An Ontology for Capturing and Integrating Statistical Data Production Metadata

Sulthoni Ashiddiiqi, Fajar J. Ekaputra, Muhammad Z.C. Candra, G. A.Putri Saptawati

Publikation: Beitrag in Buch/KonferenzbandBeitrag in Konferenzband

Abstract

A complete and integrated metadata is essential to support the openness and transparency of statistical data provided by governments and global organizations. Such metadata not only provide information about statistical data structure, but also offer crucial details and insights into the entire statistical data production processes, e.g., how the statistical data production are planned, collected, processed, and eventually published. However, creating comprehensive metadata about statistical data production requires an ontology capable of accommodating and integrating various types of relevant statistical metadata. To address this challenge, this paper proposed the Statistical Data Production Ontology (SDPO), an ontology that aim to serve as an integrator for statistical metadata relevant to statistical data production. SDPO is constructed based on existing standards of statistical data production, enhancing confidence in the completeness of the coverage of various data production processes and types of statistical metadata included. We evaluated the ontology through a set of predefined competency questions and OOPS! ontology evaluation tool with promising results.

OriginalspracheEnglisch
Titel des SammelwerksProceedings of 2024 IEEE International Conference on Data and Software Engineering
Untertitel des SammelwerksData-Driven Innovation: Transforming Industries and Societies, ICoDSE 2024
ErscheinungsortDanvers
VerlagInstitute of Electrical and Electronics Engineers Inc.
Seiten37-42
Seitenumfang6
ISBN (elektronisch)9798331506407
ISBN (Print)9798331506414
DOIs
PublikationsstatusVeröffentlicht - 2024
Veranstaltung2024 IEEE International Conference on Data and Software Engineering, ICoDSE 2024 - Hybrid, Gorontalo, Indonesien
Dauer: 30 Okt. 202431 Okt. 2024

Konferenz

Konferenz2024 IEEE International Conference on Data and Software Engineering, ICoDSE 2024
Land/GebietIndonesien
OrtHybrid, Gorontalo
Zeitraum30/10/2431/10/24

Bibliographische Notiz

Publisher Copyright:
© 2024 IEEE.

Zitat