs well even when compared to other DL reasoners with dedicated rule support.</abstract>
<year>2014</year>
<DOI>10.1007/s10817-014-9310-4</DOI>
<journal>Journal of Automated Reasoning</journal>
<volume>53</volume>
<publisher>Springer-Verlag</publisher>
<pages>351-405</pages>
<number>4</number>
<keywords>Nominal Schema, Reasoning, Description Logics, Tableau, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://link.springer.com/article/10.1007/s10817-014-9310-4</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2014/StGL14c.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>KoGl13a</citeid>
<title>Optimizing SPARQL Query Answering over OWL Ontologies</title>
<abstract>The SPARQL query language is currently being extended by the World Wide Web Consortium (W3C) with so-called entailment regimes. An entailment regime defines how queries are evaluated under more expressive semantics than SPARQL's standard simple entailment, which is based on sub-graph matching. The queries are very expressive since variables can occur within complex class expressions and can also bind to class or property names.In this paper, we describe a sound and complete algorithm for the OWL Direct Semantics entailment regime. We further propose several novel optimizations such as strategies for determining a good query execution order, query rewriting techniques, and show how specialized OWL reasoning tasks and the class and property hierarchy can be used to reduce the query execution time. For determining a good execution order, we propose a cost-based model, where the costs are based on information about the instances of classes and properties that are extracted from a model abstraction built by an OWL reasoner. We present two ordering strategies: a static and a dynamic one. For the dynamic case, we improve the performance by exploiting an individual clustering approach that allows for computing the cost functions based on one individual sample from a cluster.We provide a prototypical implementation and evaluate the efficiency of the proposed optimizations. Our experimental study shows that the static ordering usually outperforms the dynamic one when accurate statistics are available. This changes, however, when the statistics are less accurate, e.g., due to non-deterministic reasoning decisions. For queries that go beyond conjunctive instance queries we observe an improvement of up to three orders of magnitude due to the proposed optimizations.</abstract>
<year>2013</year>
<month>9</month>
<DOI>10.1613/jair.3872</DOI>
<journal>Journal of Artificial Intelligence Research (JAIR)</journal>
<volume>48</volume>
<pages>253-303</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>SFB-TRR-62,AutomatedReasoning</tags>
<web_url>https://www.jair.org/media/3872/live-3872-7402-jair.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2013/KoGl13a.pdf</file_url>
<authors>
<person>
<fn>Ilianna</fn>
<sn>Kollia</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>StGL13b</citeid>
<title>Extending Absorption to Nominal Schemas</title>
<abstract>Nominal schemas have recently been introduced as a new approach for the integration of DL-safe rules into the Description Logic framework. The efficient processing of knowledge bases with nominal schemas remains, however, challenging. We address this by extending the well-known optimisation of absorption \hlas well as the standard tableau calculus to directly handle the (absorbed) nominal schema axioms. We implement the resulting extension of standard tableau calculi in a novel reasoning system and we integrate further optimisations. In our empirical evaluation, we show the effect of these optimisations and we find that the proposed approach performs well even when compared to other DL reasoners with dedicated rule support.</abstract>
<year>2013</year>
<booktitle>Proceedings of the 26th International Description Logic Workshop (DL 2013)</booktitle>
<publisher>CEUR Workshop Proceedings</publisher>
<keywords>Nominal Schema, Reasoning, Description Logics, Tableau, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-1014/paper_20.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2013/StGL13b.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>CTSG13a</citeid>
<title>Introducing a New Scalable Data-as-a-Service Cloud Platform for Enriching Traditional Text Mining Techniques by Integrating Ontology Modelling and Natural Language Processing</title>
<year>2013</year>
<booktitle>Proceedings of the International Workshop on Big Web Data (BigWebData 2013)</booktitle>
<publisher>Springer</publisher>
<series>Lecture Notes in Computer Science</series>
<editor>Axel Tenschert and Alexey Cheptsov</editor>
<keywords>Big Data, Text Mining, Ontologies</keywords>
<tags>AutomatedReasoning</tags>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2013/CTSG13a.pdf</file_url>
<authors>
<person>
<fn>Alexey</fn>
<sn>Cheptsov</sn>
</person>
<person>
<fn>Axel</fn>
<sn>Tenschert</sn>
</person>
<person>
<fn>Paul</fn>
<sn>Schmidt</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Mauricio</fn>
<sn>Matthesius</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>StGL13a</citeid>
<title>Nominal Schema Absorption</title>
<abstract>Nominal schemas have recently been introduced as a new approach for the integration of DL-safe rules into the Description Logic framework. The efficient processing of knowledge bases with nominal schemas remains, however, challenging. We address this by extending the well-known optimisation of absorption as well as the standard tableau calculus to directly handle the (absorbed) nominal schema axioms. We implement the resulting extension of standard tableau calculi in a novel reasoning system and we integrate further optimisations. In our empirical evaluation, we show the effect of these optimisations and we find that the proposed approach performs well even when compared to other DL reasoners with dedicated rule support.</abstract>
<year>2013</year>
<booktitle>Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013)</booktitle>
<publisher>AAAI Press/The MIT Press</publisher>
<keywords>Nominal Schema, Reasoning, Description Logics, Tableau, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://www.aaai.org/ocs/index.php/IJCAI/IJCAI13/paper/view/6629</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2013/StGL13a.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>CGHM13a</citeid>
<title>The Energy Management Adviser at EDF</title>
