scholarly journals Bringing Research Data Management to Academic Libraries

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Falco Jonas Hüser ◽  
Paula Maria Martinez Lavanchy
Keyword(s):  
Data Management ◽  
Code Of Conduct ◽  
Research Integrity ◽  
Research Data ◽  
Central Position ◽  
Support Functions ◽  
Daily Routines ◽  
Research Data Management ◽  
Data Life Cycle ◽  
Funding Agencies

Modern research institutions are faced with rapidly increasing challenges imposed by data-driven science and have to deal with new demands from funding agencies and publishers regarding open access to research data as well as from the Code of Conduct for Research Integrity on reproducibility of results. In reply to these requirements, the Technical University of Denmark (DTU) has adapted a two-fold strategy of bringing together decision-makers, relevant support units in the administration and researchers from all departments for the task of designing policies and services in alignment with common traditions in the different fields of research. This mixed “bottom-up” / “top-down” approach ensures that best practices  for research data management can be implemented in the daily routines of employees in a practical and supportive way while ensuring that the researchers can live up to all relevant administrative, legal and ethical standards.  In this presentation, we will show how DTU Library has taken over a central position in this process by investigating the needs and demands from researchers in the different fields, drafting procedures and guidelines for research data management and establishing support functions and training for all aspects  of the data life cycle. Within this new and complex area, the creation of new positions for research data management at the library in addition to an optimal utilization of existing resources and knowledge has been crucial for building up the necessary expertise and thus for the success of the strategy.  AuthorsFalco Jonas Hüser, PhDProject Officer – Research Data Managementemail: [email protected] 0000-0001-9645-6691Paula Maria Martinez Lavanchy, PhDProject Officer – Research Data Managementemail: [email protected] 0000-0003-1448-0917

scholarly journals Research data management and services: Resources for novice data librarians

2017 ◽  
Vol 78 (5) ◽  
pp. 274 ◽  
Author(s):  
Sarah Barbrow ◽  
Denise Brush ◽  
Julie Goldman
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Academic Libraries ◽  
Research Data ◽  
Research Data Management ◽  
Academic Fields ◽  
Data Life Cycle ◽  
Management Plans ◽  
Share Data

Research in many academic fields today generates large amounts of data. These data not only must be processed and analyzed by the researchers, but also managed throughout the data life cycle. Recently, some academic libraries have begun to offer research data management (RDM) services to their communities. Often, this service starts with helping faculty write data management plans, now required by many federal granting agencies. Libraries with more developed services may work with researchers as they decide how to archive and share data once the grant work is complete.

Research data management: a conceptual framework

2016 ◽  
Vol 65 (4/5) ◽  
pp. 226-241 ◽  
Author(s):  
Dimple Patel
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Conceptual Framework ◽  
Data Privacy ◽  
Research Data ◽  
Content Type ◽  
Institutional Level ◽  
Research Data Management ◽  
Data Life Cycle ◽  
Effective Manner

Purpose Research data management (RDM) is gaining a lot of momentum in the present day and rightly so. Research data are the core of any research study. The findings and conclusions of a study are entirely dependent on the research data. Traditional publishing did not focus on the presentation of data, along with the publications such as research monographs and especially journal articles, probably because of the difficulties involved in managing the research data sets. The current day technology, however, has helped in making this task easier. The purpose of this paper is to present a conceptual framework for managing research data at the institutional level. Design/methodology/approach This paper discusses the significance and advantages of sharing research data. In the spirit of open access to publications, freeing research data and making it available openly, with minimal restrictions, will help in not only furthering research and development but also avoiding duplication of efforts. The issues and challenges involved in RDM at the institutional level are discussed. Findings A conceptual framework for RDM at the institutional level is presented. A model for a National Repository of Open Research Data (NRORD) is also proposed, and the workflow of the functioning of NRORD is also presented. Originality/value The framework clearly presents the workflow of the data life-cycle in its various phases right from its creation, storage, organization and sharing. It also attempts to address crucial issues in RDM such as data privacy, data security, copyright and licensing. The framework may help the institutions in managing the research data life-cycle in a more efficient and effective manner.

