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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
DOI: 10.4230/DagRep.10.2.19
Foundations of Composite Event Recognition (Dagstuhl Seminar 20071)

Authors: Alexander Artikis, Thomas Eiter, Alessandro Margara, and Stijn Vansummeren

Published in: Dagstuhl Reports, Volume 10, Issue 2 (2020)

Abstract
Composite Event Recognition (CER) refers to the activity of detecting patterns in streams of continuously arriving "event" data over, possibly geographically, distributed sources. CER is key in Big Data applications that require the processing of such event streams to obtain timely insights and to implement reactive and proactive measures. Examples include the recognition of emerging stories and trends on the Social Web, traffic and transport incidents in smart cities, and epidemic spread. Numerous CER languages have been proposed in the literature. While these systems have a common goal, they differ in their data models, pattern languages and processing mechanisms, resulting in heterogeneous implementations with fundamentally different capabilities. Moreover, we lack a common understanding of the trade-offs between expressiveness and complexity, and a theory for comparing the fundamental capabilities of CER systems. As such, CER frameworks are difficult to understand, extend and generalise. It is unclear which of the proposed approaches better meets the requirements of a given application. Furthermore, the lack of foundations makes it hard to leverage established results - from automata theory, temporal logics, etc - thus hindering scientific and technological progress in CER. The objective of the seminar was to bring together researchers and practitioners working in Databases, Distributed Systems, Automata Theory, Logic and Stream Reasoning; disseminate the recent foundational results across these fields; establish new research collaborations among these fields; thereby start making progress towards formulating such foundations.
Cite as

Alexander Artikis, Thomas Eiter, Alessandro Margara, and Stijn Vansummeren. Foundations of Composite Event Recognition (Dagstuhl Seminar 20071). In Dagstuhl Reports, Volume 10, Issue 2, pp. 19-49, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@Article{artikis_et_al:DagRep.10.2.19,
  author =	{Artikis, Alexander and Eiter, Thomas and Margara, Alessandro and Vansummeren, Stijn},
  title =	{{Foundations of Composite Event Recognition (Dagstuhl Seminar 20071)}},
  pages =	{19--49},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2020},
  volume =	{10},
  number =	{2},
  editor =	{Artikis, Alexander and Eiter, Thomas and Margara, Alessandro and Vansummeren, Stijn},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.10.2.19},
  URN =		{urn:nbn:de:0030-drops-130587},
  doi =		{10.4230/DagRep.10.2.19},
  annote =	{Keywords: complex event processing, event algebra, pattern matching, stream reasoning, temporal reasoning}
}
Document
DOI: 10.4230/DagSemProc.04171.1
04171 Abstracts Collection – Logic Based Information Agents

Authors: Jürgen Dix, Thomas Eiter, and Enrico Franconi

Published in: Dagstuhl Seminar Proceedings, Volume 4171, Logic Based Information Agents (2006)

Abstract
From 18.04.04 to 23.04.04, the Dagstuhl Seminar 04171 ``Logic Based Information Agents'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Jürgen Dix, Thomas Eiter, and Enrico Franconi. 04171 Abstracts Collection – Logic Based Information Agents. In Logic Based Information Agents. Dagstuhl Seminar Proceedings, Volume 4171, pp. 1-9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{dix_et_al:DagSemProc.04171.1,
  author =	{Dix, J\"{u}rgen and Eiter, Thomas and Franconi, Enrico},
  title =	{{04171 Abstracts Collection – Logic Based Information Agents}},
  booktitle =	{Logic Based Information Agents},
  pages =	{1--9},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{4171},
  editor =	{J\"{u}rgen Dix and Thomas Eiter and Enrico Franconi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.04171.1},
  URN =		{urn:nbn:de:0030-drops-4689},
  doi =		{10.4230/DagSemProc.04171.1},
  annote =	{Keywords: }
}
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