<abstract>The EMA (Energy Management Adviser) aims to produce personalised energy saving advice for EDF’s customers. The advice takes the form of one or more ``tips&quot;, and personalisation is achieved using semantic technologies: customers are described using RDF, an OWL ontology provides a conceptual model of the relevant domain (housing, environment, and so on) and the different kinds of tips, and SPARQL query answering is used to identify relevant tips. The current prototype provides tips to more than 300,000 EDF customers in France at least twice a year. The main challenges for our future work include providing a timely service for all of the 35 million EDF customers in France, simplifying the system's maintenance, and providing new ways for interacting with customers such as via a Web site.</abstract>
<year>2013</year>
<DOI>10.1007/978-3-642-41338-4_4</DOI>
<booktitle>Proceedings of the 12th International Semantic Web Conference (ISWC 2013)</booktitle>
<volume>8219</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<pages>49-64</pages>
<keywords>OWL, Description Logics, Explanations, Justifications</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://link.springer.com/chapter/10.1007%2F978-3-642-41338-4_4</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2013/CGHM13a.pdf</file_url>
<authors>
<person>
<fn>Pierre</fn>
<sn>Chaussecourte</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Ian</fn>
<sn>Horrocks</sn>
</person>
<person>
<fn>Boris</fn>
<sn>Motik</sn>
</person>
<person>
<fn>Laurent</fn>
<sn>Pierre</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>SG13</citeid>
<title>Towards Explicative Inference for OWL</title>
<abstract>Automated reasoning in OWL is capable of inferences that are nontrivial for people to understand. We argue that the understanding of inferences would benefit from stepwise explanations. To build a system that supports such explicative inference, we propose a framework based on inference rules and proof tactics for OWL ontologies. In particular, the goal is to present inferences in a suitable and adaptable way to human users, and to predict whether certain inferences are harder to understand than others. This article outlines the conception of this framework and its benefits whose implementation is currently work in progress.</abstract>
<year>2013</year>
<booktitle>Proceedings of the 2013 International Description Logic Workshop (DL 2013)</booktitle>
<publisher>CEUR Workshop Proceedings</publisher>
<keywords>OWL, Description Logics, Explanations, Justifications</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-1014/paper_36.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2013/ScGl13a.pdf</file_url>
<authors>
<person>
<fn>Marvin R. G.</fn>
<sn>Schiller</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GKKS13a</citeid>
<title>Using the TBox to Optimise SPARQL Queries</title>
<abstract>We present an approach for using schema knowledge from the TBox to optimize the evaluation of SPARQL queries. The queries are evaluated over an OWL ontology using the OWL Direct Semantics entailment regime. For conjunctive instance queries, we proceed by transforming the query into an ABox. We then show how the TBox and this (small) query ABox can be used to build a maximal equivalent query where the additional query atoms can be used for reducing the set of possible mappings for query variables. We also consider arbitrary SPARQL queries and show how the concept and role hierarchies can be used to prune the search space of possible answers based on the polarity of variable occurrences in the query. We provide a prototypical implementation and evaluate the efficiency of the proposed optimizations. Our experimental study shows that the use of the proposed optimizations leads to a significant improvement in the execution times of many queries.</abstract>
<year>2013</year>
<booktitle>Proceedings of the 2013 International Description Logic Workshop (DL 2013)</booktitle>
<publisher>CEUR Workshop Proceedings</publisher>
<keywords>SPARQL, OWL, Description Logics, Query Answering, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-1014/paper_80.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2013/GKKS13a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Ilianna</fn>
<sn>Kollia</sn>
</person>
<person>
<fn>Giorgos</fn>
<sn>Stamou</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>KoGl12b</citeid>
<title>Cost Based Query Ordering over OWL Ontologies</title>
<abstract>The paper presents an approach for cost-based query planning for SPARQL queries issued over an OWL ontology using the OWL Direct Semantics entailment regime of SPARQL 1.1. The costs are based on information about the instances of classes and properties that are extracted from a model abstraction built by an OWL reasoner. A static and a dynamic algorithm are presented which use these costs to find optimal or near optimal execution orders for the atoms of a query. For the dynamic case, we exploit an individual clustering approach and compute the cost functions based only on at most one individual (sample) from each of the used clusters. We provide an experimental study which shows that, for queries for which accurate estimates are available from the beginning, the static usually outperforms the dynamic algorithm. However, when queries are issued over ontologies with disjunctive information and contain many atoms for which no accurate statistics can be extracted a-priori, then dynamic ordering is more promising. The use of cluster based sampling techniques leads to a performance improvement for queries with large intermediate result sizes.</abstract>
<year>2012</year>
<month>11</month>
<DOI>10.1007/978-3-642-35176-1_15</DOI>
<booktitle>Proceedings of the 11th International Semantic Web Conference (ISWC 2012)</booktitle>
<volume>7649</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<pages>231-246</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations</keywords>
<tags>SFB-TRR-62,AutomatedReasoning</tags>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2012/KoGl12b.pdf</file_url>
<authors>
<person>
<fn>Ilianna</fn>
<sn>Kollia</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>NiGl12a</citeid>
<title>Hitting the Sweetspot: Economic Rewriting of Knowledge Bases</title>
