Interoperability-oriented Quality Assessment for Czech Open Data

Dasa Kusnirakova, Mouzhi Ge, Leonard Walletzky, Barbora Buhnova

2022

Abstract

With the rapid increase of published open datasets, it is crucial to support the open data progress in smart cities while considering the open data quality. In the Czech Republic, and its National Open Data Catalogue (NODC), the open datasets are usually evaluated based on their metadata only, while leaving the content and the adherence to the recommended data structure to the sole responsibility of the data providers. The interoperability of open datasets remains unknown. This paper therefore aims to propose a novel content-aware quality evaluation framework that assesses the quality of open datasets based on five data quality dimensions. With the proposed framework, we provide a fundamental view on the interoperability-oriented data quality of Czech open datasets, which are published in NODC. Our evaluations find that domain-specific open data quality assessments are able to detect data quality issues beyond traditional heuristics used for determining Czech open data quality, increase their interoperability, and thus increase their potential to bring value for the society. The findings of this research are beneficial not only for the case of the Czech Republic, but also can be applied in other countries that intend to enhance their open data quality evaluation processes.

Paper Citation

in Harvard Style

Kusnirakova D., Ge M., Walletzky L. and Buhnova B. (2022). Interoperability-oriented Quality Assessment for Czech Open Data. In Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-583-8, pages 446-453. DOI: 10.5220/0011291900003269

in Bibtex Style

@conference{data22,
author={Dasa Kusnirakova and Mouzhi Ge and Leonard Walletzky and Barbora Buhnova},
title={Interoperability-oriented Quality Assessment for Czech Open Data},
booktitle={Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2022},
pages={446-453},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011291900003269},
isbn={978-989-758-583-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Interoperability-oriented Quality Assessment for Czech Open Data
SN - 978-989-758-583-8
AU - Kusnirakova D.
AU - Ge M.
AU - Walletzky L.
AU - Buhnova B.
PY - 2022
SP - 446
EP - 453
DO - 10.5220/0011291900003269