Contributor identification is a core challenge in data publication. As in scholarly communication more generally, non-unique person names and the current lack of a global identification infrastructure for producers of scholarly content makes it difficult to establish the identity of authors and other contributors. This in turn makes it difficult to accurately attribute datasets published via online digital repositories to their creators – one of several key requirements for including these important outputs in the scholarly record.
In the GEN2PHEN project (http://www.gen2phen.org) we are developing a series of novel web-based systems and processes for online dissemination of genetic variation and other research data. The core aim is that of ensuring that data creators are recognized and rewarded for publishing data. This work builds on and integrates with recently launched international initiatives to i) extend and adapt the existing DOI infrastructure for identifying, locating and citing online datasets (DataCite: http://www.datacite.org), and to ii) create a global registry of unique identifiers for authors and other contributors (ORCID: http://www.orcid.org).
The technical approach we are exploring in this pilot project utilizes this emerging global data citation and contributor identification framework, in order to allow published datasets to be discovered, cited in a scholarly context and unambiguously attributed. We argue that, along with other measures, such an incentive-based approach is key to motivating the sharing of data and other types of digital research outputs in the life sciences.
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