Research news on improvement of scientific data usability

Improvement of scientific data usability encompasses methodological approaches aimed at enhancing the findability, accessibility, interoperability, and reusability (FAIR principles) of research data throughout its lifecycle. Methods include standardized metadata schemas, controlled vocabularies, and ontologies to ensure semantic consistency; implementation of open, non-proprietary file formats; rigorous data curation, normalization, and quality control pipelines; and adoption of persistent identifiers and rich provenance tracking for reproducibility. Additional practices involve designing machine-actionable data structures (e.g., well-documented APIs, standardized tabular or hierarchical formats), applying community-agreed reporting standards, and integrating data into interoperable repositories that support advanced querying, federation, and downstream computational analysis.

Swiss researchers hoard vast trove of NASA climate data

Researchers have copied massive quantities of publicly available climate and environmental data from NASA onto a Swiss supercomputer to train artificial intelligence models—and for safekeeping amid U.S. funding cuts.

Genetic databases as the key to global benefit-sharing

An international research team led by the Science Policy and Internationalization Department at the Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures has published a practical guide in the journal ...

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