3 Search Results for "Garijo, Daniel"

Document
Survey
DOI: 10.4230/TGDK.2.1.1
Towards Representing Processes and Reasoning with Process Descriptions on the Web

Authors: Andreas Harth, Tobias Käfer, Anisa Rula, Jean-Paul Calbimonte, Eduard Kamburjan, and Martin Giese

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
We work towards a vocabulary to represent processes and temporal logic specifications as graph-structured data. Different fields use incompatible terminologies for describing essentially the same process-related concepts. In addition, processes can be represented from different perspectives and levels of abstraction: both state-centric and event-centric perspectives offer distinct insights into the underlying processes. In this work, we strive to unify the representation of processes and related concepts by leveraging the power of knowledge graphs. We survey approaches to representing processes and reasoning with process descriptions from different fields and provide a selection of scenarios to help inform the scope of a unified representation of processes. We focus on processes that can be executed and observed via web interfaces. We propose to provide a representation designed to combine state-centric and event-centric perspectives while incorporating temporal querying and reasoning capabilities on temporal logic specifications. A standardised vocabulary and representation for processes and temporal specifications would contribute towards bridging the gap between the terminologies from different fields and fostering the broader application of methods involving temporal logics, such as formal verification and program synthesis.
Cite as

Andreas Harth, Tobias Käfer, Anisa Rula, Jean-Paul Calbimonte, Eduard Kamburjan, and Martin Giese. Towards Representing Processes and Reasoning with Process Descriptions on the Web. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 1:1-1:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@Article{harth_et_al:TGDK.2.1.1,
  author =	{Harth, Andreas and K\"{a}fer, Tobias and Rula, Anisa and Calbimonte, Jean-Paul and Kamburjan, Eduard and Giese, Martin},
  title =	{{Towards Representing Processes and Reasoning with Process Descriptions on the Web}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:32},
  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.2.1.1},
  URN =		{urn:nbn:de:0030-drops-198583},
  doi =		{10.4230/TGDK.2.1.1},
  annote =	{Keywords: Process modelling, Process ontology, Temporal logic, Web services}
}
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)

Copy BibTex To Clipboard

@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
DOI: 10.4230/DagMan.6.1.1
Engineering Academic Software (Dagstuhl Perspectives Workshop 16252)

Authors: Alice Allen, Cecilia Aragon, Christoph Becker, Jeffrey Carver, Andrei Chis, Benoit Combemale, Mike Croucher, Kevin Crowston, Daniel Garijo, Ashish Gehani, Carole Goble, Robert Haines, Robert Hirschfeld, James Howison, Kathryn Huff, Caroline Jay, Daniel S. Katz, Claude Kirchner, Katie Kuksenok, Ralf Lämmel, Oscar Nierstrasz, Matt Turk, Rob van Nieuwpoort, Matthew Vaughn, and Jurgen J. Vinju

Published in: Dagstuhl Manifestos, Volume 6, Issue 1 (2017)

Abstract
Software is often a critical component of scientific research. It can be a component of the academic research methods used to produce research results, or it may itself be an academic research result. Software, however, has rarely been considered to be a citable artifact in its own right. With the advent of open-source software, artifact evaluation committees of conferences, and journals that include source code and running systems as part of the published artifacts, we foresee that software will increasingly be recognized as part of the academic process. The quality and sustainability of this software must be accounted for, both a prioro and a posteriori. The Dagstuhl Perspectives Workshop on "Engineering Academic Software" has examined the strengths, weaknesses, risks, and opportunities of academic software engineering. A key outcome of the workshop is this Dagstuhl Manifesto, serving as a roadmap towards future professional software engineering for software-based research instruments and other software produced and used in an academic context. The manifesto is expressed in terms of a series of actionable "pledges" that users and developers of academic research software can take as concrete steps towards improving the environment in which that software is produced.
Cite as

Alice Allen, Cecilia Aragon, Christoph Becker, Jeffrey Carver, Andrei Chis, Benoit Combemale, Mike Croucher, Kevin Crowston, Daniel Garijo, Ashish Gehani, Carole Goble, Robert Haines, Robert Hirschfeld, James Howison, Kathryn Huff, Caroline Jay, Daniel S. Katz, Claude Kirchner, Katie Kuksenok, Ralf Lämmel, Oscar Nierstrasz, Matt Turk, Rob van Nieuwpoort, Matthew Vaughn, and Jurgen J. Vinju. Engineering Academic Software (Dagstuhl Perspectives Workshop 16252). In Dagstuhl Manifestos, Volume 6, Issue 1, pp. 1-20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

Copy BibTex To Clipboard

@Article{allen_et_al:DagMan.6.1.1,
  author =	{Allen, Alice and Aragon, Cecilia and Becker, Christoph and Carver, Jeffrey and Chis, Andrei and Combemale, Benoit and Croucher, Mike and Crowston, Kevin and Garijo, Daniel and Gehani, Ashish and Goble, Carole and Haines, Robert and Hirschfeld, Robert and Howison, James and Huff, Kathryn and Jay, Caroline and Katz, Daniel S. and Kirchner, Claude and Kuksenok, Katie and L\"{a}mmel, Ralf and Nierstrasz, Oscar and Turk, Matt and van Nieuwpoort, Rob and Vaughn, Matthew and Vinju, Jurgen J.},
  title =	{{Engineering Academic Software (Dagstuhl Perspectives Workshop 16252)}},
  pages =	{1--20},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2017},
  volume =	{6},
  number =	{1},
  editor =	{Allen, Alice and Aragon, Cecilia and Becker, Christoph and Carver, Jeffrey and Chis, Andrei and Combemale, Benoit and Croucher, Mike and Crowston, Kevin and Garijo, Daniel and Gehani, Ashish and Goble, Carole and Haines, Robert and Hirschfeld, Robert and Howison, James and Huff, Kathryn and Jay, Caroline and Katz, Daniel S. and Kirchner, Claude and Kuksenok, Katie and L\"{a}mmel, Ralf and Nierstrasz, Oscar and Turk, Matt and van Nieuwpoort, Rob and Vaughn, Matthew and Vinju, Jurgen J.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.6.1.1},
  URN =		{urn:nbn:de:0030-drops-71468},
  doi =		{10.4230/DagMan.6.1.1},
  annote =	{Keywords: Academic software, Research software, Software citation, Software sustainability}
}
  • Refine by Author
  • 1 Allen, Alice
  • 1 Allen, Bradley P.
  • 1 Aragon, Cecilia
  • 1 Becker, Christoph
  • 1 Calbimonte, Jean-Paul
  • Show More...

  • Refine by Classification
  • 1 Applied computing → Business process modeling
  • 1 Applied computing → Event-driven architectures
  • 1 Computing methodologies → Knowledge representation and reasoning
  • 1 Computing methodologies → Ontology engineering
  • 1 Computing methodologies → Temporal reasoning
  • Show More...

  • Refine by Keyword
  • 1 Academic software
  • 1 Process modelling
  • 1 Process ontology
  • 1 Research software
  • 1 Software citation
  • Show More...

  • Refine by Type
  • 3 document

  • Refine by Publication Year
  • 2 2024
  • 1 2017

© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact