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.
Original language | English |
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Title of host publication | Proceedings of 2024 IEEE International Conference on Data and Software Engineering |
Subtitle of host publication | Data-Driven Innovation: Transforming Industries and Societies, ICoDSE 2024 |
Place of Publication | Danvers |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 37-42 |
Number of pages | 6 |
ISBN (Electronic) | 9798331506407 |
ISBN (Print) | 9798331506414 |
DOIs | |
Publication status | Published - 2024 |
Event | 2024 IEEE International Conference on Data and Software Engineering, ICoDSE 2024 - Hybrid, Gorontalo, Indonesia Duration: 30 Oct 2024 → 31 Oct 2024 |
Conference
Conference | 2024 IEEE International Conference on Data and Software Engineering, ICoDSE 2024 |
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Country/Territory | Indonesia |
City | Hybrid, Gorontalo |
Period | 30/10/24 → 31/10/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- data integration
- ontology
- statistical metadata