Research data management in practice: Results from a cross-sectional survey of health and medical researchers from an academic institution in Australia

2019 ◽  
Vol 49 (2-3) ◽  
pp. 108-116 ◽  
Author(s):  
Michelle A Krahe ◽  
Julie Toohey ◽  
Malcolm Wolski ◽  
Paul A Scuffham ◽  
Sheena Reilly
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Research Data ◽  
Academic Institution ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Convenience Sample ◽  
Research Data Management ◽  
Data Life Cycle ◽  
Medical Researchers

Background: Building or acquiring research data management (RDM) capacity is a major challenge for health and medical researchers and academic institutes alike. Considering that RDM practices influence the integrity and longevity of data, targeting RDM services and support in recognition of needs is especially valuable in health and medical research. Objective: This project sought to examine the current RDM practices of health and medical researchers from an academic institution in Australia. Method: A cross-sectional survey was used to collect information from a convenience sample of 81 members of a research institute (68 academic staff and 13 postgraduate students). A survey was constructed to assess selected data management tasks associated with the earlier stages of the research data life cycle. Results: Our study indicates that RDM tasks associated with creating, processing and analysis of data vary greatly among researchers and are likely influenced by their level of research experience and RDM practices within their immediate teams. Conclusion: Evaluating the data management practices of health and medical researchers, contextualised by tasks associated with the research data life cycle, is an effective way of shaping RDM services and support in this group. Implications: This study recognises that institutional strategies targeted at tasks associated with the creation, processing and analysis of data will strengthen researcher capacity, instil good research practice and, over time, improve health informatics and research data quality.

scholarly journals Exploring research data management planning challenges in practice

2020 ◽  
Vol 62 (1) ◽  
pp. 29-37
Author(s):  
Armel Lefebvre ◽  
Baharak Bakhtiari ◽  
Marco Spruit
Keyword(s):  
Data Management ◽  
Scientific Information ◽  
Public Funding ◽  
Research Data ◽  
High Quality ◽  
Management Planning ◽  
Research Data Management ◽  
Barriers To Access ◽  
Funding Agencies ◽  
Management Plans

AbstractResearch data management planning (RDMP) is the process through which researchers first get acquainted with research data management (RDM) matters. In recent years, public funding agencies have implemented governmental policies for removing barriers to access to scientific information. Researchers applying for funding at public funding agencies need to define a strategy for guaranteeing that the acquired funds also yield high-quality and reusable research data. To achieve that, funding bodies ask researchers to elaborate on data management needs in documents called data management plans (DMP). In this study, we explore several organizational and technological challenges occurring during the planning phase of research data management, more precisely during the grant submission process. By doing so, we deepen our understanding of a crucial process within research data management and broaden our understanding of the current stakeholders, practices, and challenges in RDMP.

scholarly journals Potential Roles for Science Librarians in Research Data Management: A Gap Analysis

2021 ◽  
Author(s):  
Wade Bishop ◽  
Hannah Collier ◽  
Ashley Marie Orehek ◽  
Monica Ihli
Keyword(s):  
Data Management ◽  
Gap Analysis ◽  
Research Integrity ◽  
Research Data ◽  
Management Support ◽  
Job Descriptions ◽  
Data Services ◽  
Data Intensive ◽  
Research Data Management ◽  
Role Based

As many sciences move to be more data-intensive, some science librarians are offering more research data services and perform research data management roles. Job analyses provide insight and context to the tasks employees actually do versus what their job descriptions depict or employers assume. Two separate job analyses studies investigated the roles and responsibilities of data services librarians and research integrity officers among the top 10 private and top 10 public higher education institutions. The focus of these interviews was research data management support roles. Comparing these two groups’ responses indicates that the role-based responsibilities for research data services are not always clear within institutions and are predominantly placed on individual researchers or research teams, but science librarians may provide some solutions to address this gap. This paper presents a model for the potential roles of science librarians in research data management.

scholarly journals Investigation of Non-Academic Data Management Practices to Inform Academic Research Data Management

