research-article

LOP: capturing and linking open provenance on LOD cycle

Authors:

Rogers Reiche de Mendonça,

Sérgio Manuel Serra da Cruz,

Jonas F. S. M. De La Cerda,

Maria Cláudia Cavalcanti,

Kelli Faria Cordeiro,

Maria Luiza M. CamposAuthors Info & Claims

SWIM '13: Proceedings of the Fifth Workshop on Semantic Web Information Management

Article No.: 3, Pages 1 - 8

https://doi.org/10.1145/2484712.2484715

Published: 23 June 2013 Publication History

Abstract

The Web of Data has emerged as a means to expose, share, reuse, and connect information on the Web identified by URIs using RDF as a data model, following Linked Data Principles. However, the reuse of third party data can be compromised without proper data quality assessments. In this context, important questions emerge: how can one trust on published data and links? Which manipulation, modification and integration operations have been applied to the data before its publication? What is the nature of comparisons or transformations applied to data during the interlinking process? In this scenario, provenance becomes a fundamental element. In this paper, we describe an approach for generating and capturing Linked Open Provenance (LOP) to support data quality and trustworthiness assessments, which covers preparation and format transformation of traditional data sources, up to dataset publication and interlinking. The proposed architecture takes advantage of provenance agents, orchestrated by an ETL workflow approach, to collect provenance at any specified level and also link it with its corresponding data. We also describe a real use case scenario where the architecture was implemented to evaluate the proposal.

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Cited By

Randles AJunior AO'Sullivan D(2021)A Vocabulary for Describing Mapping Quality Assessment, Refinement and Validation2021 IEEE 15th International Conference on Semantic Computing (ICSC)10.1109/ICSC50631.2021.00076(425-430)Online publication date: Jan-2021
https://doi.org/10.1109/ICSC50631.2021.00076
Sikos LPhilp D(2020)Provenance-Aware Knowledge Representation: A Survey of Data Models and Contextualized Knowledge GraphsData Science and Engineering10.1007/s41019-020-00118-0Online publication date: 8-May-2020
https://doi.org/10.1007/s41019-020-00118-0
dos Reis Cda Silva WMartins LPinheiro RVictorino MHolanda MChbeir RManolopoulos YIlarri SPapadopoulos A(2019)Enhancing Open Government Data With Data ProvenanceProceedings of the 11th International Conference on Management of Digital EcoSystems10.1145/3297662.3365791(142-149)Online publication date: 12-Nov-2019
https://dl.acm.org/doi/10.1145/3297662.3365791
Show More Cited By

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LOP: capturing and linking open provenance on LOD cycle

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Published In

cover image ACM Conferences

SWIM '13: Proceedings of the Fifth Workshop on Semantic Web Information Management

June 2013

50 pages

ISBN:9781450321945

DOI:10.1145/2484712

General Chairs:
Roberto De Virgilio
Universitá Roma Tre, Italy
,
Fausto Giunchiglia
Universitá di Trento, Italy
,
Letizia Tanca
Politecnico di Milano, Italy

Copyright © 2013 ACM.

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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SIGMOD: ACM Special Interest Group on Management of Data

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New York, NY, United States

Publication History

Published: 23 June 2013

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SIGMOD/PODS'13: International Conference on Management of Data

June 23, 2013

New York, New York

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Cited By

Randles AJunior AO'Sullivan D(2021)A Vocabulary for Describing Mapping Quality Assessment, Refinement and Validation2021 IEEE 15th International Conference on Semantic Computing (ICSC)10.1109/ICSC50631.2021.00076(425-430)Online publication date: Jan-2021
https://doi.org/10.1109/ICSC50631.2021.00076
Sikos LPhilp D(2020)Provenance-Aware Knowledge Representation: A Survey of Data Models and Contextualized Knowledge GraphsData Science and Engineering10.1007/s41019-020-00118-0Online publication date: 8-May-2020
https://doi.org/10.1007/s41019-020-00118-0
dos Reis Cda Silva WMartins LPinheiro RVictorino MHolanda MChbeir RManolopoulos YIlarri SPapadopoulos A(2019)Enhancing Open Government Data With Data ProvenanceProceedings of the 11th International Conference on Management of Digital EcoSystems10.1145/3297662.3365791(142-149)Online publication date: 12-Nov-2019
https://dl.acm.org/doi/10.1145/3297662.3365791
Hänel CKhatami MKuhlen TWeyers BLawonn KHlawitschka MRosenthal P(2016)Towards multi-user provenance tracking of visual analysis workflows over multiple applicationsProceedings of the EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization10.5555/3057025.3057034(23-27)Online publication date: 6-Jun-2016
https://dl.acm.org/doi/10.5555/3057025.3057034
AlObaidi MMahmood KSabra SBourdeau JHendler JNkambou RHorrocks IZhao B(2016)Semantic Enrichment for Local Search Engine using Linked Open DataProceedings of the 25th International Conference Companion on World Wide Web10.1145/2872518.2890481(631-634)Online publication date: 11-Apr-2016
https://dl.acm.org/doi/10.1145/2872518.2890481
da Cruz SBarbosa LZavaleta JCosta RCampos MCho YShin SKim SHung CHong J(2014)Collecting cloud provenance metadata with MatriohskaProceedings of the 29th Annual ACM Symposium on Applied Computing10.1145/2554850.2555066(351-356)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.1145/2554850.2555066

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