Amsterdam Photo by Massimo Catarinella - Own work, CC BY-SA 3.0

Since 2015, the Stream Reasoning Workshop has been a yearly event where scientists from different communities gather together to discuss problems and recent developments around the processing of rapidly changing data (data streams).

Like in previous years, the workshop is invitation-only and focuses on strengthening this growing community by sharing different perspectives, challenges, and experiences obtained by working with expressive yet efficient decision-making over data streams.


After Vienna, Berlin, Zürich, Linköping, and Milan, the sixth edition of the workshop will be held on December 5 and 6, 2022. The event will take place at the Vrije Universiteit Amsterdam, in the heart of the final district of the city. On Monday, the workshop will be on the third floor of the New University (NU) building. The rooms can be reached freely without any pre-registration. On Tuesday, the workshop will be take place on the main building. You can find a map of the campus here with some annotations about the location of the two buildings.

Workshop Schedule

Monday 05/12/2022

In the morning, the workshop will take place in room NU-3B19 (3rd floor of the NU building)

09:30 - 10:00
10:00 - 11:00
First morning session (research talks)
  • Anh Le Tuan: Semantic stream processing on different hardwares [SLIDES]
11:00 - 11:30
Coffee break
11:30 - 13:00
Second morning session (research talks)
  • Alessio Bernardo: gives data an edge [SLIDES]
  • Mauro Dalle Lucca Tosi: TensAIR: Online Learning from Data Streams via Asynchronous Iterative Routing [SLIDES,PAPER]
13:00 - 14:30
Lunch, which will be in a dedicated area in the same building

In the afternoon, the workshop will take place in room NU-3A65 (3rd floor of the NU building)

14:30 - 15:30
Keynote by prof. Philippe Cudré-Mauroux, University of Fribourg
Title: Online Graph Data Integration
Until recently, structured (e.g., relational) and unstructured (e.g., textual) data were managed very differently: Structured data was queried declaratively using languages such as SQL, while unstructured data was searched using boolean queries over inverted indices. Today, we witness the rapid emergence of Big Data Integration techniques leveraging knowledge graphs to bridge the gap between different types of contents and integrate both unstructured and structured information more effectively. I will start this talk by giving a few examples of Big Data Integration. I will then delve into modern data integration techniques leveraging neuro-symbolic architectures and online streaming aggregation, before describing a number of systems that were recently built in my lab in that context.
15:30 - 17:00
Afternoon session (research talks)
  • Pieter Bonte: Optimizing rules for continuous querying under entailment with CSprite++
  • Daniel Schraudner: Distributed Complex Event Detection with Resource-oriented Stream Containers on the Edge [SLIDES]
  • Riccardo Tommasini: Streaming Linked Data and RSP4J: recent advancements and future work [SLIDES]
  • Giacomo Ziffer: Towards Time-Evolving Analytics: Online Learning for Time-Dependent Evolving Data Streams [SLIDES]
17:00 - 17:30
Coffee break
17:30 - 18:30
Plenary session

In the evening, there will be a dinner at Indrapura – an indonesian restaurant. We have reserved a table at 7pm. The restaurant is located on Rembrandtplein (Google Maps), in the heart of the city.

Tuesday 06/12/2022

The workshop will take place, for the entire day, in room HG 07A33 (7th floor of the main building)

09:30 - 10:30
First morning session (research talks)
  • Manolis Pitsikalis: Stream Reasoning with Cycles [SLIDES]
  • Efthymia Tsamoura: Highly-Efficient Reasoning via Trigger Graphs [SLIDES]
10:30 - 11:00
Coffee break
11:00 - 12:30
Second morning session (research talks)
  • Przemysław Wałęga: Stream reasoning in DatalogMTL via finite materialisation [SLIDES]
  • Jacopo Urbani: Towards Stream Reasoning with Composite AI
  • Patrik Schneider: A Qualitative Temporal Extension of Here-and-There Logic [SLIDES]
  • Danh Le Phuoc: Semantic Stream Learning and Reasoning: Think outside the box!
12:30 - 13:30
Lunch, which will be served in the same room
13:30 - 14:30
Keynote by prof. Bernardo Cuenca Grau, Oxford University
Title: Temporal and Stream Reasoning in DatalogMTL
DatalogMTL is a powerful extension of Datalog with operators from Metric Temporal Logic (MTL), typically interpreted over the rational timeline. DatalogMTL has received significant attention in recent years and has found applications in ontology-based data access and stream reasoning, amongst others. In this talk, I will provide an overview of the language, its theoretical properties, and the different reasoning techniques that have been developed in recent years for both static and streaming settings. I will also discuss implementation and scalability, and point at exciting directions for future work.
14:30 - 16:00
Afternoon session (research talks)
  • Daniele Dell'Aglio: Differentially private query answering over streaming knowledge graphs [SLIDES]
  • Maarten Vandenbrande: Incremental Query Aggregators in SOLID (short talk) [SLIDES]
  • Kushagra Singh Bisen: Aggregating Sensitive Health Datastreams in SOLID (short talk) [SLIDES]
  • Mathijs van Noort: Towards a Unifying Logic for Linked Data Streams (short talk) [SLIDES]
16:00 - 16:30
Coffee break
16:30 - 17:30
Plenary closing session

Where to stay

The VU situated in the financial district (Google Maps) and it is a few minutes away from Schiphol. All the buildings are situated within a close range. There are plenty of hotels nearby. A good hotel is the Crowne Plaza. Another option, which is usually cheaper, is the Holiday Inn Express. A third option, which was positively reviewed by previous guests of our group, is citizenM. All three options are at a walking distance. Alternatively, you can stay in an hotel in the city center. Amsterdam is a fairly compact city and the VU can be easily reached using the tram lines 5 or 25. Several hotels allow their guests to rent bikes. Indeed, the fastest way to travel through the city is by bike, but be aware that it can get quite busy during peak hours.