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An Introduction to the Joint Principles for Data Citation

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An Introduction to the Joint Principles for Data Citation RDAP Review EDITOR’S SUMMARY While the conventions of An Introduction to the Joint Principles for Data Citation bibliographic citation have been by Micah Altman, Christine Borgman, Mercè Crosas and Maryann Martone long established, the sole focus is on reference to other scholarly 3 works. Access to the data serving NOTE: This article summarizes and extends a longer report r of the manuscript must be available to any reader of Science ” e b as the basis for scholarly work has published as [ 1]. Contributors are listed in alphabetical order. We and that “ citations to unpublished data [emphasis added] m u been limited. Data citation extends describe contributions to the paper using a standard taxonomy N and personal communications cannot be used to support , described in [ 2]. Micah Altman and Mercè Crosas were the lead 1 important access to material that 4 authors, taking equal responsibility for revisions and authoring claims in a published paper” [ 4]. Too often, however, this e has been largely unavailable for m the first draft of the manuscript from which this is derived. All u proscription and others like it have been honored only in the l o sharing, verification and reuse. The authors contributed to the conception of the Force 11 principles V breach. Few research articles provide access to the data on – Joint Declaration of Data Citation discussed, to the methodology, to the project administration 5 1 and to the writing through critical review and commentary. which they are based, nor specific citations to data on which 0 Principles, finalized in February 2 the findings rely, nor protocols, algorithms, code or other h 2014, is a formal statement pulling c r a together practices used in the ata citation is rapidly emerging as a key practice technology necessary to reproduce, reuse or extend results. M / y r research and publishing arenas and supporting data access, sharing and reuse, as well as The practice of bibliographic citation to supporting a u r in common use. The declaration sound and reproducible scholarship. Consensus data materials was formalized in scholarly publishing more than b e D F encompasses eight principles that citation principles, articulated through the Joint Declaration a century ago. In this tradition, a “bibliographic citation” – y g stress the importance and of Data Citation Principles refers to a formal, structured reference to another scholarly o [3], represent an advance in the l o n legitimacy of data, the need to give state of the practice and a new consensus on citation. work. In most fields, citations are made in the body of the h c e scholarly credit to contributors and T Lowering the barrier to research data discovery and use, work. Full references typically appear at the end of the main d the importance of data as evidence. n coupled with an increased ability to link data with publications, text, providing more detailed bibliographic information for a e Cited data should have unique and c could enable new forms of scholarly publishing, promote each work referenced. Following the establishment of the n e persistent identifiers, and the i c interdisciplinary research, strengthen the linkage between first scientific digital data archives in the late 1960s, S citation should facilitate human n bibliographic standards for data were developed and refined o policy and science and lower the costs of replicating and i t and machine access and support a extending previous research. For this reason, the submission over the next decades but never widely used in practice. m r verification and interoperability. The o f The theory and practice of data citation have advanced n requirements for Science – one of the most cited, read and I principles are expected to have r o f broad impact on research, respected journals in the sciences – stipulate that “all data considerably over the last five years, and these parallel n o i recognition and scholarly publishing. necessary to understand, assess and extend the conclusions efforts led to concern for a unified approach. t a i c o s KEYWORDS s A data sets Micah Altman is director of research and head/scientist, program on information science for the MIT Libraries. He can be reached at e h t escience<at>mit.edu . | Christine Borgman is professor and Presidential Chair in information studies at UCLA. She can be reached at f data curation o borgman<at>gseis.ucla.edu . |Mercè Crosas is director of data science at the Institute for Quantitative Social Science at Harvard University. She can n i access to resources t be reached at mcrosas<at>iq.harvard.edu . | Maryann Martone is co-director of the National Center for Microscopy and Imaging Research at the e l l source materials UCSD. She can be reached at maryann<at>ncmir.ucsd.edu . u B citation analysis 43 CONTENTS < PREVIOUS PAGE NEXT