Carrying out digital research (almost all research is now at least semi-digital) requires that both scholars and information professionals understand how to manage and curate data over its entire lifetime of interest. At the least, individual scholars must be able to document their data curation strategies and evaluate those of collaborators and other purveyors of data.

In important ways, data curation is not new. Drawing on increasingly precise conceptual definitions of “data”—information systematically asserted as evidence ((For extended discussion see Allen H. Renear, Simone Sacchi, and Karen M. Wickett, “Definitions of Dataset in the Scientific and Technical Literature,” <i>Proceedings of the American Society for Information Science and Technology</i> 47, no. 1 (2010): 1-4, doi:10.1002/meet.14504701240; and Dubin, et al., “Content, Format, and Interpretation.”)). I would hope to convince those who are not primarily data curators that data curation is important to them because the theories and practices of data curation are crucial to communicating the enduring meaning and intent of any scholarship or research in ways that are authentic, contextualized, and complete. The first beneficiaries of data curation work are researchers themselves. Jason Scott from the Internet Archive has said that metadata is a “love note” to the future ((Jason Scott, “The Metadata Mania,” <i>ASCII</i>, June 26, 2011, <a href="http://ascii.textfiles.com/archives/3181">http://ascii.textfiles.com/archives/3181</a>.)). In terms of keeping research information comprehensible and usable, even to the person who created it, the future doesn’t need to be far distant, as anyone who has tried to decipher, some months later, a partial reference citation in his notes or tried to remember all the variables of her topic modeling experiment can attest. The strategies for data curation may be as simple as file-naming conventions, data replication, and very basic description. Or, the strategies may be as complicated as managing the integrity and renderability of large, complex 3D representations of information that cannot be recovered after its moment of collection, during the stages of an archaeological excavation, for example.

Mark Sample defines scholarship as “a creative or intellectual act [that is] public and circulates in a community of peers that evaluates and builds upon it.” ((Sample, “When Does Service Become Scholarship?”)) From this definition, it follows that scholarship depends on good data curation practice, which enables the dissemination and circulation of research products in ways that other scholars can build upon.

I also hope to convince those who are not primarily data curators of the importance of data curation by appealing to the public trust. Much of the research happening in the United States is funded by the public. The resulting data does not belong only to the researcher who creates it, but is held by that person as a public trust. Data curation is part of the ethical responsibility of good research, and that should concern everyone.