Étiquette : research data

Do You Have an Institutional Data Policy? A Review of the Current Landscape of Library Data Services and Institutional Data Policies

Auteur de l’article Par Hans Dillaerts
Date de l’article 23 septembre 2015
2 commentaires sur Do You Have an Institutional Data Policy? A Review of the Current Landscape of Library Data Services and Institutional Data Policies

INTRODUCTION

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.

METHODS

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.

RESULTS

The study has uncovered findings surrounding library data services, institutional data policies, and content within the policies.

DISCUSSION

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.

CONCLUSION

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.

URL : Do You Have an Institutional Data Policy? A Review of the Current Landscape of Library Data Services and Institutional Data Policies

DOI : http://doi.org/10.7710/2162-3309.1232

Étiquettes data policy, data repositories, Library Data Services, research data

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

Auteur de l’article Par Hans Dillaerts
Date de l’article 23 septembre 2015
2 commentaires sur 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

Étiquettes case study, data sharing, research data, research data management, scientific practices

Data Management Practices Across an Institution: Survey and Report

Auteur de l’article Par Hans Dillaerts
Date de l’article 23 septembre 2015

INTRODUCTION

Data management is becoming increasingly important to researchers in all fields. The E-Science Working Group designed a survey to investigate how researchers at Northwestern University currently manage data and to help determine their future needs regarding data management.

METHODS

A 21-question survey was distributed to approximately 12,940 faculty, graduate students, postdoctoral candidates, and selected research-affiliated staff at Northwestern’s Evanston and Chicago Campuses. Survey questions solicited information regarding types and size of data, current and future needs for data storage, data retention and data sharing, what researchers are doing (or not doing) regarding data management planning, and types of training or assistance needed. There were 831 responses and 788 respondents completed the survey, for a response rate of approximately 6.4%.

RESULTS

Survey results indicate investigators need both short and long term storage and preservation solutions. However, 31% of respondents did not know how much storage they will require. This means that establishing a correctly sized research storage service will be difficult. Additionally, research data is stored on local hard drives, departmental servers or equipment hard drives. These types of storage solutions limit data sharing and long term preservation.

Data sharing tends to occur within a research group or with collaborators prior to publication, expanding to more public availability after publication. Survey responses also indicate a need to provide increased consulting and support services, most notably for data management planning, awareness of regulatory requirements, and use of research software.

URL : Data Management Practices Across an Institution: Survey and Report

DOI : http://doi.org/10.7710/2162-3309.1225

Étiquettes case study, Data Management Infrastructure, research data, research data management, scientific practices

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

Auteur de l’article Par Hans Dillaerts
Date de l’article 18 septembre 2015

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

Étiquettes data sharing, research data, scientific practices

Empirical Big Data Research: A Systematic Literature Mapping

Auteur de l’article Par Hans Dillaerts
Date de l’article 11 septembre 2015
2 commentaires sur Empirical Big Data Research: A Systematic Literature Mapping

Background

Big Data is a relatively new field of research and technology, and literature reports a wide variety of concepts labeled with Big Data. The maturity of a research field can be measured in the number of publications containing empirical results. In this paper we present the current status of empirical research in Big Data. Method: We employed a systematic mapping method with which we mapped the collected research according to the labels Variety, Volume and Velocity. In addition, we addressed the application areas of Big Data.

Results

We found that 151 of the assessed 1778 contributions contain a form of empirical result and can be mapped to one or more of the 3 V’s and 59 address an application area.

Conclusions

The share of publications containing empirical results is well below the average compared to computer science research as a whole. In order to mature the research on Big Data, we recommend applying empirical methods to strengthen the confidence in the reported results. Based on our trend analysis we consider Variety to be the most promising uncharted area in Big Data.

URL : Empirical Big Data Research: A Systematic Literature Mapping

Alternative location : http://arxiv.org/abs/1509.03045

Étiquettes big data, research data

Sharing Research Data and Intellectual Property Law: A Primer

Auteur de l’article Par Hans Dillaerts
Date de l’article 2 septembre 2015

Sharing research data by depositing it in connection with a published article or otherwise making data publicly available sometimes raises intellectual property questions in the minds of depositing researchers, their employers, their funders, and other researchers who seek to reuse research data. In this context or in the drafting of data management plans, common questions are (1) what are the legal rights in data; (2) who has these rights; and (3) how does one with these rights use them to share data in a way that permits or encourages productive downstream uses? Leaving to the side privacy and national security laws that regulate sharing certain types of data, this Perspective explains how to work through the general intellectual property and contractual issues for all research data.

URL : Sharing Research Data and Intellectual Property Law: A Primer

DOI : 10.1371/journal.pbio.1002235

Étiquettes data reuse, Intellectual Property, research data