Data Citation Standards: Progress, But Slow Progress | The Scholarly Kitchen
" ... Recently Crossref and the Digital Curation Center (DCC) issued guidelines for best practices for data citation, namely that citations to datasets appear in the References section of any paper that uses them. This is in contrast to the ways that journals usually cite data, 'intratextually' (e.g. including a GenBank Accession Number in the text of an article) or in a separate dedicated 'data availability' section of the paper. Neither of these satisfies the new standards which are aimed at better fulfilling the Joint Declaration of Data Citation Principles (JDDCP), which states, 'data citation should be accorded the same importance in the scholarly record as citations of other research objects, such as publications.' The goal of the JDDCP is to help drive data availability by raising its importance and measurability as a means of understanding researcher productivity. If you create a dataset that drives significant research forward, then you should be acknowledged for that contribution. Proper citation is key toward the reward, not to mention the discoverability offered by data citation metrics such as Thomson Reuters’ Data Citation Index. The recent study, described here in a blog post by author Elizabeth Hull from Dryad, showed that we are far from the intended goal. Only 6% of total articles cited the data’s DOI in the articles’ reference list, 75% just listed the DOI somewhere in the body of the article, and 20% had no citation of the data DOI anywhere in the article. On a positive note, things are improving, with works cited properly in the references rising from 5% to 8% over the four years studied, and articles with no data citation at all declining from 31% to 15%. These findings indicate progress, albeit very slow progress. I suspect that as data availability becomes more common, things will improve ..."