LinkedDataLens: Linked data as a network of networks

Yolanda Gil; Paul Groth

doi:10.1145/1999676.1999720

LinkedDataLens: Linked data as a network of networks

Yolanda Gil, Paul Groth

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

1 Scopus citations

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.

Original language	English
Title of host publication	KCAP 2011 - Proceedings of the 2011 Knowledge Capture Conference
Pages	191-192
Number of pages	2
DOIs	https://doi.org/10.1145/1999676.1999720
State	Published - 2011
Externally published	Yes
Event	6th International Conference on Knowledge Capture, KCAP 2011 - Banff, AB, Canada Duration: Jun 26 2011 → Jun 29 2011

Publication series

Name	KCAP 2011 - Proceedings of the 2011 Knowledge Capture Conference

Conference

Conference	6th International Conference on Knowledge Capture, KCAP 2011
Country/Territory	Canada
City	Banff, AB
Period	06/26/11 → 06/29/11

Keywords

knowledge capture
linked open data
network analysis
web of data

Access to Document

10.1145/1999676.1999720

Cite this

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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.",

keywords = "knowledge capture, linked open data, network analysis, web of data",

author = "Yolanda Gil and Paul Groth",

year = "2011",

doi = "10.1145/1999676.1999720",

language = "Ingl{\'e}s",

isbn = "9781450303965",

series = "KCAP 2011 - Proceedings of the 2011 Knowledge Capture Conference",

pages = "191--192",

booktitle = "KCAP 2011 - Proceedings of the 2011 Knowledge Capture Conference",

note = "6th International Conference on Knowledge Capture, KCAP 2011 ; Conference date: 26-06-2011 Through 29-06-2011",

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TY - GEN

T1 - LinkedDataLens

T2 - 6th International Conference on Knowledge Capture, KCAP 2011

AU - Gil, Yolanda

AU - Groth, Paul

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.

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.

KW - knowledge capture

KW - linked open data

KW - network analysis

KW - web of data

UR - http://www.scopus.com/inward/record.url?scp=79960219751&partnerID=8YFLogxK

U2 - 10.1145/1999676.1999720

DO - 10.1145/1999676.1999720

M3 - Contribución a la conferencia

AN - SCOPUS:79960219751

SN - 9781450303965

T3 - KCAP 2011 - Proceedings of the 2011 Knowledge Capture Conference

SP - 191

EP - 192

BT - KCAP 2011 - Proceedings of the 2011 Knowledge Capture Conference

Y2 - 26 June 2011 through 29 June 2011

ER -

LinkedDataLens: Linked data as a network of networks

Abstract

Publication series

Conference

Keywords

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