Sulthoni Asshidiqqi 

Date/Time: 25.09.2024, 12:00-12:45 

Location: D2.2.094 

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 process, e.g., how the statistical data 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. In addition, an effective and efficient metadata integration method is also needed to facilitate the integration process. 

This (PhD) study aims to build an ontology integrating statistical data production standards (Generic Statistical Business Process Model, Generic Statistical Information Model, Generic Activity Model for Statistical Organizations, and Common Statistical Production Architecture) into an ontology for statistical metadata integration. This ontology will serve as a basis to develop a method for integrating statistical metadata using the established ontology to enhance information openness in data production, performance measurement, and metadata quality assurance.