This article describes the novel open source tools for open data publication in open access journal workflows. This comprises a plugin for Open Journal Systems that supports a data submission, citation, review, and publication workflow; and an extension to the Dataverse system that provides a standard deposit API.
We describe the function and design of these tools, provide examples of their use, and summarize their initial reception. We conclude by discussing future plans and potential impact.
The increase of digital content in the broad areas of Institutional and domain specific Repositories, Libraries, Archives and Museums and the increased interest in the sharing and preservation of « research data » have triggered the emergence of new roles such as Data Curator. The paper refers about the on-going investigation of current data curator education and training programs with regard to the role of information professionals and/or data scientists in the research lifecycle.
The investigation has been based on a series of workshops and events discussing the concerns of researchers and teachers about digital library and digital curation. A first list of competencies and skills at technical and operational level that professionals should have, has been evidenced. The theoretical framework and structure of educational programmes should have sufficient flexibility to accommodate the needs of various groups of specialists.
The purpose of this paper is to examine funding models for Open Access (OA) digital data repositories whose costs are not wholly core funded. Whilst such repositories are free to access, they are not without significant cost to build and maintain and the lack of both full core costs and a direct funding stream through payment-for-use poses a considerable financial challenge, placing their future and the digital collections they hold at risk.
The authors document 14 different potential funding streams for OA digital data repositories, grouped into six classes (institutional, philanthropy, research, audience, service, volunteer), drawing on the ongoing experiences of seeking a sustainable funding for the Digital Repository of Ireland (DRI).
There is no straight forward solution to funding OA digital data repositories that are not wholly core funded, with a number of general and specific challenges facing each repository, and each funding model having strengths and weaknesses. The proposed DRI solution is the adoption of a blended approach that seeks to ameliorate cyclical effects across funding streams by generating income from a number of sources rather than overly relying on a single one, though it is still reliant on significant state core funding to be viable.
The detailing of potential funding streams offers practical financial solutions to other OA digital data repositories which are seeking a means to become financially sustainable in the absence of full core funding.
The review assesses and provides concrete advice with respect to potential funding streams in order to help repository owners address the financing conundrum they face.
URL : http://dx.doi.org/10.1108/OIR-01-2015-0031
PURPOSE
The paper provides empirical evidence on research data submitted together with PhD dissertations in social sciences and humanities.
APPROACH
We conducted a survey on nearly 300 print and electronic dissertations in social sciences and humanities from the University of Lille 3 (France), submitted between 1987 and 2013.
FINDINGS
After a short overview on open access to electronic dissertations, on small data in dissertations, on data management and curation, and on the challenge for academic libraries, the paper presents the results of the survey. Special attention is paid to the size of the research data in appendices, to their presentation and link to the text, to their sources and typology, and to their potential for further research. Methodological shortfalls of the study are discussed, and barriers to open data (metadata, structure, format) and legal questions (privacy, third-party rights) are addressed. The conclusion provides some recommendations for the assistance and advice to PhD students in managing and depositing their research data.
PRACTICAL IMPLICATIONS
Our survey can be helpful for academic libraries to develop assistance and advice for PhD students in managing their research data in collaboration with the research structures and the graduate schools.
ORIGINALITY
There is a growing body of research papers on data management and curation. Produced along with PhD dissertations, little is known about the characteristics of this material, in particular in social sciences and humanities and the impact on the role of academic libraries.
URL : Hidden Treasures: Opening Data in PhD Dissertations in Social Sciences and Humanities
Understanding the differing data management practices among academic disciplines is an important way to inform existing and emerging library research support and services. This paper reports findings from a study of data sharing practices among ecology, evolution, and natural resources scientists at the University of Minnesota. It examines data sharing rates, methods, and disciplinary differences and discusses the characteristics of researchers, data, methods, and aspects of data sharing across this group of disciplines.
Data sharing practices are investigated by reviewing the two most recently published research articles (n=155) for each faculty member (n=78) in three departments at a single large research university. All mentions of data sharing in each publication were pursued in order to locate, analyze, and characterize shared data.
Seventy-two of 155 (46%) articles indicated that related research data was publicly shared by some method. The most prevalent method for data sharing was via journal websites, with 91% of data sharing articles using this method. Ecology, evolution, and behavior scientists shared data at the highest rate (70% of their articles), contrasting with fisheries, wildlife, and conservation biologists (18%), and forest resources (16%).
Differences between data sharing practices may be attributable to a range of influences: funder, journal, and institutional policies; disciplinary norms; and perceived or real rewards or incentives, as well as contrasting concerns, cost, or other barriers to sharing data.
Study results suggest differential approaches to data services outreach based on discipline and research type and support the need for education and influence on both scientist and journal practices.
Many research institutions have developed research data services in their libraries, often in anticipation of or in response to funder policy. However, policies at the institution level are either not well known or nonexistent.
This study reviewed library data services efforts and institutional data policies of 206 American universities, drawn from the July 2014 Carnegie list of universities with “Very High” or “High” research activity designation. Twenty-four different characteristics relating to university type, library data services, policy type, and policy contents were examined.
The study has uncovered findings surrounding library data services, institutional data policies, and content within the policies.
Overall, there is a general trend toward the development and implementation of data services within the university libraries. Interestingly, just under half of the universities examined had a policy of some sort that either specified or mentioned research data.
Many of these were standalone data policies, while others were intellectual property policies that included research data. When data policies were discoverable, not behind a log in, they focused on the definition of research data, data ownership, data retention, and terms surrounding the separation of a researcher from the institution.
By becoming well versed on research data policies, librarians can provide support for researchers by navigating the policies at their institutions, facilitating the activities needed to comply with the requirements of research funders and publishers. This puts academic libraries in a unique position to provide insight and guidance in the development and revisions of institutional data policies.
Sharing digital research data is increasingly common, propelled by funding requirements, journal publishers, local campus policies, or community-driven expectations of more collaborative and interdisciplinary research environments. However, it is not well understood how researchers are addressing these expectations and whether they are transitioning from individualized practices to more thoughtful and potentially public approaches to data sharing that will enable reuse of their data.
The University of Minnesota Libraries conducted a local opt-in study of data management plans (DMPs) included in funded National Science Foundation (NSF) grant proposals from January 2011 through June 2014. In order to understand the current data management and sharing practices of campus researchers, we solicited, coded, and analyzed 182 DMPs, accounting for 41% of the total number of plans available.
DMPs from seven colleges and academic units were included. The College of Science of Engineering accounted for 70% of the plans in our review. While 96% of DMPs mentioned data sharing, we found a variety of approaches for how PIs shared their data, where data was shared, the intended audiences for sharing, and practices for ensuring long-term reuse.
DMPs are useful tools to investigate researchers’ current plans and philosophies for how research outputs might be shared. Plans and strategies for data sharing are inconsistent across this sample, and researchers need to better understand what kind of sharing constitutes public access. More intervention is needed to ensure that researchers implement the sharing provisions in their plans to the fullest extent possible. These findings will help academic libraries develop practical, targeted data services for researchers that aim to increase the impact of institutional research.