<abstract>In this paper, we consider the task of knowledge base extraction with its three conflicting requirements: the size of the extracted knowledge base, the size of the corresponding signature and the syntactic similarity of the extracted knowledge base with the originally given one. We demonstrate that, both, minimal module extraction and uniform interpolation, assign an absolute priority to one of these requirements, thereby limiting the possibilities to influence the other two. To account for scenarios, in which such an extreme prioritization is not necessary, we investigate the task of knowledge base extraction for EL based on two alternative, less restrictive notions of syntactic similarity with the second highest priority given to the knowledge base size. Moreover, to address scenarios, where computation time is important, we propose a tractable rewriting approach based on the chosen prioritization of requirements and empirically compare this novel technique with the existing implemented approaches with encouraging results.</abstract>
<year>2012</year>
<month>11</month>
<DOI>10.1007/978-3-642-35176-1_25</DOI>
<booktitle>Proceedings of the 11th International Semantic Web Conference (ISWC 2012)</booktitle>
<volume>7649</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<pages>394-409</pages>
<keywords>Reasoning, Description Logics, Optimisations, Optimizations, Modularisation, Modularization, Uniform Interpolation</keywords>
<tags>AutomatedReasoning</tags>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2012/NiGl12a.pdf</file_url>
<authors>
<person>
<fn>Nadeschda</fn>
<sn>Nikitina</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>GHMS11a</citeid>
<title>A Novel Approach to Ontology Classification</title>
<abstract>Ontology classification - the computation of the subsumption hierarchies for classes and properties - is a core reasoning service provided by all OWL reasoners known to us. A popular algorithm for computing the class hierarchy is the so-called Enhanced Traversal (ET) algorithm. In this paper we present a new classification algorithm that attempts to address certain shortcomings of ET and improve its performance. Apart from classification of classes, we also consider object and data property classification. Using several simple examples, we show that the algorithms commonly used to implement these tasks are incomplete even for relatively weak ontology languages. Furthermore, we show that property classification problems can be reduced to class classification problems, which allows us to classify properties using our optimised algorithm. We implemented all our algorithms in the OWL reasoner HermiT. The results of our performance evaluation show significant performance improvements on several well-known ontologies.</abstract>
<year>2012</year>
<month>7</month>
<issn>1570-8268</issn>
<DOI>10.1016/j.websem.2011.12.007</DOI>
<journal>Journal of Web Semantics: Science, Services and Agents on the World Wide Web</journal>
<volume>14</volume>
<publisher>Elsevier Science Publishers (North-Holland)</publisher>
<address>Amsterdam</address>
<pages>84-101</pages>
<keywords>Ontologies, OWL, Class Classification, Property Classification, Optimizations</keywords>
<tags>SFB-TRR-62,AutomatedReasoning</tags>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2012/GHMS12a.pdf</file_url>
<note>Special Issue on Dealing with the Messiness of the Web of Data</note>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Ian</fn>
<sn>Horrocks</sn>
</person>
<person>
<fn>Boris</fn>
<sn>Motik</sn>
</person>
<person>
<fn>Rob</fn>
<sn>Shearer</sn>
</person>
<person>
<fn>Giorgos</fn>
<sn>Stoilos</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>KoGl12a</citeid>
<title>Cost Based Query Ordering over OWL Ontologies</title>
<abstract>The paper presents an approach for cost-based query planning for SPARQL queries issued over an OWL ontology using OWL's Direct Semantics. The costs are based on information about the instances of classes and properties that are extracted from a model abstraction built by an OWL reasoner. A static and a dynamic algorithm are presented which use these costs to find optimal or near optimal execution orders for the atoms of a query. For the dynamic case, we exploit an individual clustering approach and compute the cost functions based only on at most one individual (sample) from each of the used clusters.  We provide an experimental study which shows that, for queries for which accurate estimates are available from the beginning, the static usually outperforms the dynamic algorithm. However, when queries are issued over ontologies with disjunctive information and contain many atoms for which no accurate statistics can be extracted a-priori, then dynamic ordering is more promising. The use of cluster based sampling techniques leads to a performance improvement for queries with huge intermediate result sizes.</abstract>
<year>2012</year>
<month>6</month>
<booktitle>Proceedings of the 25th International Description Logic Workshop (DL 2012)</booktitle>
<volume>846</volume>
<series>CEUR Workshop Proceedings</series>
<keywords>Reasoning, Description Logics, Tableau, Optimisations, Optimizations</keywords>
<tags>SFB-TRR-62,AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-846/paper_40.pdf</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2012/KoGl12a.pdf</file_url>
<authors>
<person>
<fn>Ilianna</fn>
<sn>Kollia</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>StLG12b</citeid>
<title>Extended Caching and Backjumping for Expressive Description Logics</title>
<abstract>With this contribution we push the boundary of some known optimisations such as caching to the very expressive Description Logic SROIQ.The developed method is based on a sophisticated dependency management and a precise unsatisfiability caching technique, which further enables better informed tableau backtracking and more efficient pruning.
We empirically evaluate the proposed optimisation within the novel reasoning system Konclude and show that the proposed optimisations indeed result in significant performance improvements.</abstract>
<year>2012</year>
<month>6</month>
<booktitle>Proceedings of the 25th International Description Logic Workshop (DL 2012)</booktitle>
<volume>846</volume>
<series>CEUR Workshop Proceedings</series>
<keywords>Reasoning, Description Logics, Tableau, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-846/paper_36.pdf</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2012/StLG12b.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>StLG12a</citeid>
<title>Extended Caching, Backjumping and Merging for Expressive Description Logics</title>
<abstract>With this contribution we push the boundary of some known optimisations such as caching to the very expressive Description Logic SROIQ.The developed method is based on a sophisticated dependency management and a precise unsatisfiability caching technique, which further enables better informed tableau backtracking and more efficient pruning. Additionally, we optimise the handling of cardinality restrictions, by introducing a strategy called pool-based merging.