PAGE > RDAP Review ALTMAN, BORGMAN, CROSAS and MARTONE, continued The joint principles on data citation represent a new Citation Principles reflects various efforts and presents a phase of activity that focuses on principled integration with broad convergence on eight core principles: the scholarly research and publishing ecosystem and a 1. Importance. Data should be considered legitimate, broad consensus on data citation practices. What has citable products of research. Data citations should be emerged in the publishing and research communities is accorded the same importance in the scholarly record as 3 r e agreement that citation is needed to support attribution and citations of other research objects, such as publications. b m 2. Credit and Attribution. u verification, recognition that citations must support both Data citations should facilitate N , human and machine clients, maturity of robust persistent giving scholarly credit and normative and legal 1 4 e identifiers, and the desire to integrate data citation in attribution to all contributors to the data, recognizing m u l standardized ways within publications, catalogs, tool chains that a single style or mechanism of attribution may not o V – and larger systems of attribution. be applicable to all data. 5 1 0 In the summer of 2013, the Data Citation Synthesis Group 3. Evidence. In scholarly literature, whenever and 2 h c was formed to unify various parallel recommendations. wherever a claim relies upon data, the corresponding r a M Meeting weekly from July to November of 2013, the group data should be cited. / y r a thoroughly deconstructed previous data citation principles 4. Unique Identification. A data citation should include a u r b e and produced a synthesis set that included the input of more persistent method for identification that is machine F – than 25 organizations. The group also met in September actionable, globally unique and widely used by a y g o l 2013 as part of the Research Data Alliance conference, in community. o n h two half days of public workshop. As a result, in November 5. Access. Data citations should facilitate access to the c e T 2013, the proposed Joint Declaration of Data Citation data themselves and to such associated metadata, d n a Principles [3] was released to the public for open comment documentation, code and other materials as are e c n and then finalized at the end of February 2014. The joint necessary for both humans and machines to make e i c S principles reference and synthesize principles and informed use of the referenced data. n o i t recommendations from earlier work: a report by the 6. Persistence. Unique identifiers, and metadata a m r CODATA/ICTSI Task Force on Data Citation [ 5] and a describing the data and its disposition, should persist – o f n I workshop held by the National Research Council [ 6] as even beyond the lifespan of the data they describe. r o f well as standards previously proposed by Altman & King 7. Specificity and Verifiability. Data citations should n o i t a [7] and Ball & Duke [ 8]. facilitate identification of, access to and verification of i c o s The scope of the principles is solely to provide data the specific data that support a claim. Citations or s A citation recommendations, not to include detailed citation metadata should include information about e h t f specifications for implementation or to focus on provenance and fixity sufficient to facilitate verifying o n i technologies or tools or research data repositories. The that the specific time slice, version and/or granular t e l l principles should extend to all disciplines and all types of portion of data retrieved subsequently is the same as u B data. As will be seen below, the Joint Declaration of Data was originally cited. 44 CONTENTS TOP OF ARTICLE < PREVIOUS PAGE NEXT PAGE > RDAP Review ALTMAN, BORGMAN, CROSAS and MARTONE, continued 8. Interoperability and flexibility. Data citation methods compliant, or close to being compliant, with these should be sufficiently flexible to accommodate the principles (for example, Dataverse, DataDryad, DataCite). variant practices among communities but should not We anticipate that the impact of the unified, widely differ so much that they compromise interoperability of disseminated Joint Declaration of Data Citation Principles data citation practices across communities. will be substantial and will change current publication 3 r e The Force 11 website [ 9] currently hosts the data citation workflows, create new data citation technologies, define b m u principles and includes examples, detailed documentation new metrics for scholarly impact and recognition and, N , and references to the standards and reports they incorporate. more importantly, provide persistent access to the data 1 4 e Less than a month after the principles were finalized, supporting scientific results to validate and extend previous m u l they were endorsed officially by 30 organizations (now 85, scientific work.
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