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Streaming the Web: Reasoning Over Dynamic Data

24 Pages Posted: 7 Jul 2018 Publication Status: Accepted

See all articles by Alessandro Margara

Alessandro Margara

VU University Amsterdam - Department of Computer Science

Jacopo Urbani

VU University Amsterdam - Department of Computer Science

Frank van Harmelen

VU University Amsterdam - Department of Artificial Intelligence

Henri Bal

VU University Amsterdam - Department of Computer Science

Abstract

In the last few years a new research area, called stream reasoning, emerged to bridge the gap between reasoning and stream processing. While current reasoning approaches are designed to work on mainly static data, the Web is, on the other hand, extremely dynamic: information is frequently changed and updated, and new data is continuously generated from a huge number of sources, often at high rate. In other words, fresh information is constantly made available in the form of streams of new data and updates. Despite some promising investigations in the area, stream reasoning is still in its infancy, both from the perspective of models and theories development, and from the perspective of systems and tools design and implementation. The aim of this paper is threefold: (i) we identify the requirements coming from different application scenarios, and we isolate the problems they pose; (ii) we survey existing approaches and proposals in the area of stream reasoning, highlighting their strengths and limitations; (iii) we draw a research agenda to guide the future research and development of stream reasoning. In doing so, we also analyze related research fields to extract algorithms, models, techniques, and solutions that could be useful in the area of stream reasoning.

Keywords: Semantic Web, Stream Reasoning, Survey, Stream Processing, Complex Event Processing

Suggested Citation

Margara, Alessandro and Urbani, Jacopo and van Harmelen, Frank and Bal, Henri, Streaming the Web: Reasoning Over Dynamic Data (March 2014). Journal of Web Semantics First Look, Available at SSRN: https://ssrn.com/abstract=3199091 or http://dx.doi.org/10.2139/ssrn.3199091

Alessandro Margara (Contact Author)

VU University Amsterdam - Department of Computer Science ( email )

De Boelelaan 1081
1081 HV Amsterdam
Netherlands

Jacopo Urbani

VU University Amsterdam - Department of Computer Science ( email )

De Boelelaan 1081
1081 HV Amsterdam
Netherlands

Frank Van Harmelen

VU University Amsterdam - Department of Artificial Intelligence ( email )

De Boelelaan 1081
1081 HV Amsterdam
Netherlands

Henri Bal

VU University Amsterdam - Department of Computer Science ( email )

De Boelelaan 1081
1081 HV Amsterdam
Netherlands

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