A Fuzzy Approach for Data Quality Assessment of Linked Datasets

Narciso Arruda, J. Alcântara, V. Vidal, Angelo Brayner, M. Casanova, V. Pequeno, Wellington Franco

Abstract

For several applications, an integrated view of linked data, denoted linked data mashup, is a critical requirement. Nonetheless, the quality of linked data mashups highly depends on the quality of the data sources. In this sense, it is essential to analyze data source quality and to make this information explicit to consumers of such data. This paper introduces a fuzzy ontology to represent the quality of linked data source. Furthermore, the paper shows the applicability of the fuzzy ontology in the process of evaluating data source quality used to build linked data mashups.

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Paper Citation


in Harvard Style

Arruda N., Alcântara J., Vidal V., Brayner A., Casanova M., Pequeno V. and Franco W. (2019). A Fuzzy Approach for Data Quality Assessment of Linked Datasets.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-372-8, pages 399-406. DOI: 10.5220/0007718803990406


in Bibtex Style

@conference{iceis19,
author={Narciso Arruda and J. Alcântara and V. Vidal and Angelo Brayner and M. Casanova and V. Pequeno and Wellington Franco},
title={A Fuzzy Approach for Data Quality Assessment of Linked Datasets},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2019},
pages={399-406},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007718803990406},
isbn={978-989-758-372-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Fuzzy Approach for Data Quality Assessment of Linked Datasets
SN - 978-989-758-372-8
AU - Arruda N.
AU - Alcântara J.
AU - Vidal V.
AU - Brayner A.
AU - Casanova M.
AU - Pequeno V.
AU - Franco W.
PY - 2019
SP - 399
EP - 406
DO - 10.5220/0007718803990406