Streaming the Web: Reasoning over dynamic data

Research output: Contribution to JournalArticleAcademicpeer-review

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. © 2014 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)24-44
Number of pages21
JournalJournal of Web Semantics
Volume25
DOIs
Publication statusPublished - 2014

Fingerprint

Processing

Keywords

  • Complex Event Processing
  • Semantic Web
  • Stream processing
  • Stream reasoning
  • Survey

Cite this

@article{29462648d9424241ae9f3c6d4eb31e12,
title = "Streaming the Web: Reasoning over dynamic data",
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. {\circledC} 2014 Elsevier B.V. All rights reserved.",
keywords = "Complex Event Processing, Semantic Web, Stream processing, Stream reasoning, Survey",
author = "Alessandro Margara and Jacopo Urbani and {Van Harmelen}, Frank and Henri Bal",
year = "2014",
doi = "10.1016/j.websem.2014.02.001",
language = "English",
volume = "25",
pages = "24--44",
journal = "Journal of Web Semantics",
issn = "1570-8268",
publisher = "Elsevier",

}

Streaming the Web: Reasoning over dynamic data. / Margara, Alessandro; Urbani, Jacopo; Van Harmelen, Frank; Bal, Henri.

In: Journal of Web Semantics, Vol. 25, 2014, p. 24-44.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Streaming the Web: Reasoning over dynamic data

AU - Margara, Alessandro

AU - Urbani, Jacopo

AU - Van Harmelen, Frank

AU - Bal, Henri

PY - 2014

Y1 - 2014

N2 - 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. © 2014 Elsevier B.V. All rights reserved.

AB - 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. © 2014 Elsevier B.V. All rights reserved.

KW - Complex Event Processing

KW - Semantic Web

KW - Stream processing

KW - Stream reasoning

KW - Survey

U2 - 10.1016/j.websem.2014.02.001

DO - 10.1016/j.websem.2014.02.001

M3 - Article

VL - 25

SP - 24

EP - 44

JO - Journal of Web Semantics

JF - Journal of Web Semantics

SN - 1570-8268

ER -