11 Search Results for "Studer, Rudi"

Document
Position
DOI: 10.4230/TGDK.2.1.2
Grounding Stream Reasoning Research

Authors: Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1

Abstract
In the last decade, there has been a growing interest in applying AI technologies to implement complex data analytics over data streams. To this end, researchers in various fields have been organising a yearly event called the "Stream Reasoning Workshop" to share perspectives, challenges, and experiences around this topic. In this paper, the previous organisers of the workshops and other community members provide a summary of the main research results that have been discussed during the first six editions of the event. These results can be categorised into four main research areas: The first is concerned with the technological challenges related to handling large data streams. The second area aims at adapting and extending existing semantic technologies to data streams. The third and fourth areas focus on how to implement reasoning techniques, either considering deductive or inductive techniques, to extract new and valuable knowledge from the data in the stream. This summary is written not only to provide a crystallisation of the field, but also to point out distinctive traits of the stream reasoning community. Moreover, it also provides a foundation for future research by enumerating a list of use cases and open challenges, to stimulate others to join this exciting research area.
Cite as

Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer. Grounding Stream Reasoning Research. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 2:1-2:47, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{bonte_et_al:TGDK.2.1.2,
  author =	{Bonte, Pieter and Calbimonte, Jean-Paul and de Leng, Daniel and Dell'Aglio, Daniele and Della Valle, Emanuele and Eiter, Thomas and Giannini, Federico and Heintz, Fredrik and Schekotihin, Konstantin and Le-Phuoc, Danh and Mileo, Alessandra and Schneider, Patrik and Tommasini, Riccardo and Urbani, Jacopo and Ziffer, Giacomo},
  title =	{{Grounding Stream Reasoning Research}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:47},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.2},
  URN =		{urn:nbn:de:0030-drops-198597},
  doi =		{10.4230/TGDK.2.1.2},
  annote =	{Keywords: Stream Reasoning, Stream Processing, RDF streams, Streaming Linked Data, Continuous query processing, Temporal Logics, High-performance computing, Databases}
}
Document
Survey
DOI: 10.4230/TGDK.2.1.3
Semantic Web: Past, Present, and Future

Authors: Ansgar Scherp, Gerd Groener, Petr Škoda, Katja Hose, and Maria-Esther Vidal

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1

Abstract
Ever since the vision was formulated, the Semantic Web has inspired many generations of innovations. Semantic technologies have been used to share vast amounts of information on the Web, enhance them with semantics to give them meaning, and enable inference and reasoning on them. Throughout the years, semantic technologies, and in particular knowledge graphs, have been used in search engines, data integration, enterprise settings, and machine learning. In this paper, we recap the classical concepts and foundations of the Semantic Web as well as modern and recent concepts and applications, building upon these foundations. The classical topics we cover include knowledge representation, creating and validating knowledge on the Web, reasoning and linking, and distributed querying. We enhance this classical view of the so-called "Semantic Web Layer Cake" with an update of recent concepts that include provenance, security and trust, as well as a discussion of practical impacts from industry-led contributions. We conclude with an outlook on the future directions of the Semantic Web. This is a living document. If you like to contribute, please contact the first author and visit: https://github.com/ascherp/semantic-web-primer
Cite as

Ansgar Scherp, Gerd Groener, Petr Škoda, Katja Hose, and Maria-Esther Vidal. Semantic Web: Past, Present, and Future. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 3:1-3:37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{scherp_et_al:TGDK.2.1.3,
  author =	{Scherp, Ansgar and Groener, Gerd and \v{S}koda, Petr and Hose, Katja and Vidal, Maria-Esther},
  title =	{{Semantic Web: Past, Present, and Future}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:37},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.3},
  URN =		{urn:nbn:de:0030-drops-198607},
  doi =		{10.4230/TGDK.2.1.3},
  annote =	{Keywords: Linked Open Data, Semantic Web Graphs, Knowledge Graphs}
}
Document
Position
DOI: 10.4230/TGDK.2.1.5
Standardizing Knowledge Engineering Practices with a Reference Architecture