We empirically evaluate the proposed optimisations within the novel reasoning system Konclude and show that the proposed optimisations indeed result in significant performance improvements.</abstract>
<year>2012</year>
<month>6</month>
<DOI>10.1007/978-3-642-31365-3_40</DOI>
<booktitle>Proceedings of the 6th International Joint Conference on Automated Reasoning (IJCAR 2012)</booktitle>
<volume>7364</volume>
<series>Lecture Notes in Computer Science</series>
<pages>514-529</pages>
<keywords>Reasoning, Description Logics, Tableau, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2012/StLG12a.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>proceedings</bibtype>
<citeid>GHKP12a</citeid>
<title>OWL: Yet to arrive on the Web of Data?</title>
<year>2012</year>
<month>4</month>
<day>16</day>
<volume>937</volume>
<publisher>CEUR Workshop Proceedings</publisher>
<event_name>Proceedings of the 5th Linked Data on the Web Workshop (LDOW2012)</event_name>
<keywords>Ontologies, OWL, Linked Data, Semantic Web</keywords>
<tags>AutomatedReasoning</tags>
<web_url>http://ceur-ws.org/Vol-937/ldow2012-paper-16.pdf</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2012/GHKP12a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Aidan</fn>
<sn>Hogan</sn>
</person>
<person>
<fn>Markus</fn>
<sn>Krötzsch</sn>
</person>
<person>
<fn>Axel</fn>
<sn>Polleres</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>NiRG11c</citeid>
<title>Interactive Ontology Revision</title>
<abstract>When ontological knowledge is acquired automatically, quality control is essential. Which part of the automatically acquired knowledge is appropriate for an application often depends on the context in which the knowledge base or ontology is used. In order to determine relevant and irrelevant or even wrong knowledge, we support the tightest possible quality assurance approach - an exhaustive manual inspection of the acquired data. By using automated reasoning, this process can be partially automatized: after each expert decision, axioms that are entailed by the already confirmed statements are automatically approved, whereas axioms that would lead to an inconsistency are declined. Starting from this consideration, this paper provides theoretical foundations, heuristics, optimization strategies and comprehensive experimental results for our approach to efficient reasoning-supported interactive ontology revision. We introduce and elaborate on the notions of revision states and revision closure as formal foundations of our method. Additionally, we propose a notion of axiom impact which is used to determine a beneficial order of axiom evaluation in order to further increase the effectiveness of ontology revision. The initial notion of impact is then further refined to take different validity ratios - the proportion of valid statements within a dataset - into account. Since the validity ratio is generally not known a priori - we show how one can work with an estimate that is continuously improved over the course of the inspection process.Finally, we develop the notion of decision spaces, which are structures for calculating and updating the revision closure and axiom impact. We optimize the computation performance further by employing partitioning techniques and provide an implementation supporting these optimizations as well as featuring a user front-end. Our evaluation shows that our ranking functions almost achieve the maximum possible automatization and that the computation time needed for each reasoning-based, automatic decision takes less than one second on average for our test dataset of over 25,000 statements.</abstract>
<year>2012</year>
<month>4</month>
<issn>1570-8268</issn>
<DOI>10.1016/j.websem.2011.12.002</DOI>
<journal>Journal of Web Semantics: Science, Services and Agents on the World Wide Web</journal>
<volume>12-13</volume>
<publisher>Elsevier Science Publishers (North-Holland), Amsterdam</publisher>
<pages>118-130</pages>
<keywords>Ontologies, Knowledge Representation, Automated Reasoning, Quality Assurance, OWL</keywords>
<tags>SFB-TRR-62,AutomatedReasoning</tags>
<web_url>http://www.sciencedirect.com/science/article/pii/S1570826811001028</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2012/NiRG12a.pdf</file_url>
<note>Special Issue on Reasoning with Context in the Semantic Web</note>
<authors>
<person>
<fn>Nadeschda</fn>
<sn>Nikitina</sn>
</person>
<person>
<fn>Sebastian</fn>
<sn>Rudolph</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>techreport</bibtype>
<citeid>StLG12c</citeid>
<title>Extended Caching, Backjumping and Merging for Expressive Description Logics</title>
<abstract>With this contribution we push the boundary of some known optimisations such as caching to the very expressive Description Logic SROIQ.The developed method is based on a sophisticated dependency management and a precise unsatisfiability caching technique, which further enables better informed tableau backtracking and more efficient pruning. Additionally, we optimise the handling of cardinality restrictions, by introducing a strategy called pool-based merging.We empirically evaluate the proposed optimisations within the novel reasoning system Konclude and show that the proposed optimisations indeed result in significant performance improvements.</abstract>
<year>2012</year>
<institution>University of Ulm</institution>
<number>TR-2012-01</number>
<keywords>Reasoning, Description Logics, Tableau, Optimisations, Optimizations</keywords>
<tags>AutomatedReasoning</tags>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui/Ulmer_Informatik_Berichte/2012/UIB-2012-01.pdf</file_url>
<authors>
<person>
<fn>Andreas</fn>
<sn>Steigmiller</sn>
</person>
<person>
<fn>Thorsten</fn>
<sn>Liebig</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>KoGH11b</citeid>
<title>Answering Queries over OWL Ontologies with SPARQL</title>
<abstract>W3C currently extends the SPARQL query language with so-called entailment regimes, which define how queries are evaluated using logical entailment relations. We describe a sound and complete algorithm for the OWL Direct Semantics entailment regime. Since OWL’s Direct Semantics is based on Description Logics (DLs), this results in an expressive query language for DL knowledge bases. The query language differs from the commonly studied conjunctive queries in that it only has distinguished variables. Furthermore, variables can occur within complex concepts and can also bind to concept or role names. We provide a prototypical implementation and propose several novel optimizations strategies.We evaluate the efficiency of the proposed optimizations and find that for ABox queries our system performs comparably to already deployed systems. For complex queries an improvement of up to three orders of magnitude can be observed.</abstract>
<year>2011</year>
<booktitle>Proceedings of the 8th International Workshop on OWL: Experiences and Directions (OWLED 2011)</booktitle>
<volume>796</volume>
<publisher>CEUR Workshop Proceedings</publisher>
