“Data curation is the active and ongoing management of data through its lifecycle of interest and usefulness to scholarship, science, and education. Data curation enables data discovery and retrieval, maintains data quality, adds value, and provides for re-use over time through activities including authentication, archiving, management, preservation, and representation.”
Data curation intersects with a few specific actions and processes in the practical context, including: description, annotation, collection/aggregation, storage and migration.
Several major types of research objects and collections that present distinctive forms of data and distinctive curation challenges have been identified:
Some strategic points concerning the treatment of this data need to be stressed:
This information is from:
“An Introduction to Humanities Data Curation” (Julia Flanders & Trevor Muñoz)
The digital curation lifecycle model developed by is one of the most widely used models and it covers the following curation actions:
A Data Curation Profile is a document about the origin of a dataset or a collection and its lifecycle within a research project. It describes the data generated and used in research that may be published, shared and preserved for future reuse and repurposing. The Data Curation Profile records requirements for specific data generated by a single scientist, scholar or research group based on their needs and requirements. It can be created by librarians, archivists, IT professionals and/or data managers through interviewing the researcher(s) and documenting the results.
The sponsored by Institute of Museum and Library Services (IMLS) can be used as a tool to conduct data curation interview. It can be downloaded at: http://docs.lib.purdue.edu/dcptoolkit/
Some completed Data Curation Profiles can be found at the Data Curation Profile Directory.