Authors: Bradley P. Allen and Filip Ilievski

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1

Abstract
Knowledge engineering is the process of creating and maintaining knowledge-producing systems. Throughout the history of computer science and AI, knowledge engineering workflows have been widely used given the importance of high-quality knowledge for reliable intelligent agents. Meanwhile, the scope of knowledge engineering, as apparent from its target tasks and use cases, has been shifting, together with its paradigms such as expert systems, semantic web, and language modeling. The intended use cases and supported user requirements between these paradigms have not been analyzed globally, as new paradigms often satisfy prior pain points while possibly introducing new ones. The recent abstraction of systemic patterns into a boxology provides an opening for aligning the requirements and use cases of knowledge engineering with the systems, components, and software that can satisfy them best, however, this direction has not been explored to date. This paper proposes a vision of harmonizing the best practices in the field of knowledge engineering by leveraging the software engineering methodology of creating reference architectures. We describe how a reference architecture can be iteratively designed and implemented to associate user needs with recurring systemic patterns, building on top of existing knowledge engineering workflows and boxologies. We provide a six-step roadmap that can enable the development of such an architecture, consisting of scope definition, selection of information sources, architectural analysis, synthesis of an architecture based on the information source analysis, evaluation through instantiation, and, ultimately, instantiation into a concrete software architecture. We provide an initial design and outcome of the definition of architectural scope, selection of information sources, and analysis. As the remaining steps of design, evaluation, and instantiation of the architecture are largely use-case specific, we provide a detailed description of their procedures and point to relevant examples. We expect that following through on this vision will lead to well-grounded reference architectures for knowledge engineering, will advance the ongoing initiatives of organizing the neurosymbolic knowledge engineering space, and will build new links to the software architectures and data science communities.
Cite as

Bradley P. Allen and Filip Ilievski. Standardizing Knowledge Engineering Practices with a Reference Architecture. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 5:1-5:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{allen_et_al:TGDK.2.1.5,
  author =	{Allen, Bradley P. and Ilievski, Filip},
  title =	{{Standardizing Knowledge Engineering Practices with a Reference Architecture}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:23},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.5},
  URN =		{urn:nbn:de:0030-drops-198623},
  doi =		{10.4230/TGDK.2.1.5},
  annote =	{Keywords: knowledge engineering, knowledge graphs, quality attributes, software architectures, sociotechnical systems}
}
Document
Vision
DOI: 10.4230/TGDK.1.1.13
Autonomy in the Age of Knowledge Graphs: Vision and Challenges

Authors: Jean-Paul Calbimonte, Andrei Ciortea, Timotheus Kampik, Simon Mayer, Terry R. Payne, Valentina Tamma, and Antoine Zimmermann

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
In this position paper, we propose that Knowledge Graphs (KGs) are one of the prime approaches to support the programming of autonomous software systems at the knowledge level. From this viewpoint, we survey how KGs can support different dimensions of autonomy in such systems: For example, the autonomy of systems with respect to their environment, or with respect to organisations; and we discuss related practical and research challenges. We emphasise that KGs need to be able to support systems of autonomous software agents that are themselves highly heterogeneous, which limits how these systems may use KGs. Furthermore, these heterogeneous software agents may populate highly dynamic environments, which implies that they require adaptive KGs. The scale of the envisioned systems - possibly stretching to the size of the Internet - highlights the maintainability of the underlying KGs that need to contain large-scale knowledge, which requires that KGs are maintained jointly by humans and machines. Furthermore, autonomous agents require procedural knowledge, and KGs should hence be explored more towards the provisioning of such knowledge to augment autonomous behaviour. Finally, we highlight the importance of modelling choices, including with respect to the selected abstraction level when modelling and with respect to the provisioning of more expressive constraint languages.
Cite as

