Datasuch

Datasuch is a conceptual framework for discovering and retrieving datasets across heterogeneous data repositories through a unified search and access interface. It aims to bridge silos by enabling researchers, analysts, and organizations to locate data assets based on descriptive metadata, content attributes, licensing, and provenance, rather than by source alone. The term appears in data science literature as a way to describe federated data discovery that respects source governance while offering a coherent user experience.

Its architecture typically includes a metadata catalog that indexes datasets, a federated query planner that translates user requests into source-specific queries, adapters or connectors for various data stores (databases, data lakes, APIs), and a policy engine that enforces access controls and usage restrictions. Data provenance tracking records lineage from source to result, supporting reproducibility. The framework supports schema-agnostic search, schema mapping, and pluggable ranking to surface relevant data assets.

Datasuch has been explored in research prototypes and pilot portals, particularly in environments with multiple data custodians. Use cases include academic data discovery, enterprise data lake navigation, and public sector data portals. Critics note that achieving reliable performance, maintaining consistent metadata quality, and enforcing governance across diverse sources remain challenging. Privacy-preserving techniques, such as access-limited querying and data masked previews, are often incorporated to mitigate risk.

See also: data federation, data catalog, data provenance, schema mapping, data governance.