Archives des mots-clés : research data

The Research Data Alliance: globally co-ordinated action against barriers to data publishing and sharing

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“This article discusses the drivers behind the formation of the Research Data Alliance (RDA), its current state, the lessons learned from its first full year of operation, and its anticipated impact on data publishing and sharing. One of the pressing challenges in data infrastructure (taken here to include issues relating to hardware, software and content format, as well as human actors) is how best to enable data interoperability across boundaries. This is particularly critical as the world deals with bigger and more complex problems that require data and insights from a range of disciplines. The RDA has been set up to enable more data to be shared across barriers to address these challenges. It does this through focused Working Groups and Interest Groups, formed of experts from around the world, and drawing from the academic, industry, and government sectors.”

URL : http://dx.doi.org/10.1087/20140503

Data and scholarly publishing: the transforming landscape

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“This article sets the scene for the special issue on research data and publishing. Research data – that material commonly accepted by the scholarly community as required evidence for hypotheses and insights, for verification and/or reproducibility of experiments – has become an increasingly critical issue for publishers given recent developments in funders’ mandates, technological advances, policymakers’ interests, and so forth. I outline some of the recent initiatives that are responding to policy directives, particularly Project ODE, and consider how publishers are working with data and integrating their practices with other collaborative efforts. A summary of the new policies, products, and partnerships demonstrates that the onus is now with scholarly publishers to gain an understanding of these developments and how they are affecting fellow key stakeholders within the research communications ecosystem.”

URL : http://dx.doi.org/10.1087/20140502

Building a Bridge Between Journal Articles and Research Data: The PKP-Dataverse Integration Project

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“A growing number of funding agencies and international scholarly organizations are requesting that research data be made more openly available to help validate and advance scientific research. Thus, this is an opportune moment for research data repositories to partner with journal editors and publishers in order to simplify and improve data curation and publishing practices. One practical example of this type of cooperation is currently being facilitated by a two year (2012-2014) one million dollar Sloan Foundation grant, integrating two well-established open source systems: the Public Knowledge Project’s (PKP) Open Journal Systems (OJS), developed by Stanford University and Simon Fraser University; and Harvard University’s Dataverse Network web application, developed by the Institute for Quantitative Social Science (IQSS). To help make this interoperability possible, an OJS Dataverse plugin and Data Deposit API are being developed, which together will allow authors to submit their articles and datasets through an existing journal management interface, while the underlying data are seamlessly deposited into a research data repository, such as the Harvard Dataverse. This practice paper will provide an overview of the project, and a brief exploration of some of the specific challenges to and advantages of this integration.”

URL : Building a Bridge Between Journal Articles and Research Data

Alternative URL : http://www.ijdc.net/index.php/ijdc/article/view/9.1.176

Cross-Linking Between Journal Publications and Data Repositories: A Selection of Examples

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“This article provides a selection of examples of the many ways that a link can be made between a journal article (whether in a data journal or otherwise) and a dataset held in a data repository. In some cases the method of linking is well established, while in others, they have yet to be rolled out uniformly across the journal landscape. We explore ways in which these examples might be implemented in a data journal, such as Geoscience Data Journal, as explored by the PREPARDE project.”

URL :  Cross-Linking Between Journal Publications and Data Repositories

Alternative URL : http://www.ijdc.net/index.php/ijdc/article/view/9.1.164

Guidelines on Recommending Data Repositories as Partners in Publishing Research Data

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“This document summarises guidelines produced by the UK Jisc-funded PREPARDE data publication project on the key issues of repository accreditation. It aims to lay out the principles and the requirements for data repositories intent on providing a dataset as part of the research record and as part of a research publication. The data publication requirements that repository accreditation may support are rapidly changing, hence this paper is intended as a provocation for further discussion and development in the future.”

URL : Guidelines on Recommending Data Repositories as Partners in Publishing Research Data

Alternative URL : http://www.ijdc.net/index.php/ijdc/article/view/9.1.152

Publishing and Pushing: Mixing Models for Communicating Research Data in Archaeology

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“We present a case study of data integration and reuse involving 12 researchers who published datasets in Open Context, an online data publishing platform, as part of collaborative archaeological research on early domesticated animals in Anatolia. Our discussion reports on how different editorial and collaborative review processes improved data documentation and quality, and created ontology annotations needed for comparative analyses by domain specialists. To prepare data for shared analysis, this project adapted editor-supervised review and revision processes familiar to conventional publishing, as well as more novel models of revision adapted from open source software development of public version control. Preparing the datasets for publication and analysis required significant investment of effort and expertise, including archaeological domain knowledge and familiarity with key ontologies. To organize this work effectively, we emphasized these different models of collaboration at various stages of this data publication and analysis project. Collaboration first centered on data editors working with data contributors, then widened to include other researchers who provided additional peer-review feedback, and finally the widest research community, whose collaboration is facilitated by GitHub’s version control system. We demonstrate that the “publish” and “push” models of data dissemination need not be mutually exclusive; on the contrary, they can play complementary roles in sharing high quality data in support of research. This work highlights the value of combining multiple models in different stages of data dissemination.”

URL : Publishing and Pushing: Mixing Models for Communicating Research Data in Archaeology

Alternative URL : http://www.ijdc.net/index.php/ijdc/article/view/9.1.57

Data Producers Courting Data Reusers: Two Cases from Modeling Communities

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“Data sharing is a difficult process for both the data producer and the data reuser. Both parties are faced with more disincentives than incentives. Data producers need to sink time and resources into adding metadata for data to be findable and usable, and there is no promise of receiving credit for this effort. Making data available also leaves data producers vulnerable to being scooped or data misuse. Data reusers also need to sink time and resources into evaluating data and trying to understand them, making collecting their own data a more attractive option. In spite of these difficulties, some data producers are looking for new ways to make data sharing and reuse a more viable option. This paper presents two cases from the surface and climate modeling communities, where researchers who produce data are reaching out to other researchers who would be interested in reusing the data. These cases are evaluated as a strategy to identify ways to overcome the challenges typically experienced by both data producers and data reusers. By working together with reusers, data producers are able to mitigate the disincentives and create incentives for sharing data. By working with data producers, data reusers are able to circumvent the hurdles that make data reuse so challenging.”

URL : Data Producers Courting Data Reusers

Alternative URL : http://www.ijdc.net/index.php/ijdc/article/view/9.1.98