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An assessment of high-value datasets: How accessible are these datasets across Europe?

An assessment of high-value datasets: How accessible are these datasets across Europe?

Recently, we published our study ‘High-value datasets: Cross-country findability and comparability of metada’, which highlights the critical need for improved findability and metadata accessibility of high-value datasets (HVDs) across European Union Member States. Conducted between April and May 2024, before the Commission Implementing Regulation in force since June 2024, the study evaluates the availability and usability of 24 datasets from Denmark, Estonia, Latvia, and Finland. It focuses on six thematic categories: geospatial, earth observation and environment, meteorological, statistics, companies and company ownership, and mobility.  

The study reveals that while most HVDs are generally accessible, there are significant inconsistencies in metadata clarity and language. For instance, 6 out of 24 datasets were published only in the national language, creating a translation difficulty for international users. Additionally, eight of the datasets lacked references to relevant regulations, complicating efforts to verify compliance. Despite these challenges, the study found that 20 out of 24 datasets were easily available. 

To address these issues, the report recommends several actions for Member States. These include referencing the regulation in metadata, using standardised dataset titles, enriching metadata with detailed descriptions, and adhering to DCAT-AP guidelines for structured metadata. Implementing these recommendations would significantly improve the findability and usability of HVDs, facilitating better data sharing and reuse across the EU. Additionally, the report contains a section on the user’s experience with finding HVD’s on our data.europa.eu platform 

In conclusion, the study emphasises the need for a harmonised approach to metadata standardisation and dataset tagging. By adopting the recommended practices, Member States can enhance the accessibility and interoperability of high-value datasets, ultimately supporting transparency and innovation in various sectors. 

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