The Importance of Data Citation

Abstract

Over the past decade, a growing movement toward greater accessibility, transparency, and reproducibility has taken hold in the scientific community. One area of open science that has gained significant traction is the concept of FAIR data principles—that is, guidelines ensuring data are findable, accessible, interoperable, and reusable. Indeed, many scientific journals now require data be made available in FAIR-aligned repositories prior to publication—and, in some cases, even prior to acceptance. These issues are important to me as an information manager in the US Long Term Ecological Research (LTER) Network, which has long been a pioneer in scientific data management. FAIR data are accompanied by high-quality metadata, and when archived in FAIR-aligned repositories, they receive persistent, unique identifiers (e.g., a digital object identifier, or DOI) to track provenance and enable data citation. While great strides have been made to establish data management best practices, scientists are lagging behind with respect to proper data citation. Data are a valuable research output, and providers should be credited accordingly. Moreover, scientists have a professional responsibility to ensure that data are properly cited. Citing data is as easy as citing a publication; thus, the format and placement of data citations should be quite familiar. Data citations should include, at minimum, the author, year of publication, title, publisher (the data repository), DOI, and, where appro…