5 Search Results for "Savkovic, Ognjen"

Document
Use Case
DOI: 10.4230/TGDK.3.3.5
LLM-Supported Manufacturing Mapping Generation

Authors: Wilma Johanna Schmidt, Irlan Grangel-González, Adrian Paschke, and Evgeny Kharlamov

Published in: TGDK, Volume 3, Issue 3 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 3

Abstract
In large manufacturing companies, such as Bosch, that operate thousands of production lines with each comprising up to dozens of production machines and other equipment, even simple inventory questions such as of location and quantities of a particular equipment type require non-trivial solutions. Addressing these questions requires to integrate multiple heterogeneous data sets which is time consuming and error prone and demands domain as well as knowledge experts. Knowledge graphs (KGs) are practical for consolidating inventory data by bringing it into the same format and linking inventory items. However, the KG creation and maintenance itself pose challenges as mappings are needed to connect data sets and ontologies. In this work, we address these challenges by exploring LLM-supported and context-enhanced generation of both YARRRML and RML mappings. Facing large ontologies in the manufacturing domain and token limitations in LLM prompts, we further evaluate ontology reduction methods in our approach. We evaluate our approach both quantitatively against reference mappings created manually by experts and, for YARRRML, also qualitatively with expert feedback. This work extends the exploration of the challenges with LLM-supported and context-enhanced mapping generation YARRRML [Schmidt et al., 2025] by comprehensive analyses on RML mappings and an ontology reduction evaluation. We further publish the source code of this work. Our work provides a valuable support when creating manufacturing mappings and supports data and schema updates.
Cite as

Wilma Johanna Schmidt, Irlan Grangel-González, Adrian Paschke, and Evgeny Kharlamov. LLM-Supported Manufacturing Mapping Generation. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 5:1-5:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{schmidt_et_al:TGDK.3.3.5,
  author =	{Schmidt, Wilma Johanna and Grangel-Gonz\'{a}lez, Irlan and Paschke, Adrian and Kharlamov, Evgeny},
  title =	{{LLM-Supported Manufacturing Mapping Generation}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:22},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.5},
  URN =		{urn:nbn:de:0030-drops-252164},
  doi =		{10.4230/TGDK.3.3.5},
  annote =	{Keywords: Mapping Generation, Knowledge Graph Construction, Ontology Reduction, RML, YARRRML, LLM, Manufacturing}
}
Document
Research
DOI: 10.4230/TGDK.3.3.1
A Logic Programming Approach to Repairing SHACL Constraint Violations

Authors: Shqiponja Ahmetaj, Robert David, Axel Polleres, and Mantas Šimkus

Published in: TGDK, Volume 3, Issue 3 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 3

Abstract
The Shapes Constraint Language (SHACL) is a recent standard, a W3C recommendation, for validating RDF graphs against shape constraints to be checked on target nodes of a data graph. The standard also describes the notion of validation reports, which detail the results of the validation process. In case of violation of constraints, the validation report should explain the reasons for non-validation, offering guidance on how to identify or fix violations in the data graph. Since the specification left it open to SHACL processors to define such explanations, a recent work proposed the use of explanations in the style of database repairs, where a repair is a set of additions to or deletions from the data graph so that the resulting graph validates against the constraints. In this paper, we study such repairs for non-recursive SHACL, the largest fragment of SHACL that is fully defined in the specification. We propose an algorithm to compute repairs by encoding the explanation problem - using Answer Set Programming (ASP) - into a logic program, where the answer sets contain (minimal) repairs. We then study a scenario where it is not possible to simultaneously repair all the targets, which may be the case due to overall unsatisfiability or conflicting constraints. We introduce a relaxed notion of validation, which allows to validate a (maximal) subset of the targets and adapt the ASP translation to take into account this relaxation. Finally, we add support for repairing constraints which use property paths and equality of paths. Our implementation in clingo is - to the best of our knowledge - the first implementation of a repair program for SHACL.
Cite as