Jean-Paul Calbimonte, Andrei Ciortea, Timotheus Kampik, Simon Mayer, Terry R. Payne, Valentina Tamma, and Antoine Zimmermann. Autonomy in the Age of Knowledge Graphs: Vision and Challenges. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 13:1-13:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{calbimonte_et_al:TGDK.1.1.13,
  author =	{Calbimonte, Jean-Paul and Ciortea, Andrei and Kampik, Timotheus and Mayer, Simon and Payne, Terry R. and Tamma, Valentina and Zimmermann, Antoine},
  title =	{{Autonomy in the Age of Knowledge Graphs: Vision and Challenges}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{13:1--13:22},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.13},
  URN =		{urn:nbn:de:0030-drops-194872},
  doi =		{10.4230/TGDK.1.1.13},
  annote =	{Keywords: Knowledge graphs, Autonomous Systems}
}
Document
Vision
DOI: 10.4230/TGDK.1.1.3
Knowledge Engineering Using Large Language Models

Authors: Bradley P. Allen, Lise Stork, and Paul Groth

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Knowledge engineering is a discipline that focuses on the creation and maintenance of processes that generate and apply knowledge. Traditionally, knowledge engineering approaches have focused on knowledge expressed in formal languages. The emergence of large language models and their capabilities to effectively work with natural language, in its broadest sense, raises questions about the foundations and practice of knowledge engineering. Here, we outline the potential role of LLMs in knowledge engineering, identifying two central directions: 1) creating hybrid neuro-symbolic knowledge systems; and 2) enabling knowledge engineering in natural language. Additionally, we formulate key open research questions to tackle these directions.
Cite as

Bradley P. Allen, Lise Stork, and Paul Groth. Knowledge Engineering Using Large Language Models. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 3:1-3:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{allen_et_al:TGDK.1.1.3,
  author =	{Allen, Bradley P. and Stork, Lise and Groth, Paul},
  title =	{{Knowledge Engineering Using Large Language Models}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:19},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.3},
  URN =		{urn:nbn:de:0030-drops-194777},
  doi =		{10.4230/TGDK.1.1.3},
  annote =	{Keywords: knowledge engineering, large language models}
}
Document
DOI: 10.4230/DagRep.3.6.83
Interoperation in Complex Information Ecosystems (Dagstuhl Seminar 13252)

Authors: Andreas Harth, Craig A. Knoblock, Kai-Uwe Sattler, and Rudi Studer

Published in: Dagstuhl Reports, Volume 3, Issue 6 (2013)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 13252 "Interoperation in Complex Information Ecosystems".
Cite as

Andreas Harth, Craig A. Knoblock, Kai-Uwe Sattler, and Rudi Studer. Interoperation in Complex Information Ecosystems (Dagstuhl Seminar 13252). In Dagstuhl Reports, Volume 3, Issue 6, pp. 83-134, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@Article{harth_et_al:DagRep.3.6.83,
  author =	{Harth, Andreas and Knoblock, Craig A. and Sattler, Kai-Uwe and Studer, Rudi},
  title =	{{Interoperation in Complex Information Ecosystems (Dagstuhl Seminar 13252)}},
  pages =	{83--134},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2013},
  volume =	{3},
  number =	{6},
  editor =	{Harth, Andreas and Knoblock, Craig A. and Sattler, Kai-Uwe and Studer, Rudi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.3.6.83},
  URN =		{urn:nbn:de:0030-drops-42597},
  doi =		{10.4230/DagRep.3.6.83},
  annote =	{Keywords: Information integration, System interoperation, Complex information ecosystems, Dataspaces, Linked Data, Semantic Web, Sensor networks, Restful design}
}
Document
DOI: 10.4230/DagRep.2.4.39
Semantic Data Management (Dagstuhl Seminar 12171)

Authors: Grigoris Antoniou, Oscar Corcho, Karl Aberer, Elena Simperl, and Rudi Studer

Published in: Dagstuhl Reports, Volume 2, Issue 4 (2012)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 12171 "Semantic Data Management". The purpose of the seminar was to have a fruitful exchange of ideas between the semantic web, database systems and information retrieval communities, organised across four main themes: scalability, provenance, dynamicity and search. Relevant key questions cutting across all of these themes were: (i) how can existing DB and IR solutions be adapted to manage semantic data; and (ii) are there new challenges that arise for the DB and IR communities (i.e. are radically new techniques required)? The outcome was a deeper, more integrated understanding of the current state of the art on semantic data management and a the identification of a set of open challenges that will inform the three communities in this intersection.
Cite as

Grigoris Antoniou, Oscar Corcho, Karl Aberer, Elena Simperl, and Rudi Studer. Semantic Data Management (Dagstuhl Seminar 12171). In Dagstuhl Reports, Volume 2, Issue 4, pp. 39-65, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@Article{antoniou_et_al:DagRep.2.4.39,
  author =	{Antoniou, Grigoris and Corcho, Oscar and Aberer, Karl and Simperl, Elena and Studer, Rudi},
  title =	{{Semantic Data Management (Dagstuhl Seminar 12171)}},
  pages =	{39--65},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2012},
  volume =	{2},
  number =	{4},
  editor =	{Antoniou, Grigoris and Corcho, Oscar and Aberer, Karl and Simperl, Elena and Studer, Rudi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.2.4.39},
  URN =		{urn:nbn:de:0030-drops-35976},
  doi =		{10.4230/DagRep.2.4.39},
  annote =	{Keywords: Semantic data, Semantic Web, Linked Data, Large-scale data management, Dynamicity and stream processing, Provenance and access control, Information retrieval and ranking}
}
Document
DOI: 10.4230/DagSemProc.09271.1
09271 Report – Perspectives Workshop: Semantic Web Reflections and Future Directions

Authors: John Domingue, Dieter Fensel, James A. Hendler, and Rudi Studer

Published in: Dagstuhl Seminar Proceedings, Volume 9271, Perspectives Workshop: Semantic Web Reflections and Future Directions (2010)

Abstract
With an ever increasing amount of data being stored and processed on computers, and the ubiquitous use of the Web for communication and dissemination of content, the world contains a vast amount of digital data that is growing ever faster. The available data is increasingly used to gain insights for science and research, to create commercial value, and to hold governments accountable. Semantic Web technologies for supporting machine-readable web content aim at facilitating the processing and integration of data from the open web environment where large portions of the publicly available data is being published. Since the first Dagstuhl seminar “Semantics on the Web” in 2000 the amount of machine-readable data on the web has exploded, and Semantic Web technologies have matured and made their way from research labs and universities into commercial applications. This report identifies lessons learned and future directions for the field as discussed at a Perspectives Workshop on Semantic Web, which took place in Dagstuhl, Germany, in June/July 2009.
Cite as

John Domingue, Dieter Fensel, James A. Hendler, and Rudi Studer. 09271 Report – Perspectives Workshop: Semantic Web Reflections and Future Directions. In Perspectives Workshop: Semantic Web Reflections and Future Directions. Dagstuhl Seminar Proceedings, Volume 9271, pp. 1-22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{domingue_et_al:DagSemProc.09271.1,
  author =	{Domingue, John and Fensel, Dieter and Hendler, James A. and Studer, Rudi},
  title =	{{09271 Report – Perspectives Workshop: Semantic Web Reflections and Future Directions}},
  booktitle =	{Perspectives Workshop: Semantic Web Reflections and Future Directions},
  pages =	{1--22},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9271},
  editor =	{John Domingue and Dieter Fensel and James A. Fendler and Rudi Studer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09271.1},
  URN =		{urn:nbn:de:0030-drops-25335},
  doi =		{10.4230/DagSemProc.09271.1},
  annote =	{Keywords: Semantic Web, Semantic Web Services, eBusiness, SOA, Web Services, GRID, Web 2.0}
}
Document
DOI: 10.4230/DagSemProc.05371.4
Description Logic Programs: A Practical Choice For the Modelling of Ontologies

Authors: Pascal Hitzler, York Sure, and Rudi Studer

Published in: Dagstuhl Seminar Proceedings, Volume 5371, Principles and Practices of Semantic Web Reasoning (2006)

