What Drives Academic Data Sharing?

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“Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher’s point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded as knowledge commons, but research policies that better incentivise data sharing are needed to improve the quality of research results and foster scientific progress.”

URL : What Drives Academic Data Sharing?

DOI :10.1371/journal.pone.0118053

Incentives and motivations for sharing research data: researcher’s perspectives

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“This study, commissioned by Knowledge Exchange, has gathered evidence, examples and opinions on current and future incentives for research data sharing from the researcher’s point of view, in order to provide recommendations for policy and practice development on how best to incentivise data access and reuse. Whilst most researchers appreciate the benefits of sharing research data, on an individual basis they may be reluctant to share their own data. This study is based on qualitative interviews with 22 selected researchers of five research teams that have established data sharing cultures, in the partner countries of Knowledge Exchange: Denmark, Finland, Germany, the Netherlands and the United Kingdom. The five case studies span various academic disciplines: arts and humanities, social sciences, biomedicine, chemistry and biology.”

URL : Incentives and motivations for sharing research data: researcher’s perspectives

Alternative URL : http://knowledge-exchange.info/Default.aspx?ID=733

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 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

Datasharing guía práctica para compartir datos de investigación…

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Datasharing: guía práctica para compartir datos de investigación :

“Asociar los datos de investigación a la publicación favorece que la comunidad científica los reutilice, pero no tiene suficientes garantías de preservación. Almacenarlos en bases de datos solventa esta contingencia y aporta visibilidad, pero en España no existen demasiados servicios de estas características. Por esta razón, se describen, evalúan y exponen los pros y contras de depósitos de datos multidisciplinares extranjeros que pueden ser de utilidad para investigadores y gestores de información: Dryad, Figshare, Zenodo y Dataverse. Todavía es pronto para escoger de forma óptima y definitiva entre una u otra aplicación, por lo que se concluye con unas recomendaciones que orienten a la comunidad de usuarios e intermediarios.”

“To associate research data to the published results favors their reuse by the scientific community, but this does not afford sufficient guarantees of preservation. To store them in databases solves this contingency and provides visibility, but in Spain there are not many services of this kind. For this reason, we describe, evaluate and discuss the pros and cons of foreign multidisciplinary data repositories that can be useful for researchers and information managers: Dryad, Figshare, Zenodo and Dataverse. It is still early to choose optimally and definitively one or the other application, so we conclude with recommendations to guide the user community and intermediaries.”

URL : http://eprints.rclis.org/20907/

The Open Access Divide This paper is…

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The Open Access Divide :

“This paper is an attempt to review various aspects of the open access divide regarding the difference between those academics who support free sharing of data and scholarly output and those academics who do not. It provides a structured description by adopting the Ws doctrines emphasizing such questions as who, what, when, where and why for information-gathering. Using measurable variables to define a common expression of the open access divide, this study collects aggregated data from existing open access as well as non-open access publications including journal articles and extensive reports. The definition of the open access divide is integrated into the discussion of scholarship on a larger scale.”

URL : http://www.mdpi.com/2304-6775/1/3/113

Data sharing and its implications for academic libraries…

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Data sharing and its implications for academic libraries :

Purpose : As an important aspect of the scientific process, research data sharing is the practice of making data used for scholarly research publicly available for use by other researchers. This paper seeks to provide a more comprehensive understanding of the data-sharing challenges and opportunities posed by the data deluge in academics. An attempt is made to discuss implications for the changing role and functioning of academic libraries.

Design/methodology/approach : An extensive review of literature on current trends and the impact of data sharing are performed.

Findings : The context in which the increasing demands for data sharing have arisen is presented. Some of the practices, trends, and issues central to data sharing among academics are presented. Emerging implications for academic libraries that are expected to provide a data service are discussed.

Originality/value : An insightful review and synthesis of context, issues, and trends in data sharing will help academic libraries to plan and develop programs and policies for their data services.”

URL : http://www.emeraldinsight.com/journals.htm?issn=0307-4803&volume=114&issue=11&articleid=17097171&show=abstract