research-article

Monitoring the dynamism of the linked data space through environment abstraction

Authors:

Riza Cenk Erdur,

Oylum Alatli,

Tayfun Gökmen Halaç,

Oguz DikenelliAuthors Info & Claims

I-SEMANTICS '13: Proceedings of the 9th International Conference on Semantic Systems

Pages 81 - 88

https://doi.org/10.1145/2506182.2506193

Published: 04 September 2013 Publication History

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Abstract

Management of data dynamics is a major issue for linked data applications. There are some approaches and applications addressing this problem which are either pull or push based. However, these one sided solutions do not solve the problem since pull based approaches bring an overhead to data consumers, and push based approaches require the collaboration of the data publishers which is contrary to the free nature of the Web of Data. In this paper, to monitor the dynamism of the linked data space, we present an infrastructure that combines pull and push approaches to monitor the changes of SPARQL queries over the linked data space. In the design of this infrastructure, environment abstraction of multi-agent systems domain is followed. The proposed infrastructure has been built upon the CArtAgO environment infrastructure, and VoID based federated query engine, WoDQA, is incorporated into CArtAgO to handle dynamic discovery of datasets and execution of monitored SPARQL queries.

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Cited By

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SOYGAZİ FTUĞLULAR TDİKENELLİ O(2023)Data Management and Ontology Development for Provenance-Aware Organizations in Linked Data SpaceEuropean Journal of Technic10.36222/ejt.1402149Online publication date: 26-Dec-2023
https://doi.org/10.36222/ejt.1402149
Dikenelli OAlatlı OErdur R(2014)Where Are All the Semantic Web AgentsRevised Selected and Invited Papers of the 4th International Workshop on Agent Environments for Multi-Agent Systems IV - Volume 906810.1007/978-3-319-23850-0_3(41-51)Online publication date: 6-May-2014
https://dl.acm.org/doi/10.1007/978-3-319-23850-0_3

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I-SEMANTICS '13: Proceedings of the 9th International Conference on Semantic Systems

September 2013

158 pages

ISBN:9781450319720

DOI:10.1145/2506182

Editors:
Marta Sabou
MODUL University Vienna, Austria
,
Eva Blomqvist
Linköpings Universitet, Sweden
,
Tommaso Di Noia
Technical University of Bari, Italy
,
Harald Sack
Hasso-Plattner-Institute for IT Systems Engineering, Germany
,
Tassilo Pellegrini
St. Pölten University of Applied Sciences, Austria

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 04 September 2013

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Türkiye Bilimsel ve Teknolojik Arastirma Kurumu

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ISEM '13

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St. Pölten University
HPI
Compass Verlag
Wolters Kluwer
Semantic Web Company
TUG

ISEM '13: I-SEMANTICS 2013 - 9th International Conference on Semantic Systems

September 4 - 6, 2013

Graz, Austria

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SOYGAZİ FTUĞLULAR TDİKENELLİ O(2023)Data Management and Ontology Development for Provenance-Aware Organizations in Linked Data SpaceEuropean Journal of Technic10.36222/ejt.1402149Online publication date: 26-Dec-2023
https://doi.org/10.36222/ejt.1402149
Dikenelli OAlatlı OErdur R(2014)Where Are All the Semantic Web AgentsRevised Selected and Invited Papers of the 4th International Workshop on Agent Environments for Multi-Agent Systems IV - Volume 906810.1007/978-3-319-23850-0_3(41-51)Online publication date: 6-May-2014
https://dl.acm.org/doi/10.1007/978-3-319-23850-0_3

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Integrating Linked Data Space with Agents Using the Environment Abstraction

Towards a Linked Geospatial Data Infrastructure

Supporting scalable data analytics on large linked data

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