Grounding Stream Reasoning Research

• Published in: Transactions on Graph Data and Knowledge 2024-05, Vol.2 (1), p.2:1-2:47
• Main Authors: Bonte, Pieter, Calbimonte, Jean-Paul, de Leng, Daniel, Dell'Aglio, Daniele, Valle, Emanuele Della, Eiter, Thomas, Giannini, Federico, Heintz, Fredrik, Schekotihin, Konstantin, Le-Phuoc, Danh, Mileo, Alessandra, Schneider, Patrik, Tommasini, Riccardo, Urbani, Jacopo, Ziffer, Giacomo
• Format: Article
• Language: English
• Subjects: Computer Science; continuous query processing; high-performance computing; rdf streams; stream processing; stream reasoning; streaming linked data; temporal logics
• ISSN: 2942-7517
• DOI: 10.4230/TGDK.2.1.2

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.