Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data

C.I. Bucur, Fiorela Ciroku, Tatiana Makhalova, Ettore Rizza, Thiviyan Thanapalasingam, Dalia Varanka, Michael Wolowyk, John Domingue

Research output: Chapter in Book / Report / Conference proceedingChapterAcademic

Abstract

Linked Open Data (LOD) is the publicly available RDF data in the Web. Each
LOD entity is identified by a URI and accessible via HTTP. LOD encodes globalscale
knowledge potentially available to any human as well as artificial intelligence
that may want to benefit from it as background knowledge for supporting
their tasks. LOD has emerged as the backbone of applications in diverse fields
such as Natural Language Processing, Information Retrieval, Computer Vision,
Speech Recognition, and many more. Nevertheless, regardless of the specific
tasks that LOD-based tools aim to address, the reuse of such knowledge may
be challenging for diverse reasons, e.g. semantic heterogeneity, provenance, and
data quality. As aptly stated by Heath et al. “Linked Data might be outdated,
imprecise, or simply wrong”: there arouses a necessity to investigate the problem
of linked data validity. This work reports a collaborative effort performed
by nine teams of students, guided by an equal number of senior researchers, attending
the International Semantic Web Research School (ISWS 2018) towards
addressing such investigation from different perspectives coupled with different
approaches to tackle the issue.
Original languageEnglish
Title of host publicationLinked Open Data Validity -- A Technical Report from ISWS 2018
Subtitle of host publicationA Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data
Chapter9
Pages88-97
Number of pages10
Publication statusPublished - 2019

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HTTP
Data privacy
Semantic Web
Information retrieval
Speech recognition
Computer vision
Semantics
Students
Processing

Cite this

Bucur, C. I., Ciroku, F., Makhalova, T., Rizza, E., Thanapalasingam, T., Varanka, D., ... Domingue, J. (2019). Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data. In Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data (pp. 88-97)
Bucur, C.I. ; Ciroku, Fiorela ; Makhalova, Tatiana ; Rizza, Ettore ; Thanapalasingam, Thiviyan ; Varanka, Dalia ; Wolowyk, Michael ; Domingue, John. / Linked Open Data Validity -- A Technical Report from ISWS 2018 : A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data. Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data. 2019. pp. 88-97
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title = "Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data",
abstract = "Linked Open Data (LOD) is the publicly available RDF data in the Web. EachLOD entity is identified by a URI and accessible via HTTP. LOD encodes globalscaleknowledge potentially available to any human as well as artificial intelligencethat may want to benefit from it as background knowledge for supportingtheir tasks. LOD has emerged as the backbone of applications in diverse fieldssuch as Natural Language Processing, Information Retrieval, Computer Vision,Speech Recognition, and many more. Nevertheless, regardless of the specifictasks that LOD-based tools aim to address, the reuse of such knowledge maybe challenging for diverse reasons, e.g. semantic heterogeneity, provenance, anddata quality. As aptly stated by Heath et al. “Linked Data might be outdated,imprecise, or simply wrong”: there arouses a necessity to investigate the problemof linked data validity. This work reports a collaborative effort performedby nine teams of students, guided by an equal number of senior researchers, attendingthe International Semantic Web Research School (ISWS 2018) towardsaddressing such investigation from different perspectives coupled with differentapproaches to tackle the issue.",
author = "C.I. Bucur and Fiorela Ciroku and Tatiana Makhalova and Ettore Rizza and Thiviyan Thanapalasingam and Dalia Varanka and Michael Wolowyk and John Domingue",
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Bucur, CI, Ciroku, F, Makhalova, T, Rizza, E, Thanapalasingam, T, Varanka, D, Wolowyk, M & Domingue, J 2019, Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data. in Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data. pp. 88-97.

Linked Open Data Validity -- A Technical Report from ISWS 2018 : A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data. / Bucur, C.I.; Ciroku, Fiorela; Makhalova, Tatiana; Rizza, Ettore; Thanapalasingam, Thiviyan; Varanka, Dalia; Wolowyk, Michael; Domingue, John.

Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data. 2019. p. 88-97.

Research output: Chapter in Book / Report / Conference proceedingChapterAcademic

TY - CHAP

T1 - Linked Open Data Validity -- A Technical Report from ISWS 2018

T2 - A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data

AU - Bucur, C.I.

AU - Ciroku, Fiorela

AU - Makhalova, Tatiana

AU - Rizza, Ettore

AU - Thanapalasingam, Thiviyan

AU - Varanka, Dalia

AU - Wolowyk, Michael

AU - Domingue, John

PY - 2019

Y1 - 2019

N2 - Linked Open Data (LOD) is the publicly available RDF data in the Web. EachLOD entity is identified by a URI and accessible via HTTP. LOD encodes globalscaleknowledge potentially available to any human as well as artificial intelligencethat may want to benefit from it as background knowledge for supportingtheir tasks. LOD has emerged as the backbone of applications in diverse fieldssuch as Natural Language Processing, Information Retrieval, Computer Vision,Speech Recognition, and many more. Nevertheless, regardless of the specifictasks that LOD-based tools aim to address, the reuse of such knowledge maybe challenging for diverse reasons, e.g. semantic heterogeneity, provenance, anddata quality. As aptly stated by Heath et al. “Linked Data might be outdated,imprecise, or simply wrong”: there arouses a necessity to investigate the problemof linked data validity. This work reports a collaborative effort performedby nine teams of students, guided by an equal number of senior researchers, attendingthe International Semantic Web Research School (ISWS 2018) towardsaddressing such investigation from different perspectives coupled with differentapproaches to tackle the issue.

AB - Linked Open Data (LOD) is the publicly available RDF data in the Web. EachLOD entity is identified by a URI and accessible via HTTP. LOD encodes globalscaleknowledge potentially available to any human as well as artificial intelligencethat may want to benefit from it as background knowledge for supportingtheir tasks. LOD has emerged as the backbone of applications in diverse fieldssuch as Natural Language Processing, Information Retrieval, Computer Vision,Speech Recognition, and many more. Nevertheless, regardless of the specifictasks that LOD-based tools aim to address, the reuse of such knowledge maybe challenging for diverse reasons, e.g. semantic heterogeneity, provenance, anddata quality. As aptly stated by Heath et al. “Linked Data might be outdated,imprecise, or simply wrong”: there arouses a necessity to investigate the problemof linked data validity. This work reports a collaborative effort performedby nine teams of students, guided by an equal number of senior researchers, attendingthe International Semantic Web Research School (ISWS 2018) towardsaddressing such investigation from different perspectives coupled with differentapproaches to tackle the issue.

M3 - Chapter

SP - 88

EP - 97

BT - Linked Open Data Validity -- A Technical Report from ISWS 2018

ER -

Bucur CI, Ciroku F, Makhalova T, Rizza E, Thanapalasingam T, Varanka D et al. Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data. In Linked Open Data Validity -- A Technical Report from ISWS 2018: A Decentralized Approach to Validating Personal Data Using a Combination of Blockchains and Linked Data. 2019. p. 88-97