dataunderlag
Dataunderlag is a Swedish term for the data foundation used to support analyses, decisions, and reporting. It includes datasets, their metadata, and the documentation describing how the data were collected, processed, and organized. A dataunderlag should be fit for purpose, accurate, timely, and sufficiently complete to support the intended analysis.
Core elements are data sources (primary data collected for a purpose and secondary data reused from existing
Quality and governance focus on validity, reliability, completeness, and timeliness, as well as provenance. Privacy, security,
Uses include informing research, policy making, performance evaluation, risk assessment, and forecasting. It supports model calibration,
Challenges include fragmented sources, inconsistent formats, missing values, biases, and balancing openness with privacy. Best practices
Examples vary by sector. A municipal dataunderlag might comprise census figures, land use data, transport counts,
The dataunderlag lifecycle covers collection, validation, storage, sharing, reuse, archiving, and disposal, with ongoing maintenance to