Exploring the opportunities and challenges of implementing open research strategies within development institutions

This research proposal calls for support for a pilot project to conduct open data pilot case studies with eight (8) IDRC grantees to develop and implement open data management and sharing plans.

The results of the case studies will serve to refine guidelines for the implementation of development research funders’ open research data policies. The case studies will examine the scale of legal, ethical and technical challenges that might limit the sharing of data from IDRC projects including issues of:

  • Privacy, personally identifiable information and protection of human subject
  • Protection of intellectual property generated from projects or potential for financial risks for projects or institutions
  • Challenges in the local legal environment, including ownership of data
  • Ethical issues in releasing or sharing of indigenous and community knowledge, and the relationship between project participants and investigators particularly in the context of historical expropriation of resources
  • Local and global issues of capacity and expertise in the management and sharing of data

The duration of the current project will be fifteen (16) months, commencing September 2015 and ending in December 2016. The project will focus on auditing the data being produced by the participating projects, supporting the development of data management and sharing plans, and surfacing and cataloguing issues that arise.

URL : Exploring the opportunities and challenges of implementing open research strategies within development institutions

Alternative location : http://rio.pensoft.net/articles.php?id=8880

 

Open Data in Global Environmental Research: The Belmont Forum’s Open Data Survey

This paper presents the findings of the Belmont Forum’s survey on Open Data which targeted the global environmental research and data infrastructure community. It highlights users’ perceptions of the term “open data”, expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing.

URL : Open Data in Global Environmental Research: The Belmont Forum’s Open Data Survey

DOI :10.1371/journal.pone.0146695

The data sharing advantage in astrophysics

We present here evidence for the existence of a citation advantage within astrophysics for papers that link to data. Using simple measures based on publication data from NASA Astrophysics Data System we find a citation advantage for papers with links to data receiving on the average significantly more citations per paper than papers without links to data. Furthermore, using INSPEC and Web of Science databases we investigate whether either papers of an experimental or theoretical nature display different citation behavior.

URL : http://arxiv.org/abs/1511.02512

Data Sharing Among Ecology, Evolution, and Natural Resources Scientists: An Analysis of Selected Publications

INTRODUCTION

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.

METHODS

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.

RESULTS

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%).

DISCUSSION

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.

CONCLUSION

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.

URL : Data Sharing Among Ecology, Evolution, and Natural Resources Scientists: An Analysis of Selected Publications

DOI : http://doi.org/10.7710/2162-3309.1244

Approaches to Data Sharing: An Analysis of NSF Data Management Plans from a Large Research University

INTRODUCTION

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

URL : Approaches to Data Sharing: An Analysis of NSF Data Management Plans from a Large Research University

DOI : http://doi.org/10.7710/2162-3309.1231

Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide

The incorporation of data sharing into the research lifecycle is an important part of modern scholarly debate. In this study, the DataONE Usability and Assessment working group addresses two primary goals: To examine the current state of data sharing and reuse perceptions and practices among research scientists as they compare to the 2009/2010 baseline study, and to examine differences in practices and perceptions across age groups, geographic regions, and subject disciplines.

We distributed surveys to a multinational sample of scientific researchers at two different time periods (October 2009 to July 2010 and October 2013 to March 2014) to observe current states of data sharing and to see what, if any, changes have occurred in the past 3–4 years. We also looked at differences across age, geographic, and discipline-based groups as they currently exist in the 2013/2014 survey.

Results point to increased acceptance of and willingness to engage in data sharing, as well as an increase in actual data sharing behaviors. However, there is also increased perceived risk associated with data sharing, and specific barriers to data sharing persist. There are also differences across age groups, with younger respondents feeling more favorably toward data sharing and reuse, yet making less of their data available than older respondents. Geographic differences exist as well, which can in part be understood in terms of collectivist and individualist cultural differences.

An examination of subject disciplines shows that the constraints and enablers of data sharing and reuse manifest differently across disciplines. Implications of these findings include the continued need to build infrastructure that promotes data sharing while recognizing the needs of different research communities.

Moving into the future, organizations such as DataONE will continue to assess, monitor, educate, and provide the infrastructure necessary to support such complex grand science challenges.

URL : Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide

DOI : 10.1371/journal.pone.0134826

Best Practices for Ethical Sharing of Individual-Level Health Research Data From Low- and Middle-Income Settings

Sharing individual-level data from clinical and public health research is increasingly being seen as a core requirement for effective and efficient biomedical research. This article discusses the results of a systematic review and multisite qualitative study of key stakeholders’ perspectives on best practices in ethical data sharing in low- and middle-income settings.

Our research suggests that for data sharing to be effective and sustainable, multiple social and ethical requirements need to be met. An effective model of data sharing will be one in which considered judgments will need to be made about how best to achieve scientific progress, minimize risks of harm, promote fairness and reciprocity, and build and sustain trust.

URL : Best Practices for Ethical Sharing of Individual-Level Health Research Data From Low- and Middle-Income Settings

Alternative location : http://m.jre.sagepub.com/content/10/3/302