Data Curation Fundamentals

Data curation is a key component of the data sharing and publication process, during which data professionals review a dataset, code, and related outputs to ensure that data are findable, accessible, interoperable, and reusable (FAIR) and incorporates ethical curation considerations. Data curation enables data discovery and access, maintains data quality and authenticity, adds value, and provides for re-use over time through activities including open and controlled access, archiving, metadata creation, digital preservation, and file format transformation. There are many additional activities encompassed by the term data curation– which can be daunting for a novice to understand and apply in a meaningful way.

The IASSIST & CARTO 2024 proposed Data Curation Network (DCN) and Digital Research Alliance of Canada co-hosted Data Curation Fundamentals training workshop will provide attendees with a framework for getting started with data curation, including hands-on practical curation training using various data formats . Using the DCN CURATE(D) workflow (z.umn.edu/curate) and the Canadian bilingual (English and French) CURATION framework, attendees will learn practical curation techniques that can be applied across research disciplines. Provided by members of the DCN Education Committee, and the Alliance’s Curation Expert Group (CEG) and invited speakers, this workshop will leverage both active learning opportunities, using example datasets, as well as discussions in an inclusive peer-to-peer learning environment. This established curriculum has been used for both in-person and virtual learning opportunities, with overwhelming success. This workshop has been taught in the United States, adapted and extended for use in Canada, and we are eager to bring our curriculum to the international community.