Interoperability-oriented Quality Assessment for Czech Open Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00125959" target="_blank" >RIV/00216224:14330/22:00125959 - isvavai.cz</a>
Result on the web
<a href="https://www.scitepress.org/PublicationsDetail.aspx?ID=UrE+LJsln4A=&t=1" target="_blank" >https://www.scitepress.org/PublicationsDetail.aspx?ID=UrE+LJsln4A=&t=1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0011291900003269" target="_blank" >10.5220/0011291900003269</a>
Alternative languages
Result language
angličtina
Original language name
Interoperability-oriented Quality Assessment for Czech Open Data
Original language description
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.
Czech name
—
Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 11th International Conference on Data Science, Technology and Applications
ISBN
9789897585838
ISSN
2184-285X
e-ISSN
—
Number of pages
8
Pages from-to
446-453
Publisher name
Scitepress
Place of publication
Lisbon, Portugal
Event location
Lisbon, Portugal
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000852749000047