<web_url>http://ceur-ws.org/Vol-796/owled2011_submission_4.pdf</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2011/KoGH11b.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>KoGH11c</citeid>
<title>Query Answering over SROIQ Knowledge Bases with SPARQL</title>
<abstract>W3C currently extends the SPARQL query language with so-called entailment regimes, which define how queries are evaluated using logical entailment relations. We describe a sound and complete algorithm for the OWL Direct Semantics entailment regime. Since OWL’s Direct Semantics is based on Description Logics (DLs), this results in an expressive query language for DL knowledge bases. The query language differs from the commonly studied conjunctive queries in that it only has distinguished variables. Furthermore, variables can occur within complex concepts and can also bind to concept or role names. We provide a prototypical implementation and propose several novel optimizations strategies. We evaluate the efficiency of the proposed optimizations and find that for ABox queries our system performs comparably to already deployed systems. For complex queries an improvement of up to three orders of magnitude can be observed.</abstract>
<year>2011</year>
<booktitle>Proceedings of the 2011 International Workshop on Description Logic (DL 2011)</booktitle>
<volume>745</volume>
<publisher>CEUR Workshop Proceedings</publisher>
<web_url>http://ceur-ws.org/Vol-745/paper_27.pdf</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2011/KoGH11c.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inbook</bibtype>
<citeid>Glimm11a</citeid>
<title>Reasoning Web 2011</title>
<abstract>This chapter accompanies the lecture on SPARQL with entailment regimes at the 7th Reasoning Web Summer School in Galway, Ireland, 2011. SPARQL is a query language and protocol for data specified in the Resource Description format (RDF). The basic evaluation mechanism for SPARQL queries is based on subgraph matching. The query criteria are given in the form of RDF triples possibly with variables in place of the subject, object, or predicate of a triple, called basic graph patterns. Each instantiation of the variables that yields a subgraph of the queried RDF graph constitutes a solution. The query language further contains capabilities for querying for optional basic graph patterns, alternative graph patterns etc. We first introduce the main features of SPARQL as a query language. In order to define the semantics of a query, we show how a query can be translated to an abstract query, which can then be evaluated according to SPARQL’s query evaluation mechanism. Apart from the features of SPARQL 1.0, we also briefly introduce the new features of SPARQL 1.1, which is currently being developed by the Data Access Working Group of the World Wide Web Consortium. In the second part of these notes, we introduce SPARQL’s extension point for basic graph pattern matching. We illustrate how this extension point can be used to define a semantics for basic graph pattern evaluation based on more elaborate semantics such as RDF Schema (RDFS) entailment or OWL entailment. This allows for solutions to a query that implicitly follow from an RDF graph, but which are not necessarily explicitly present. We illustrate what constitutes an extension point and how problems that arise from using a semantic entailment relation can be addressed. We first introduce SPARQL in combination with the RDFS entailment relation and then move on to the more expressive Web Ontology Language OWL.We cover OWL’s Direct Semantics, which is based on Description Logics, and the RDF-Based Semantics,</abstract>
<year>2011</year>
<DOI>10.1007/978-3-642-23032-5_3</DOI>
<volume>6848</volume>
<publisher>Springer-Verlag</publisher>
<chapter>Using SPARQL with RDFS and OWL Entailment</chapter>
<series>Lecture Notes in Computer Science</series>
<pages>137-201</pages>
<web_url>http://www.springerlink.com/content/f631487023034527/fulltext.pdf</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2011/Glim11a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>NiRG11a</citeid>
<title>Reasoning-Supported Interactive Revision of Knowledge Bases</title>
<abstract>Quality control is an essential task within ontology development projects, especially when the knowledge formalization is partially automatized. We propose a method for integrating newly acquired, possibly low-quality axioms into an existing ontology. During the process, some of the newly acquired axioms have to be inspected manually; based on the decision whether the axiom is desired or not, several of the yet unevaluated axioms are evaluated automatically. Since the evaluation order can significantly increase the amount of automization, we further propose the notion of axiom impact. Finally, we introduce decision spaces as structures to efficiently compute the axiom impact and the implicit evaluation decisions. Compared to a na¨ıve implementation, this reduces the number of costly reasoning operations on average by 75%.</abstract>
<year>2011</year>
<booktitle>Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011)</booktitle>
<volume>745</volume>
<publisher>AAAI Press/The MIT Press</publisher>
<web_url>http://www.aaai.org/ocs/index.php/IJCAI/IJCAI11/paper/view/2998</web_url>
<file_url>http://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2011/NiRG11a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GliKazLut:11:QIO:DL</citeid>
<title>Status QIO: An Update</title>
<abstract>We prove that conjunctive query answering in the description logic ALCOIF is co-N2ExpTime-hard, thus improving the previously known 2ExpTime lower bound. The result transfers to OWL DL and OWL2 DL, of which ALCOIF is an important fragment. A matching upper bound remains open.</abstract>
<year>2011</year>
<booktitle>Description Logics</booktitle>
<volume>745</volume>
<publisher>CEUR-WS.org</publisher>
<series>CEUR Workshop Proceedings</series>
<editor>Riccardo Rosati and Sebastian Rudolph and Michael Zakharyaschev</editor>
<tags>KnowledgeModeling</tags>
<web_url>http://ceur-ws.org/Vol-745/paper_44.pdf</web_url>
<file_url>fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2011/GliKazLut11QIO_DL.pdf</file_url>
<authors>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
<person>
<fn>Carsten</fn>
<sn>Lutz</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>NiGR11a</citeid>
<title>Wheat and Chaff - Practically Feasible Interactive Ontology Revision</title>
