Finding data in the long-tail

Biosystems Analytics

blog_1_fig_1Scientists are increasingly examining the most comprehensive catalogue of datasets for any particular question.  Making sure you can find as much of the data relevant to a particular problem thus begins to loom as a large issue.   Although institutional repositories (such as NCBI, Dryad, Figshare etc.) are great at storing the final published versions of the data sets, some early and smaller-scale research data can get lost in the “long-tail“.   Anne Thessen has a great post over on her blog on the Data Detektiv, on how to locate and keep track of such “dark data”:

Finding relevant data, especially if the needed data are dark, can be a difficult and lengthy task. … Was there a way to discover data based on events earlier in the research workflow? After some thought, I realized that databases and lists of awards made by funding agencies were an…

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