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      A data citation roadmap for scientific publishers


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          This article presents a practical roadmap for scholarly publishers to implement data citation in accordance with the Joint Declaration of Data Citation Principles (JDDCP), 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. Authors reading this roadmap will also better know 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.

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          Sharing Detailed Research Data Is Associated with Increased Citation Rate

          Background Sharing research data provides benefit to the general scientific community, but the benefit is less obvious for the investigator who makes his or her data available. Principal Findings We examined the citation history of 85 cancer microarray clinical trial publications with respect to the availability of their data. The 48% of trials with publicly available microarray data received 85% of the aggregate citations. Publicly available data was significantly (p = 0.006) associated with a 69% increase in citations, independently of journal impact factor, date of publication, and author country of origin using linear regression. Significance This correlation between publicly available data and increased literature impact may further motivate investigators to share their detailed research data.
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            How open science helps researchers succeed

            Open access, open data, open source and other open scholarship practices are growing in popularity and necessity. However, widespread adoption of these practices has not yet been achieved. One reason is that researchers are uncertain about how sharing their work will affect their careers. We review literature demonstrating that open research is associated with increases in citations, media attention, potential collaborators, job opportunities and funding opportunities. These findings are evidence that open research practices bring significant benefits to researchers relative to more traditional closed practices. DOI: http://dx.doi.org/10.7554/eLife.16800.001
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              Identifiers.org and MIRIAM Registry: community resources to provide persistent identification

              The Minimum Information Required in the Annotation of Models Registry (http://www.ebi.ac.uk/miriam) provides unique, perennial and location-independent identifiers for data used in the biomedical domain. At its core is a shared catalogue of data collections, for each of which an individual namespace is created, and extensive metadata recorded. This namespace allows the generation of Uniform Resource Identifiers (URIs) to uniquely identify any record in a collection. Moreover, various services are provided to facilitate the creation and resolution of the identifiers. Since its launch in 2005, the system has evolved in terms of the structure of the identifiers provided, the software infrastructure, the number of data collections recorded, as well as the scope of the Registry itself. We describe here the new parallel identification scheme and the updated supporting software infrastructure. We also introduce the new Identifiers.org service (http://identifiers.org) that is built upon the information stored in the Registry and which provides directly resolvable identifiers, in the form of Uniform Resource Locators (URLs). The flexibility of the identification scheme and resolving system allows its use in many different fields, where unambiguous and perennial identification of data entities are necessary.

                Author and article information

                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group
                20 November 2018
                : 5
                [1 ]Elsevier , Amsterdam 1043 NX, Netherlands
                [2 ]Springer Nature , London N1 9XW, UK
                [3 ]Public Library of Science , San Francisco CA 94111, USA
                [4 ]eLife Sciences Publications, Ltd , Cambridge CB4 1YG, UK
                [5 ]JISC , Bristol BS2 0JA, UK
                [6 ]EMBO Press , 69117 Heidelberg, Germany
                [7 ]University of Reading , Reading RG6 6AH, UK
                [8 ]John Wiley & Sons, Inc. , Hoboken NJ 07030, USA
                [9 ]University of California San Diego , La Jolla CA 92093, USA
                [10 ]University of Virginia, School of Medicine , Charlottesville VA 22908, USA
                [11 ]University of Virginia, Data Science Institute , Charlottesville VA 22904, USA
                [12 ]Crossref , Lynnfield, MA 01940, USA
                Author notes

                These authors contributed equally to this work.


                Present address: DataCite, Hannover, Germany.


                H.C. and A.K. co-chaired the DCIP Publishers Expert Group which produced this article. They had primary responsibility for leading regular telecons as well as a face-to-face meeting of participants (see Acknowledgements) at the Springer Nature London campus in July of 2016. H.C. and A.K. provided the article structure; organized their Expert Group to collect and integrate information from the participating publishers, including their own organizations; and did the majority of writing for this article. They made equal contributions to the work. E.G., P.P., M.H., D.K., T.L., S.T. and F.M. participated in the work of the Publishers Expert Group and co-authored this article. They provided knowledgeable content and input to the work from the perspectives of their respective organizations. In addition, M.H. coordinated and informed this work with the perspective of the JATS4R group (Journal Article Tag Suite for Reuse), which she chairs. T.C. coordinated the work of the Publishers Expert Group with the other DCIP participants (Repositories, Identifiers, JATS, and Primer/FAQ), co-authored sections of this article and edited the whole. T.C. and M.M. co-led the Data Citation Implementation Pilot as a whole.

                Copyright © 2018, The Author(s)

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/


                research data,publishing,data publication and archiving


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