What is data curation?
In simple terms, data curation is the art of maintaining the value of data (source: TechRebuplic). Curation at CanWIN consists of several steps which take a dataset from its raw state to a form that is understandable, retains value long term, and is FAIR - Findable, Accessible, Interoperable and Reusable.
These steps include:
- Collecting data
- Organizing data
- Cleaning data
- Enhancing/enriching data
- Standardizing data
- Storing/preserving data for future use.
Data curation takes place at all stages of the data life cycle.
Below are some pages that can assist you in the data curation stage:
- On our CanWIN Public Guides site, we have outlined some key concepts and best practices that can help considerably when curating data. Visit our data and metadata best practices pages for some great tips!
- The CanWIN Curated Terms page focuses on an important step in curation - data standardization. This practice involves using standardized names for variables, as well as other metadata fields that you may add to your dataset. This allows for your data to be unambiguous, interoperable, and facilitates reusability.