Abstract
Knowledge representation using ontologies constitutes the heart of semantic technologies. Despite successful standardization efforts by the W3C, however, there are still numerous different ontology representation languages being used, and interoperability between them is in general not given. The problem is aggrevated by the fact that current standards lay foundations only and are well-known to be insufficient for the modelling of finer details. Thus, a plethora of extensions of the basic languages is being proposed, rendering the picture of ontology representation languages to be chaotic, to say the least. While semantic technologies start to become applicable and are being applied in adjacent areas of research and in research projects with industrial participation, and can soon be expected to become an integral part of industrial applications, the practitioner is faced with the difficult task of choosing his basic ontology representation paradigm. We will argue that the OWL subset known as Description Logic Programs constitutes a very reasonable choice.
Cite as

Pascal Hitzler, York Sure, and Rudi Studer. Description Logic Programs: A Practical Choice For the Modelling of Ontologies. In Principles and Practices of Semantic Web Reasoning. Dagstuhl Seminar Proceedings, Volume 5371, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{hitzler_et_al:DagSemProc.05371.4,
  author =	{Hitzler, Pascal and Sure, York and Studer, Rudi},
  title =	{{Description Logic Programs: A Practical Choice For the Modelling of Ontologies}},
  booktitle =	{Principles and Practices of Semantic Web Reasoning},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5371},
  editor =	{Fran\c{c}ois Bry and Fran\c{c}ois Fages and Massimo Marchiori and Hans-J\"{u}rgen Ohlbach},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05371.4},
  URN =		{urn:nbn:de:0030-drops-4783},
  doi =		{10.4230/DagSemProc.05371.4},
  annote =	{Keywords: Description Logic Programs}
}
Document
DOI: 10.4230/DagSemRep.281
Knowledge Management: An Interdisciplinary Approach (Dagstuhl Seminar 00281)

Authors: Matthias Jarke, Dan E. O'Leary, and Rudi Studer

Published in: Dagstuhl Seminar Reports. Dagstuhl Seminar Reports, Volume 1 (2021)

Abstract
Cite as

Matthias Jarke, Dan E. O'Leary, and Rudi Studer. Knowledge Management: An Interdisciplinary Approach (Dagstuhl Seminar 00281). Dagstuhl Seminar Report 281, pp. 1-19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2001)

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@TechReport{jarke_et_al:DagSemRep.281,
  author =	{Jarke, Matthias and O'Leary, Dan E. and Studer, Rudi},
  title =	{{Knowledge Management: An Interdisciplinary Approach (Dagstuhl Seminar 00281)}},
  pages =	{1--19},
  ISSN =	{1619-0203},
  year =	{2001},
  type = 	{Dagstuhl Seminar Report},
  number =	{281},
  institution =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemRep.281},
  URN =		{urn:nbn:de:0030-drops-151652},
  doi =		{10.4230/DagSemRep.281},
}
Document
DOI: 10.4230/DagSemRep.113
Shareable and Reusable Problem Solving Methods (Dagstuhl Seminar 9519)

Authors: Rudi Studer and Mark A. Musen

Published in: Dagstuhl Seminar Reports. Dagstuhl Seminar Reports, Volume 1 (2021)

Abstract
Cite as

Rudi Studer and Mark A. Musen. Shareable and Reusable Problem Solving Methods (Dagstuhl Seminar 9519). Dagstuhl Seminar Report 113, pp. 1-22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (1995)

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@TechReport{studer_et_al:DagSemRep.113,
  author =	{Studer, Rudi and Musen, Mark A.},
  title =	{{Shareable and Reusable Problem Solving Methods (Dagstuhl Seminar 9519)}},
  pages =	{1--22},
  ISSN =	{1619-0203},
  year =	{1995},
  type = 	{Dagstuhl Seminar Report},
  number =	{113},
  institution =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemRep.113},
  URN =		{urn:nbn:de:0030-drops-150014},
  doi =		{10.4230/DagSemRep.113},
}
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