Citing and valueing Open Data
The academic world has. perhaps unsurprisingly, been somewhat slow to respond to the challenge of recognising different sources of knowledge. A little strangely, one important step in developing recognition of different forms of scholarly research and knowledge is the development and use of forms of citation.
Si in that regard it is encouraging to see the publication of “The Amsterdam Manifesto on Data Citation Principles.”
In the preface they state:
We wish to promote best practices in data citation to facilitate access to data sets and to enable attribution and reward for those who publish data. Through formal data citation, the contributions to science by those that share their data will be recognized and potentially rewarded. To that end, we propose that:
1. Data should be considered citable products of research.
2. Such data should be held in persistent public repositories.
3. If a publication is based on data not included with the article, those data should be cited in the publication.
4. A data citation in a publication should resemble a bibliographic citation and be located in the publication’s reference list.
5. Such a data citation should include a unique persistent identifier (a DataCite DOI recommended, or other persistent identifiers already in use within the community).
6. The identifier should resolve to a page that either provides direct access to the data or information concerning its accessibility. Ideally, that landing page should be machine-actionable to promote interoperability of the data.
7. If the data are available in different versions, the identifier should provide a method to access the previous or related versions.
8. Data citation should facilitate attribution of credit to all contributors
The Manifesto was created during the Beyond the PDF 2 Conference in Amsterdam in March 2013.
The original authors were Mercè Crosas, Todd Carpenter, David Shotton and Christine Borgman.