<abstract>When ontological knowledge is acquired automatically, quality control is essential. We consider the tightest possible approach - an exhaustive manual inspection of the acquired data. By using automated reasoning, we partially automate the process: after each expert decision, axioms that are entailed by the already approved statements are automatically approved, whereas axioms that would lead to an inconsistency are declined. Adequate axiom ranking strategies are essential in this setting to minimize the amount of expert decisions. In this paper, we present a generalization of the previously proposed ranking techniques which works well for arbitrary validity ratios - the proportion of valid statements within a dataset - whereas the previously described ranking functions were either tailored towards validity ratios of exactly 100% and 0% or were optimizing the worst case. The validity ratio - generally not known a priori - is continuously estimated over the course of the inspection process. We further employ partitioning techniques to significantly reduce the computational effort. We provide an implementation supporting all these optimizations as well as featuring a user front-end for successive axiom evaluation, thereby making our proposed strategy applicable to practical scenarios. This is witnessed by our evaluation showing that the novel parameterized ranking function almost achieves the maximum possible automation and that the computation time needed for each reasoning-based, automatic decision is reduced to less than one second on average for our test dataset of over 25,000 statements.</abstract>
<year>2011</year>
<DOI>10.1007/978-3-642-25073-6_31</DOI>
<booktitle>Proceedings of the 10th International Semantic Web Conference (ISWC 2011)</booktitle>
<volume>7031</volume>
<publisher>Springer-Verlag</publisher>
<pages>487-503</pages>
<tags>AutomatedReasoning</tags>
<web_url>http://www.springerlink.com/content/r51v2xn6188kv4m2/</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2011/NiGR11a.pdf</file_url>
<authors>
<person>
<fn>Nadeschda</fn>
<sn>Nikitina</sn>
</person>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Sebastian</fn>
<sn>Rudolph</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>techreport</bibtype>
<citeid>GlRV10b</citeid>
<title>Integrated Metamodeling and Diagnosis in OWL 2</title>
<abstract>Ontological metamodeling has a variety of applications yet only very restricted forms are supported by OWL 2 directly. We propose a novel encoding scheme enabling class-based metamodeling inside the domain ontology with full reasoning support through standard OWL 2 reasoning systems. We demonstrate the usefulness of our method by applying it to the OntoClean methodology. En passant, we address performance problems arising from the inconsistency diagnosis strategy originally proposed for OntoClean by introducing an alternative technique where sources of conflicts are indicated by means of marker predicates.</abstract>
<year>2010</year>
<DOI>10.1007/978-3-642-17746-0_17</DOI>
<institution>Institut AIFB, KIT</institution>
<booktitle>Proceedings of the 9th International Semantic Web Conference (ISWC 2010)</booktitle>
<volume>6414</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<pages>257-272</pages>
<number>3006</number>
<web_url>http://www.springerlink.com/content/t227034122234502/</web_url>
<file_url>http://www.aifb.kit.edu/images/a/a4/TR-GRV-MEtamodelling.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>RuGl10a</citeid>
<title>Nominals, Inverses, Counting, and Conjunctive Queries or: Why Infinity is your Friend!</title>
<abstract>Description Logics are knowledge representation formalisms that provide, for example, the logical underpinning of the W3C OWL standards. Conjunctive queries, the standard query language in databases, have recently gained significant attention as an expressive formalism for querying Description Logic knowledge bases. Several different techniques for deciding conjunctive query entailment are available for a wide range of DLs. Nevertheless, the combination of nominals, inverse roles, and number restrictions in OWL 1 and OWL 2 DL causes unsolvable problems for the techniques hitherto available. We tackle this problem and present a decidability result for entailment of unions of conjunctive queries in the DL ALCHOIQb that contains all three problematic constructors simultaneously. Provided that queries contain only simple roles, our result also shows decidability of entailment of (unions of) conjunctive queries in the logic that underpins OWL 1 DL and we believe that the presented results will pave the way for further progress towards conjunctive query entailment decision procedures for the Description Logics underlying the OWL standards.</abstract>
<year>2010</year>
<DOI>10.1613/jair.3029</DOI>
<journal>Journal of Artificial Intelligence Research</journal>
<volume>39</volume>
<pages>429-481</pages>
<web_url>http://www.jair.org/media/3029/live-3029-5248-jair.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2010/RuGl10a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GHMS10a</citeid>
<title>Optimising Ontology Classification</title>
<abstract>Ontology classification - the computation of subsumption hierarchies for classes and properties - is one of the most important tasks for OWL reasoners. Based on the algorithm by Shearer and Horrocks [1], we present a new classification procedure that addresses several open issues of the original algorithm, and that uses several novel optimisations in order to achieve superior performance. We also consider the classification of (object and data) properties. We show that algorithms commonly used to implement that task are incomplete even for relatively weak ontology languages. Furthermore, we show how to reduce the property classification problem into a standard (class) classification problem, which allows reasoners to classify properties using our optimised procedure. We have implemented our algorithms in the OWL HermiT reasoner, and we present the results of a performance evaluation.</abstract>
<year>2010</year>
<DOI>10.1007/978-3-642-21034-1_26</DOI>
<booktitle>Proceedings of the 9th International Semantic Web Conference (ISWC 2010)</booktitle>
<volume>6414</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<pages>225-240</pages>
<web_url>http://www.springerlink.com/content/b6t3155821j66477/</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2010/GHMS10a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlHM10a</citeid>
<title>Optimized Description Logic Reasoning via Core Blocking</title>
<abstract>State of the art reasoners for expressive description logics, such as those that underpin the OWL ontology language, are typically based on highly optimized implementations of (hyper)tableau algorithms. Despite numerous optimizations, certain ontologies encountered in practice still pose significant challenges to such reasoners, mainly because of the size of the model abstractions that they construct. To address this problem, we propose a new blocking technique that tries to identify and halt redundant construction at a much earlier stage than standard blocking techniques. An evaluation of a prototypical implementation in the HermiT reasoner shows that our technique can dramatically reduce the size of constructed model abstractions and reduce reasoning time.</abstract>
<year>2010</year>
<DOI>10.1007/978-3-642-14203-1_39</DOI>
<booktitle>Proceedings of the International Joint Conference on Automated Reasoning (IJCAR 2010)</booktitle>
<volume>6173</volume>
<publisher>Springer-Verlag</publisher>
