Kohdedatan

Kohdedatan is a term used in information science and digital humanities to describe a workflow for integrating data from heterogeneous sources to support comprehensive analysis. As a concept rather than a single technology, kohdedatan encompasses activities such as data discovery, metadata harmonization, cross-source linkage, provenance tracking, and iterative interpretation of results. Proponents emphasize that kohdedatan aims to preserve contextual information from each source while enabling new insights through synthesis.

Origin and usage: The term does not appear in major dictionaries or standards and it emerged in informal online discourse and project reports in the 2010s. Because there is no formal standard, definitions vary among researchers and practitioners; some use kohdedatan to refer specifically to the orchestration of a data integration workflow, while others apply it more broadly to any effort that combines data across domains.

Applications: In digital archives, kohdedatan is used to create integrated datasets from library catalogs, archival finding aids, and digitized texts; in social science research, it supports combining census, administrative, and survey data. The approach stresses provenance and reproducibility, and it often involves multidisciplinary collaboration to interpret synthesized results.

Limitations and critiques: Critics note that the lack of standardization can hinder interoperability, and that the process can be resource-intensive and error-prone if not carefully managed. Advocates argue that when well designed, kohdedatan can reveal patterns not visible in isolated sources and support richer interpretation.

Relation to related concepts: Kohdedatan shares goals with data integration, data fusion, and linked data, but places a stronger emphasis on contextual preservation, domain-specific semantics, and provenance.