7 Search Results for "Kalayci, Elem Güzel"

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
Invited Paper
DOI: 10.4230/OASIcs.RW.2024/2025.9
Reasoning About Time in DatalogMTL: Course Notes (Invited Paper)

Authors: Przemysław Andrzej Wałęga

Published in: OASIcs, Volume 138, Joint Proceedings of the 20th and 21st Reasoning Web Summer Schools (RW 2024 & RW 2025)

Abstract
Many real-world applications, such as those in healthcare, finance, and logistics, require reasoning over temporal data. Standard rule-based languages like Datalog, however, lack explicit mechanisms for handling time and temporal dependencies. In this chapter, we discussDatalogMTL, an extension of Datalog with operators frommetric temporal logic that allow to express complex temporal properties. We focus on reasoning algorithms for DatalogMTL, discussing bothmaterialisation, based on fixpoint applications of the immediate consequence operator, and anovel saturation-based extensionthat detects and halts infinite derivations, ensuring both completeness and termination of reasoning.
Cite as

Przemysław Andrzej Wałęga. Reasoning About Time in DatalogMTL: Course Notes (Invited Paper). In Joint Proceedings of the 20th and 21st Reasoning Web Summer Schools (RW 2024 & RW 2025). Open Access Series in Informatics (OASIcs), Volume 138, pp. 9:1-9:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{walega:OASIcs.RW.2024/2025.9,
  author =	{Wa{\l}\k{e}ga, Przemys{\l}aw Andrzej},
  title =	{{Reasoning About Time in DatalogMTL: Course Notes}},
  booktitle =	{Joint Proceedings of the 20th and 21st Reasoning Web Summer Schools (RW 2024 \& RW 2025)},
  pages =	{9:1--9:23},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-405-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{138},
  editor =	{Artale, Alessandro and Bienvenu, Meghyn and Garc{\'\i}a, Yazm{\'\i}n Ib\'{a}\~{n}ez and Murlak, Filip},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.RW.2024/2025.9},
  URN =		{urn:nbn:de:0030-drops-250546},
  doi =		{10.4230/OASIcs.RW.2024/2025.9},
  annote =	{Keywords: DatalogMTL, Logic Programming, Temporal Reasoning}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.TIME.2025.15
The Temporal Vadalog System (Short Paper)

Authors: Luigi Bellomarini, Livia Blasi, Markus Nissl, and Emanuel Sallinger

Published in: LIPIcs, Volume 355, 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)

Abstract
The recent resurgence of the Datalog language in the Knowledge Representation and Reasoning community has paved the way for a very promising proposal for temporal extension. DatalogMTL (Datalog with Metric Temporal Operators) is a language that offers a good trade-off between computational complexity and expressive power. However, existing implementations are still preliminary or prototypical. In this extended abstract, we give a brief overview of Temporal Vadalog, a system supporting reasoning over DatalogMTL programs built upon an engineered architecture and adopted in production scenarios in the financial setting.
Cite as

Luigi Bellomarini, Livia Blasi, Markus Nissl, and Emanuel Sallinger. The Temporal Vadalog System (Short Paper). In 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 355, pp. 15:1-15:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{bellomarini_et_al:LIPIcs.TIME.2025.15,
  author =	{Bellomarini, Luigi and Blasi, Livia and Nissl, Markus and Sallinger, Emanuel},
  title =	{{The Temporal Vadalog System}},
  booktitle =	{32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)},
  pages =	{15:1--15:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-401-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{355},
  editor =	{Vidal, Thierry and Wa{\l}\k{e}ga, Przemys{\l}aw Andrzej},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2025.15},
  URN =		{urn:nbn:de:0030-drops-244611},
  doi =		{10.4230/LIPIcs.TIME.2025.15},
  annote =	{Keywords: temporal reasoning, Datalog, DatalogMTL}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2025.31
On Deciding the Data Complexity of Answering Linear Monadic Datalog Queries with LTL Operators

Authors: Alessandro Artale, Anton Gnatenko, Vladislav Ryzhikov, and Michael Zakharyaschev

Published in: LIPIcs, Volume 328, 28th International Conference on Database Theory (ICDT 2025)

Abstract
Our concern is the data complexity of answering linear monadic datalog queries whose atoms in the rule bodies can be prefixed by operators of linear temporal logic LTL. We first observe that, for data complexity, answering any connected query with operators ○/○- (at the next/previous moment) is either in AC⁰, or in ACC⁰\AC⁰, or NC¹-complete, or L-hard and in NL. Then we show that the problem of deciding L-hardness of answering such queries is PSpace-complete, while checking membership in the classes AC⁰ and ACC⁰ as well as NC¹-completeness can be done in ExpSpace. Finally, we prove that membership in AC⁰ or in ACC⁰, NC¹-completeness, and L-hardness are undecidable for queries with operators ◇/◇- (sometime in the future/past) provided that NC¹ ≠ NL and L ≠ NL.
Cite as

