LinkedDataLens: Linked Data as a Network of Networks

Y Gil; P.T. Groth

doi:10.1145/1999676.1999720

LinkedDataLens: Linked Data as a Network of Networks

Y Gil, P.T. Groth

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

With billions of assertions and counting, the Web of Data represents the largest multi-contributor interlinked knowledge base that ever existed. We present a novel framework for analyzing and using the Web of Data based on extracting and analyzing thematic subsets of it. We view the Web of Data as a "network of networks" from which to extract meaningful subsets that can be converted them into self-contained networks to be further analyzed and reused. These extracted networks can then be analyzed through network analysis and discovery algorithms, and the results of these analyses can be published back on the Web of Data. We describe LinkedDataLens, an implementation of this framework that uses the Wings workflow system to represent multi-step network extraction and analysis processes. © 2011 Authors.

Original language	English
Title of host publication	Proceedings of the 6th International Conference on Knowledge Capture (K-CAP 2011)
Editors	M.A. Musen, Ó Corcho
Publisher	ACM
Pages	191-192
ISBN (Print)	978-1-4503-0396-8
DOIs	https://doi.org/10.1145/1999676.1999720
Publication status	Published - 2011
Event	International Conference on Knowledge Capture - Duration: 1 Jan 2011 → 1 Jan 2011

Conference

Conference	International Conference on Knowledge Capture
Period	1/01/11 → 1/01/11

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10.1145/1999676.1999720

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@inproceedings{294d8978c7a04bb6af5f6ef414626e6d,

title = "LinkedDataLens: Linked Data as a Network of Networks",

abstract = "With billions of assertions and counting, the Web of Data represents the largest multi-contributor interlinked knowledge base that ever existed. We present a novel framework for analyzing and using the Web of Data based on extracting and analyzing thematic subsets of it. We view the Web of Data as a {"}network of networks{"} from which to extract meaningful subsets that can be converted them into self-contained networks to be further analyzed and reused. These extracted networks can then be analyzed through network analysis and discovery algorithms, and the results of these analyses can be published back on the Web of Data. We describe LinkedDataLens, an implementation of this framework that uses the Wings workflow system to represent multi-step network extraction and analysis processes. {\textcopyright} 2011 Authors.",

author = "Y Gil and P.T. Groth",

year = "2011",

doi = "10.1145/1999676.1999720",

language = "English",

isbn = "978-1-4503-0396-8",

pages = "191--192",

editor = "M.A. Musen and {\'O} Corcho",

booktitle = "Proceedings of the 6th International Conference on Knowledge Capture (K-CAP 2011)",

publisher = "ACM",

note = "International Conference on Knowledge Capture ; Conference date: 01-01-2011 Through 01-01-2011",

}

TY - GEN

T1 - LinkedDataLens: Linked Data as a Network of Networks

AU - Gil, Y

AU - Groth, P.T.

PY - 2011

Y1 - 2011

N2 - With billions of assertions and counting, the Web of Data represents the largest multi-contributor interlinked knowledge base that ever existed. We present a novel framework for analyzing and using the Web of Data based on extracting and analyzing thematic subsets of it. We view the Web of Data as a "network of networks" from which to extract meaningful subsets that can be converted them into self-contained networks to be further analyzed and reused. These extracted networks can then be analyzed through network analysis and discovery algorithms, and the results of these analyses can be published back on the Web of Data. We describe LinkedDataLens, an implementation of this framework that uses the Wings workflow system to represent multi-step network extraction and analysis processes. © 2011 Authors.

AB - With billions of assertions and counting, the Web of Data represents the largest multi-contributor interlinked knowledge base that ever existed. We present a novel framework for analyzing and using the Web of Data based on extracting and analyzing thematic subsets of it. We view the Web of Data as a "network of networks" from which to extract meaningful subsets that can be converted them into self-contained networks to be further analyzed and reused. These extracted networks can then be analyzed through network analysis and discovery algorithms, and the results of these analyses can be published back on the Web of Data. We describe LinkedDataLens, an implementation of this framework that uses the Wings workflow system to represent multi-step network extraction and analysis processes. © 2011 Authors.

U2 - 10.1145/1999676.1999720

DO - 10.1145/1999676.1999720

M3 - Conference contribution

SN - 978-1-4503-0396-8

SP - 191

EP - 192

BT - Proceedings of the 6th International Conference on Knowledge Capture (K-CAP 2011)

A2 - Musen, M.A.

A2 - Corcho, Ó

PB - ACM

T2 - International Conference on Knowledge Capture

Y2 - 1 January 2011 through 1 January 2011

ER -

LinkedDataLens: Linked Data as a Network of Networks

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