Research data management

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Last Update

  • Updated.jpg 12 April 2017


See also Data management | Data management portal | Digital Libraries Glossary | Dublin Core | Open data | Ontologies | Research data glossary

  • Research data management is a trending topic in higher education government agencies and organizations. The experiences of academic institutions and groups are wide-ranging, and include creating and developing research data services as well as planning and implementing new research data management services for the first time. These experiences include but are not limited to: obtaining university and campus support, building partnerships with faculty, data management consultations, assisting with data management plans and data literacy. Academic librarians should be acquainted with the challenges and lessons learned in research data services by other institutions, organizations and agencies...

Main themes in research data

  • Institutional policies for research data
  • Building/expanding research data services
  • Collaboration or tension between units involved with research data
  • Institutional responses to government policies/guidelines concerning research data
  • Systems/strategies for full-life cycle research data curation
  • Tools developed and/or used for data curation/management
  • Digital preservation
  • Data citation and reuse
  • Data repositories (institutional/disciplinary/other)
  • Education and training for research data management/curation

Academic libraries - research data services

More academic libraries are starting to offer a range of research data services related to the identification, collection, management, analysis, and curation of quantitative and qualitative research data.

Assessment of data management needs

Data services can help faculty assess the data management needs of your particular project and develop a plan at the beginning of the data life cycle.

Data management plans required by NSF, NIH, and other funders

Funding agencies, such as the National Science Foundation (NSF) and the National Institutes of Health (NIH), have requirements for data sharing and data management plans. Research Data Services can help you to put together such a plan to comply with the requirements.

Data collection and discovery

Data services can provide consulting in research methods, study design, and questionnaire and interview design. It can provide assistance in locating and using freely available as well as proprietary quantitative, qualitative and GIS data.

Data analysis

Data services can assist with quantitative and qualitative data analysis, use of software, especially SAS, Stata, SPSS and ArcGIS. Services include research methodology, instrument design, and data analysis.

Data curation in digital repositories

Data services can assist you in identifying and finding appropriate repositories for your research data. Academic libraries can help to generate and assign permanent data identifiers (DOIs) to your datasets which allow for easy citation and attribution of datasets.

Types of research data support

  • Identifying appropriate repositories, internal or external
  • Finding existing data sources
  • Data mining
  • Web scraping
  • GIS/Geospatial data management and analysis
  • Dataset purchase/acquisition/subscription
  • Data management plan creation/metadata consulting
  • Qualitative/textual analysis/digital humanities
  • Data preparation
  • Data analysis assistance
  • Statistical software and programming assistance
  • Data visualization
  • Other (please specify in the comments section below)


  • Lack of time
  • Staffing/research coordination
  • Research funding
  • Transitions of team members (for example, graduate students)
  • Publication demands/timelines
  • Regulations/compliance/IRB application
  • Choosing a repository for data
  • Preparing data for sharing
  • Creating a Data Management Plan
  • Lack of appropriate tools to assist with planning and data sharing
  • Lack of institutional support
  • Other (please specify in the comments section below)
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