<series>Lecture Notes in Computer Science</series>
<pages>457-471</pages>
<web_url>http://www.springerlink.com/content/k248v45858j1101k/</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2010/GlHM10a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>techreport</bibtype>
<citeid>GHPP09b</citeid>
<title>A Syntax for Rules in OWL 2</title>
<abstract>Being able to extend an OWL ontology with some form of rules is a feature that many ontology developers consider as very important. Nevertheless, working with rules in practice can be difficult since the tool support is not as good as for handling ontologies without rules. Furthermore, the existing rule syntaxes are not very well aligned with the new OWL 2 standard. We propose, therefore, an extension to OWL 2 for representing rules, which is directly inspired by (DL Safe) SWRL rules, but uses and extends the succinct and human-readable functional-style syntax of OWL 2. We also propose an OWL/XML version of the syntax to allow for easy XML serialization. Support for parsing such rules has been added to the new OWL API 3.0 and reasoning over ontologies extended with these rules is possible with the two OWL 2 reasoners Pellet and HermiT. In HermiT, these rules can also be used in conjunction with Description Graphs.</abstract>
<year>2009</year>
<institution>The University of Oxford</institution>
<booktitle>Proceedings of the 6th International Workshop on OWL: Experiences and Directions (OWLED 2009)</booktitle>
<volume>529</volume>
<publisher>CEUR Workshop Proceedings</publisher>
<web_url>http://ceur-ws.org/Vol-529/owled2009_submission_16.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2009/GHPP09b.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlRu09a</citeid>
<title>Conjunctive Query Entailment: Decidable in Spite of O, I, and Q</title>
<year>2009</year>
<booktitle>Proceedings of the 2009 International Workshop on Description Logic (DL 2009)</booktitle>
<volume>477</volume>
<publisher>CEUR Workshop Proceedings</publisher>
<web_url>http://ceur-ws.org/Vol-477/paper_6.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2009/GlRu09a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>techreport</bibtype>
<citeid>GlKa08bb</citeid>
<title>Role Conjunctions in Expressive Description Logics</title>
<abstract>We show that adding role conjunctions to the prominent DLs SHIF and SHOIN causes a jump in the computational complexity of the standard reasoning tasks from ExpTime to 2ExpTime already for SHI and from NExpTime to N2ExpTime for SHOIF. We further show that this increase in complexity is due to a subtle interaction between inverse roles, role hierarchies, and role transitivity in the presence of role conjunctions and that for the DL SHQ a jump in the computational complexity cannot be observed.</abstract>
<year>2008</year>
<DOI>10.1007/978-3-540-89439-1_28</DOI>
<institution>The University of Oxford</institution>
<booktitle>Proceedings of the 15th International Conference on Logic for Programming and Automated Reasoning (LPAR 2008)</booktitle>
<volume>5330</volume>
<publisher>Lecture Notes in Computer Science</publisher>
<pages>391-405</pages>
<web_url>http://www.springerlink.com/content/r5641x1502220vv2/</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2008/GlKa08b.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
<person>
<fn>Yevgeny</fn>
<sn>Kazakov</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GHLS07a</citeid>
<title>Conjunctive Query Answering for the Description Logic SHIQ</title>
<abstract>Conjunctive queries play an important role as an expressive query language for Description Logics (DLs). Although modern DLs usually provide for transitive roles, it was an open problem whether conjunctive query answering over DL knowledge bases is decidable if transitive roles are admitted in the query. In this paper, we consider conjunctive queries over knowledge bases formulated in the popular DL SHIQ and allow transitive roles in both the query and the knowledge base. We show that query answering is decidable and establish the following complexity bounds: regarding combined complexity, we devise a deterministic algorithm for query answering that needs time single exponential in the size of the KB and double exponential in the size of the query. Regarding data complexity, we prove co-NP-completeness.</abstract>
<year>2007</year>
<DOI>10.1613/jair.2372</DOI>
<booktitle>Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007)</booktitle>
<journal>Journal of Artificial Intelligence Research (JAIR)</journal>
<volume>31</volume>
<pages>150-197</pages>
<web_url>http://www.aaai.org/Library/IJCAI/2007/ijcai07-062.php</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2007/GHLS07a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlHS07a</citeid>
<title>Conjunctive Query Entailment for SHOQ</title>
<abstract>An important reasoning task, in addition to the standard DL reasoning services, is conjunctive query answering. In this paper, we present a decision procedure for conjunctive query entailment in the expressive Description Logic SHOQ. This is, to the best of our knowledge, the first decision procedure for conjunctive query entailment in a logic that allows for nominals. We achieve this by combining the techniques used in the conjunctive query entailment procedure for SHIQ with the techniques proposed for a restricted class of conjunctive queries in SHOQ.</abstract>
<year>2007</year>
<booktitle>Proceedings of the 2007 International Workshop on Description Logic (DL 2007)</booktitle>
<volume>250</volume>
<publisher>CEUR Workshop Proceedings</publisher>
<web_url>http://ceur-ws.org/Vol-250/paper_63.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2007/GlHS07a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>article</bibtype>
<citeid>HoGS07a</citeid>
<title>Hybrid Logics and Ontology Languages</title>
<abstract>Description Logics (DLs) are a family of logic based knowledge representation formalisms. Although they have a range of applications, they are perhaps best known as the basis for widely used ontology languages such as OIL, DAML+OIL and OWL, the last of which is now a World Wide Web Consortium (W3C) recommendation. SHOIN, the DL underlying OWL DL (the most widely used “species” of OWL), includes familiar features from hybrid logic. In particular, in order to support extensionally defined classes, SHOIN includes nominals: classes whose extension is a singleton set. This is an important feature for a logic that is designed for use in ontology language applications, because extensionally defined classes are very common in ontologies. Binders and state variables are another feature from Hybrid Logic that would clearly be useful in an ontology language, but it is well known that adding this feature to even a relatively weak language would lead to undecidability. However, recent work has shown that this feature could play a very useful role in query answering, where the syntactic structure of queries means that the occurrence of state variables is restricted in a way that allows for decidable reasoning.</abstract>
