A data citation roadmap for scientific publishers

Abstract

This article presents a practical roadmap for scholarly publishers to implement data citation in accordance with the Joint Declaration of Data Citation Principles (JDDCP) [1], a synopsis and harmonization of the recommendations of major science policy bodies. It was developed by the Publishers Early Adopters Expert Group as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH BioCADDIE program. The structure of the roadmap presented here follows the "life of a paper" workflow and includes the categories Pre-submission, Submission, Production, and Publication. The roadmap is intended to be publisher-agnostic so that all publishers can use this as a starting point when implementing JDDCP-compliant data citation. It can also act as a guide to authors -what to expect from publishers and how to enable their own data citations to gain maximum impact, as well as complying with what will become increasingly common funder mandates on data transparency.

Technical note: Open-paleo-data implementation pilot – the PAGES 2k special issue

“…This structured format enables future users to conveniently access datasets directly from a list rather than having to locate the DOI (or URL) identifier within the references-cited section. On the other hand, including the data citations in the reference list makes it easier for publishers to capture and process the citations in the same way as other references (Cousijin et al, 2017). In the future, it may be possible for automated data harvesters to recognize and resolve DOI (or URL) identifiers from within the text outside of the reference list.…”

Theory and practice of data citation

“…Moreover, the scientific community is taking action to promote an open research culture (Nosek et al, 2015) and effective means to share, discover, and access scientific data that too often still remain "hidden" at their origin or are shared in suboptimal ways (Ohno-machado et al, 2015). Indeed, as a matter of good scientific practice, scientific databases are recommended to be FAIR (Findable, Accessible, Interoperable, and Reusable) (Wilkinson et al, 2016) and accessible from the articles referring to or using them (Cousijn et al, 2017).…”

“…Since scientific works and publications increasingly rely on curated databases, traditional references are starting to be placed alongside references to data; hence, scientific publishers (e.g., Elsevier, PLoS, Springer, Nature) have been defining data policies and author guidelines to include data citations in the reference lists (Cousijn et al, 2017;Walton, 2010). At the institutional level, within the Horizon 2020 program, the European Commission has introduced the Open Research Data Pilot (ODP), which aims to improve and maximize the access to and reuse of research data and to increase the credit given to data creators; in the same vein, also the National Science Foundation (NSF) and the National Institutes of Health (NIH) in the United States and the Economic and Social Research Council in the United Kingdom ask researchers applying for grants to provide data management plans describing how the data they use and produce will be shared and referenced (MacKenzie, 2012;Spengler, 2012).…”

“…Nevertheless, data citations are often referred to as "formal ways to ground the research findings in a manuscript, upon their supporting evidence, when that evidence consists of externally archived datasets" (Cousijn et al, 2017) and it is argued that citations to data should be placed in the reference list section, as published works are (Altman, 2012;Corti, Van den Eynden, Bishop, & Woollard, 2014;Park & Wolfram, 2017). Hence, a data citation could be indicated with the triple {R, C, D}, where R is the reference paper, C is the citation, and D is the data set-that is, the object of the citation.…”

Strategies and guidelines for scholarly publishing of biodiversity data

“…It is expected that a new working group will take these software citation principles forward by supporting potential implementers and developing metadata standards, following the example of the FORCE11 Data Citation Working Group (Cousijn et al 2017). …”