If the idea of sharing your finished dataset seems a little uncomfortable, perhaps it would be useful to consider an alternative perspective: gathering credit for your data. After all, as a 2013 report on data citation affirms, “Data citations should be accorded the same importance in the scholarly record as the citation of other objects.”1 In some cases, your dataset may provide a greater contribution to answering scholarly questions than any published results because your work will be reusable by you and by other researchers down the road as they ask new and more pointed questions of a difficult subject.
Being able to cite data, and to track how and where that data is getting cited, is also becoming a visible aspect of publishing. When seeking a permanent home for your dataset in conjunction with results publication, take great care to seek a repository that will make your data available in a way that is advantageous to citation and discovery.
Make sure you understand how your data will be licensed for use, and verify that the repository has all of the proper elements such as DOI provisions, download and even citation tracking, and a good balance between visibility within your discipline and discoverability outside of your scholarly circle. In other words, all of the issues a researcher would consider when seeking a place to publish their written reports, articles, and analyses!
1 Yvonne M. Sorcha, ed., “Out of Cite, Out of Mind: The Current State of Practice, Policy, and Technology for the Citation of Data,” Data Science Journal 12 (13 Sept. 2013): 3.2.1 <http://dx.doi.org/10.2481/dsj.OSOM13-043>, and M. Martone, ed., Data Citation Synthesis Group: Joint Declaration of Data Citation Principles (San Diego, CA: FORCE11, 2014) <https://www.force11.org/group/joint-declaration-data-citation-principles-final>.