The Curation Process Adds Value to Primary Research Data and is Key to its Usability - Charleston Hub

"As more data is made openly accessible as a part of journal articles or federal funder requirements, the importance of data curation can not be over-emphasized.  Data is not intrinsically useful.  Furthermore, datasets do not simply become useful because they are publicly available.  Data is useful only insofar as it meets the needs of the user.  Likewise, more data does not mean more value (Binggeser, 2017).  Data is of the highest value for those who collected it.  Others who were not involved in the data collection and analysis efforts can find data less useful for their needs, especially if the data is not properly curated.  Including as supplemental information a dataset that has not been properly prepared for public use reduces the usefulness of the data.  Data must be cleaned and prepared properly for it to be useful.  And this process does not happen by accident; it must be purposely conducted by someone trained in properly curating a dataset for public use (Johnston et al, 2018)....

What value does the curation process provide for data?  The data curation steps formalized by the DCN in the C.U.R.A.T.E.D. acronym include the following:  Check (the files for completeness and viability), Understand (the contents), Request (additional information), Augment (metadata), Transform (to open formats), Evaluate (for FAIRness), and Document (the curation process) (Johnston et al, 2018). ..."