2018 ◽  
Vol 4 ◽  
Author(s):  
Steven Van Tuyl ◽  
Amanda Whitmire
Keyword(s):  
Best Practices ◽  
Data Management ◽  
Management Practices ◽  
Academic Research ◽  
Research Data ◽  
Government Agencies ◽  
University Administrators ◽  
Academic Environments ◽  
Research Data Management ◽  
Funding Agencies

In recent years, the academic research data management (RDM) community has worked closely with funding agencies, university administrators, and researchers to develop best practices for RDM. The RDM community, however, has spent relatively little time exploring best practices used in non-academic environments (industry, government, etc.) for management, preservation, and sharing of data. In this poster, we present the results of a project wherein we approached a number of non-academic corporations and institutions to discuss how data is managed in those organizations and discern what the academic RDM community could learn from non-academic RDM practices. We conducted interviews with 10-20 companies including tech companies, government agencies, and consumer retail corporations. We present the results in the form of user stories, common themes from interviews, and summaries of areas where the RDM community might benefit from further understanding of non-academic data management practices.

Research data management in Turkey: A survey to build an effective national data repository

IFLA Journal ◽  
2020 ◽  
pp. 034003522091798
Author(s):  
Guleda Dogan ◽  
Zehra Taskin ◽  
Arsev Umur Aydinoglu
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Management Plan ◽  
Development Stage ◽  
Research Data ◽  
Data Repository ◽  
Research Data Management ◽  
Funding Agencies ◽  
Technological Research Council ◽  
Management Issues

Research data management is an important topic for funding agencies, universities and researchers. In this context, the main aim of this study is to collect preliminary information for Aperta, which is being developed by the Scientific and Technological Research Council of Turkey, to fulfil the following goals: determine the research data management awareness levels of researchers in Turkey; understand current research data management practices in their research environments; and find out their experiences of policy issues. For this, a questionnaire was distributed to 37,223 researchers, with 1577 researchers completing it. The results indicated that researchers who spend more time with data have more concerns about data management issues. The levels of experience of creating a data management plan were quite low. The importance of this study lies in how it is able to show the current research data management practices of Turkish scholars during the new repository’s foundational development stage.

scholarly journals Effectiveness of data auditing as a tool to reinforce good research data management (RDM) practice: a Singapore study

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Hui Xing Lau ◽  
Ser Lin Celine Lee ◽  
Yusuf Ali
Keyword(s):  
Data Management ◽  
Medical Science ◽  
Research Integrity ◽  
Routine Data ◽  
Sampling Period ◽  
Research Data ◽  
Data Repository ◽  
Research Data Management ◽  
Data Auditing ◽  
Good Research

Abstract Background Institutions, funding agencies and publishers are placing increasing emphasis on good research data management (RDM). RDM lapses in medical science can result in questionable data and cause the public’s confidence in the scientific community to crumble. A fledgling medical school in a young university in Singapore has mandated every funded research project to have a data management plan (DMP). However, researchers’ adherence to their DMPs was unknown until the school embarked on routine data auditing. We hypothesize that research data auditing improves RDM awareness, compliance and reception in the school. Methods We conducted surveys with research PIs and researchers before and after data auditing to evaluate differences in self-reported RDM awareness, compliance and reception. As it is mandatory to deposit research data in a central data repository system in the school, we tracked data deposition by each laboratory from 2 weeks before to 3 months after data auditing as a marker of actual RDM compliance. Results Research data auditing had an overall positive effect on self-reported RDM awareness, compliance and reception for both research PIs and researchers. Research PIs agreed more that RDM was important to scientific reproducibility, were more aware of proper RDM, had higher RDM strength in their laboratories and were more compliant with the DMP. Both research PIs and researchers believed data auditing helped them to be more compliant with data deposition in the repository. However, data auditing had no significant impact on laboratories’ data deposition rates over time, which could be due to the short sampling period. Conclusions Research PIs and researchers generally felt that data auditing was effective in improving RDM practices. It helped to evaluate their RDM practices objectively, propose corrective actions for RDM lapses and spread awareness of the university’s data management policies. Our findings corroborated other studies in medical research, geosciences, engineering and ethics that data auditing promotes good RDM practices. Hence, we recommend research institutions worldwide to adopt data auditing as a tool to reinforce research integrity.

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