Scientific Data – a way of getting credit for data
In an interesting development, Nature Publishing Group has launched a new initiative: Scientific Data – a online-only open access journal that publishes data sets without the demand of testing scientific hypotheses in connection to the data. That is, the data itself is seen as the valuable product, not any findings that might result from it. There is an immediate upside of this; large scientific data sets might be accessible to the research community in a way that enables proper credit for the sample collection effort. Since there is no demand for a full analysis of the data, the data itself might quicker be of use to others, without worrying that someone else might steal the bang of the data per se. I also see a possible downside, though. It would be easy to hold on to the data until you have analyzed it yourself, and then release it separately just about when you submit the paper on the analysis, generating extra papers and citation counts. I don’t know if this is necessarily bad, but it seems it could contribute to “publishing unit dilution”. Nevertheless, I believe that this is overall a good initiative, although how well it actually works will be up to us – the scientific community. Some info copied from the journal website:
Scientific Data’s main article-type is the Data Descriptor: peer-reviewed, scientific publications that provide an in-depth look at research datasets. Data Descriptors are a combination of traditional scientific publication content and structured information curated in-house, and are designed to maximize reuse and enable searching, linking and data mining. (…) Scientific Data aims to address the increasing need to make research data more available, citable, discoverable, interpretable, reusable and reproducible. We understand that wider data-sharing requires credit mechanisms that reward scientists for releasing their data, and peer evaluation mechanisms that account for data quality and ensure alignment with community standards.