<year>2007</year>
<DOI>10.1016/j.entcs.2006.11.022</DOI>
<journal>Electronic Notes in Theoretical Computer Science</journal>
<volume>174</volume>
<pages>3-14</pages>
<number>6</number>
<keywords>Description Logic, Hybrid Logic, Tableaux Reasoning</keywords>
<web_url>http://www.sciencedirect.com/science/article/pii/S1571066107002393</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2007/HoGS07a.pdf</file_url>
<note>Proceedings of the International Workshop on Hybrid Logic (HyLo 2006)</note>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>phdthesis</bibtype>
<citeid>Glimm07a</citeid>
<title>Querying Description Logic Knowledge Bases</title>
<abstract>Knowledge representation systems provide a mechanism for storing facts about some part of the real world in a knowledge base, inferring new knowledge based on the given facts, and querying knowledge bases. The ability to infer new knowledge is one of the distinguishing features compared to databases. Such inference services require the definition of knowledge in a language for which such inference algorithms exist, e.g., a Description Logic (DL). A DL language allows for the specification of concepts, individuals that are instances of these concepts, and roles, which are interpreted as binary relations over the individuals. Description Logics have proved useful in a wide range of applications and form the foundations of the Web Ontology Language (OWL), which is used in the Semantic Web as a means for specifying machine processable information. Despite their popularity, the query facilities provided by DL systems are still limited. Current algorithms are incomplete or impose restrictions on the types of allowed queries. In this thesis we identify sources of incompleteness in existing algorithms and present extended query procedures that eliminate the deficiencies described above. More precisely, we present query answering algorithms for unrestricted conjunctive queries for the DLs SHIQ and SHOQ—the former of which was a long standing open problem. Furthermore, the correctness of the presented algorithms is proved formally and an analysis of the theoretical complexity is given. The planned future work is targeted on optimisation techniques to improve the algorithms’ practicality. The work presented in this thesis should be of value mainly to implementors of Description Logic systems, as the presented algorithms build the theoretical foundation for implementable query answering interfaces. Additionally, the algorithms can also be used in order to extend a DL system with datalog style rules.</abstract>
<type>PhD thesis</type>
<year>2007</year>
<school>The University of Manchester</school>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2007/Glim07a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlHS06a</citeid>
<title>Conjunctive Query Answering for Description Logics with Transitive Roles</title>
<abstract>An important reasoning task, in addition to the standard DL reasoning services, is conjunctive query answering. In this paper, we present algorithms for conjunctive query answering in the expressive Description Logics SHQ and SHOQ. In particular, we allow for transitive (or nonsimple) roles in the query body, which is a feature that is not supported by other existing conjunctive query answering algorithms. For SHQ, we achieve this by extending the logic with a restricted form of # binders and state variables as known from Hybrid Logics. We also highlight, why the addition of inverse roles makes the task of finding a decision procedure for conjunctive query answering more complicated.</abstract>
<year>2006</year>
<booktitle>Proceedings of the 2006 International Workshop on Description Logic (DL 2006)</booktitle>
<volume>189</volume>
<web_url>http://ceur-ws.org/Vol-189/submission_5.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2006/GlHS06a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>techreport</bibtype>
<citeid>GHLS06a</citeid>
<title>Conjunctive Query Answering in the Description Logic SHIQ</title>
<abstract>Conjunctive queries play an important role as an expressive query language for Description Logics (DLs). Although modern DLs usually provide for transitive roles, it was an open problem whether conjunctive query answering over DL knowledge bases is decidable if transitive roles are admitted in the query. In this paper, we consider conjunctive queries over knowledge bases formulated in the popular DL SHIQ and allow transitive roles in both the query and the knowledge base. We show that query answering is decidable and establish the following complexity bounds: regarding combined complexity, we devise a deterministic algorithm for query answering that needs time single exponential in the size of the KB and double exponential in the size of the query. Regarding data complexity, we prove co-NP-completeness.</abstract>
<year>2006</year>
<institution>Chair for Automata Theory, Institute for Theoretical Computer Science, Dresden University of Technology, Germany</institution>
<number>LTCS-06-01</number>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2006/GHLS06a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlHo05a</citeid>
<title>Handling Cyclic Conjunctive Queries</title>
<year>2005</year>
<booktitle>Proceedings of the 2005 International Workshop on Description Logic (DL 2005)</booktitle>
<volume>147</volume>
<publisher>CEUR Workshop Proceedings</publisher>
<web_url>http://ceur-ws.org/Vol-147/09-Glimm.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2005/GlHo05a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
<reference>
<bibtype>inproceedings</bibtype>
<citeid>GlHo04a</citeid>
<title>Query Answering Systems in the Semantic Web</title>
<abstract>In this paper a new query answering system is presented for querying knowledge bases in the Semantic Web. The implementation follows the DAML+OIL Query Language Abstract Specification (DQL) and supports acyclic conjunctive queries. The system uses a Description Logic (DL) reasoner to answer the queries and the conjunctive queries are transformed into DL retrieval or boolean queries. After the introduction to the new DQL implementation, a comparison with other systems follows. This includes the recently introduced new Racer Query Language (nRQL), the DQL implementation provided by the Knowledge Systems Laboratory of the Stanford University and a DQL implementation provided by the University of Maryland, Baltimore County. The paper highlights and compares the different approaches of these systems.</abstract>
<year>2004</year>
<booktitle>Proceedings the of KI-2004 Workshop on Applications of Description Logics (ADL 2004)</booktitle>
<volume>115</volume>
<publisher>CEUR Workshop Proceedings</publisher>
<web_url>http://ceur-ws.org/Vol-115/03-glimm.pdf</web_url>
<file_url>https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.090/Publikationen/2004/GlHo04a.pdf</file_url>
<authors>
<person>
<fn>Birte</fn>
<sn>Glimm</sn>
</person>
</authors>
</reference>
</bib>