Alessandro Artale, Anton Gnatenko, Vladislav Ryzhikov, and Michael Zakharyaschev. On Deciding the Data Complexity of Answering Linear Monadic Datalog Queries with LTL Operators. In 28th International Conference on Database Theory (ICDT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 328, pp. 31:1-31:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{artale_et_al:LIPIcs.ICDT.2025.31,
  author =	{Artale, Alessandro and Gnatenko, Anton and Ryzhikov, Vladislav and Zakharyaschev, Michael},
  title =	{{On Deciding the Data Complexity of Answering Linear Monadic Datalog Queries with LTL Operators}},
  booktitle =	{28th International Conference on Database Theory (ICDT 2025)},
  pages =	{31:1--31:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-364-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{328},
  editor =	{Roy, Sudeepa and Kara, Ahmet},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2025.31},
  URN =		{urn:nbn:de:0030-drops-229723},
  doi =		{10.4230/LIPIcs.ICDT.2025.31},
  annote =	{Keywords: Linear monadic datalog, linear temporal logic, data complexity}
}
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.2.1.4
Logics for Conceptual Data Modelling: A Review

Authors: Pablo R. Fillottrani and C. Maria Keet

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
Information modelling for databases and object-oriented information systems avails of conceptual data modelling languages such as EER and UML Class Diagrams. Many attempts exist to add logical rigour to them, for various reasons and with disparate strengths. In this paper we aim to provide a structured overview of the many efforts. We focus on aims, approaches to the formalisation, including key dimensions of choice points, popular logics used, and the main relevant reasoning services. We close with current challenges and research directions.
Cite as

Pablo R. Fillottrani and C. Maria Keet. Logics for Conceptual Data Modelling: A Review. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 4:1-4:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{fillottrani_et_al:TGDK.2.1.4,
  author =	{Fillottrani, Pablo R. and Keet, C. Maria},
  title =	{{Logics for Conceptual Data Modelling: A Review}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:30},
  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.2.1.4},
  URN =		{urn:nbn:de:0030-drops-198616},
  doi =		{10.4230/TGDK.2.1.4},
  annote =	{Keywords: Conceptual Data Modelling, EER, UML, Description Logics, OWL}
}
Document
DOI: 10.4230/LIPIcs.TIME.2019.7
Two-Dimensional Rule Language for Querying Sensor Log Data: A Framework and Use Cases

Authors: Sebastian Brandt, Diego Calvanese, Elem Güzel Kalaycı, Roman Kontchakov, Benjamin Mörzinger, Vladislav Ryzhikov, Guohui Xiao, and Michael Zakharyaschev

Published in: LIPIcs, Volume 147, 26th International Symposium on Temporal Representation and Reasoning (TIME 2019)

Abstract
Motivated by two industrial use cases that involve detecting events of interest in (asynchronous) time series from sensors in manufacturing rigs and gas turbines, we design an expressive rule language DslD equipped with interval aggregate functions (such as weighted average over a time interval), Allen’s interval relations and various metric constructs. We demonstrate how to model events in the uses cases in terms of DslD programs. We show that answering DslD queries in our use cases can be reduced to evaluating SQL queries. Our experiments with the use cases, carried out on the Apache Spark system, show that such SQL queries scale well on large real-world datasets.
Cite as

Sebastian Brandt, Diego Calvanese, Elem Güzel Kalaycı, Roman Kontchakov, Benjamin Mörzinger, Vladislav Ryzhikov, Guohui Xiao, and Michael Zakharyaschev. Two-Dimensional Rule Language for Querying Sensor Log Data: A Framework and Use Cases. In 26th International Symposium on Temporal Representation and Reasoning (TIME 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 147, pp. 7:1-7:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{brandt_et_al:LIPIcs.TIME.2019.7,
  author =	{Brandt, Sebastian and Calvanese, Diego and Kalayc{\i}, Elem G\"{u}zel and Kontchakov, Roman and M\"{o}rzinger, Benjamin and Ryzhikov, Vladislav and Xiao, Guohui and Zakharyaschev, Michael},
  title =	{{Two-Dimensional Rule Language for Querying Sensor Log Data: A Framework and Use Cases}},
  booktitle =	{26th International Symposium on Temporal Representation and Reasoning (TIME 2019)},
  pages =	{7:1--7:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-127-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{147},
  editor =	{Gamper, Johann and Pinchinat, Sophie and Sciavicco, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2019.7},
  URN =		{urn:nbn:de:0030-drops-113658},
  doi =		{10.4230/LIPIcs.TIME.2019.7},
  annote =	{Keywords: Ontology-based data access, temporal logic, sensor log data}
}
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