Shqiponja Ahmetaj, Robert David, Axel Polleres, and Mantas Šimkus. A Logic Programming Approach to Repairing SHACL Constraint Violations. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 1:1-1:36, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{ahmetaj_et_al:TGDK.3.3.1,
  author =	{Ahmetaj, Shqiponja and David, Robert and Polleres, Axel and \v{S}imkus, Mantas},
  title =	{{A Logic Programming Approach to Repairing SHACL Constraint Violations}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:36},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.1},
  URN =		{urn:nbn:de:0030-drops-252124},
  doi =		{10.4230/TGDK.3.3.1},
  annote =	{Keywords: SHACL, Shapes Constraint Language, Database Repairs, Knowledge Graphs, Semantic Web, Answer Set Programming}
}
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
Survey
DOI: 10.4230/TGDK.1.1.11
How Does Knowledge Evolve in Open Knowledge Graphs?

Authors: Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs

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
Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the collective management of evolving knowledge. The present work aims t o provide an analysis of the obstacles related to investigating and processing specifically this central aspect of evolution in KGs. To this end, we discuss (i) the dimensions of evolution in KGs, (ii) the observability of evolution in existing, open, collaboratively constructed Knowledge Graphs over time, and (iii) possible metrics to analyse this evolution. We provide an overview of relevant state-of-the-art research, ranging from metrics developed for Knowledge Graphs specifically to potential methods from related fields such as network science. Additionally, we discuss technical approaches - and their current limitations - related to storing, analysing and processing large and evolving KGs in terms of handling typical KG downstream tasks.
Cite as

Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs. How Does Knowledge Evolve in Open Knowledge Graphs?. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 11:1-11:59, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{polleres_et_al:TGDK.1.1.11,
  author =	{Polleres, Axel and Pernisch, Romana and Bonifati, Angela and Dell'Aglio, Daniele and Dobriy, Daniil and Dumbrava, Stefania and Etcheverry, Lorena and Ferranti, Nicolas and Hose, Katja and Jim\'{e}nez-Ruiz, Ernesto and Lissandrini, Matteo and Scherp, Ansgar and Tommasini, Riccardo and Wachs, Johannes},
  title =	{{How Does Knowledge Evolve in Open Knowledge Graphs?}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{11:1--11:59},
  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.1.1.11},
  URN =		{urn:nbn:de:0030-drops-194855},
  doi =		{10.4230/TGDK.1.1.11},
  annote =	{Keywords: KG evolution, temporal KG, versioned KG, dynamic KG}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2016.16
Query Stability in Monotonic Data-Aware Business Processes

Authors: Ognjen Savkovic, Elisa Marengo, and Werner Nutt

Published in: LIPIcs, Volume 48, 19th International Conference on Database Theory (ICDT 2016)

Abstract
Organizations continuously accumulate data, often according to some business processes. If one poses a query over such data for decision support, it is important to know whether the query is stable, that is, whether the answers will stay the same or may change in the future because business processes may add further data. We investigate query stability for conjunctive queries. To this end, we define a formalism that combines an explicit representation of the control flow of a process with a specification of how data is read and inserted into the database. We consider different restrictions of the process model and the state of the system, such as negation in conditions, cyclic executions, read access to written data, presence of pending process instances, and the possibility to start fresh process instances. We identify for which restriction combinations stability of conjunctive queries is decidable and provide encodings into variants of Datalog that are optimal with respect to the worst-case complexity of the problem.
Cite as

Ognjen Savkovic, Elisa Marengo, and Werner Nutt. Query Stability in Monotonic Data-Aware Business Processes. In 19th International Conference on Database Theory (ICDT 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 48, pp. 16:1-16:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{savkovic_et_al:LIPIcs.ICDT.2016.16,
  author =	{Savkovic, Ognjen and Marengo, Elisa and Nutt, Werner},
  title =	{{Query Stability in Monotonic Data-Aware Business Processes}},
  booktitle =	{19th International Conference on Database Theory (ICDT 2016)},
  pages =	{16:1--16:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-002-6},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{48},
  editor =	{Martens, Wim and Zeume, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2016.16},
  URN =		{urn:nbn:de:0030-drops-57851},
  doi =		{10.4230/LIPIcs.ICDT.2016.16},
  annote =	{Keywords: Business Processes, Query Stability}
}
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