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Data Curation / Management Pathway

Data curation and data management school of information sciences.

Data curation and data management falls within the umbrella term, digital curation. Work in data curation and data management is for data of all kinds but is often focused on scientific research data. This may include (1) research data collections, such as “local data generated in a laboratory or research project;” (2) community and reference collections, like “genome databases such as MGI-Mouse,” the “Protein Data Bank;” and (3) other data collections of scientific merit and interest comprised of genetic, biological, climate, census and other scientific and research data (Oliver & Harvey, 2016, p. 48). Data curation and management responsibilities include developing data management plans, describing data using metadata schema, assuring the quality of the data, and preparing data to be used in visualizations and modeling. Other essential tasks include policy development and compliance, preservation planning and facilitation, advocacy and training. Information professionals working in data curation and data librarianship work closely with data creators and data scientists to ensure that research data remains useful and accessible across the data lifecycle.

See Also (Pathways): Digital Collections: Libraries

Data Curation/Management: Position Titles in Information Sciences

These are some of the many positions these information professionals hold:

  • Data Analyst
  • Data Curation Librarian
  • Digital Curation
  • Data Manager
  • Data Specialist
  • eScience Specialist

Data Curation: Position Titles and Descriptions

For more position titles and job requirements, consult job posting services, including the ALA JobList (; I Need a Library Job (; Also, be aware positions may be hybrid. For example, you may find full-time positions that combine roles, such as

  • Data Curators play a leading role in creating workflows, identifying, implementing and assessing the use of technologies that support qualitative and quantitative data gathering, manipulation, transformation, visualization, and analysis within their particular information organization. They may also be expected to advise on the development of infrastructure supporting data repositories that ensure the exposure and reuse of data sets within their organizations holdings. Furthermore, data curators are typically responsible for archiving datasets into digital repositories and for selecting and managing technologies for transforming metadata to augment datasets.
  • Data Librarians are often work in specific disciplines, (e.g., eScience, Social Science, Geography), but in general their responsibilities include maintaining expertise with issues related to scholarly communication such as copyright, open access, and data management and preservation, within their respective discipline. They also develop and provide consultation services for users of the data within their purview, including assistance with data discovery, analysis, visualization, and management.
  • Data Quality Engineers often work in private, business-oriented settings such as private companies (as opposed to academic/public libraries). Their chief responsibility is to maintain the integrity and quality of large data sets. This is done by (1) developing tools, scripts, and tests which detect data anomalies (2) creating new data collections and curating existing data collections, and (3) automating the evaluation of data quality and collecting metrics for further analysis, among other things. This kind of position requires programming skills, including the ability to write scripts in several computer languages such as Python, PHP, Perl, ruby, etc.

Preparing to Enter the Professional World of Science:

Professional Development:


    • Association of College and Research Libraries (Digital Curation Interest Group)
    • CODATA: The International Council For Science’s Committee on Data for Science and Technology
    • Research Data Alliance


    • International Digital Curation Conference
    • Research Description and Access (RDA)
    • SciDataCon
    • Research Data Alliance Plenary Meetings

Publications of Note:

    • International Journal of Digital Curation
    • Journal of eScience Librarianship
    • CODATA Data Science Journal
    • Data journals (specific ones in a variety of domains)

Required Courses:

    • 510 Information Environment
    • 520 Information Representation and Organization
    • 530 Information Access and Retrieval

Recommended Courses:

    • 516 Geospatial Technologies
    • 543 Geographic Information in Information Sciences
    • 532 Sources and Services for Science & Engineering
    • 541 Knowledge Management
    • 545 Scientific and Technical Communications
    • 546 Environmental Informatics
    • 547 Health Sciences Information Centers
    • 552 Academic Libraries
    • 553 Specialized Information Agencies and Services
    • 562 Digital Curation
    • 564 Archives and Records Management
    • 565 Digital Libraries
    • 584 Database Management Systems
    • 588 Human Computer Interaction
    • 592 Big Data Analytics
    • 597 Information Architecture
    • 598 Web Design
    • 599 Practicum

Real-World Potential Experience:

Practicum Settings:

    • Oak Ridge National Laboratory
    • UT Library (Both Hodges and Agriculture)
    • US Geological Survey (USGS)
    • National Center for Atmospheric Research
    • National Oceanic and Atmospheric Administration
    • US Department of State

Recent Placements of UTK-SIS Alumni:

    • US Geological Survey (USGS)
    • National Oceanic and Atmospheric Administration (NOAA)
    • UT Library
    • Cornell University Library

More about Digital curation:

Digital curation is “concerned with actively managing data for as long as it continues to be of scholarly, scientific, research, administrative, and/or personal interest, with the aims of supporting reproducibility, reuse of, and adding value to that data, managing it from its point of creation until it is determined not to be useful, and ensuring its accessibility, preservation, authenticity, and integrity over time” (Oliver & Harvey, 2016, p. 8-9). Digital curation includes “data management, intensive data description, ensuring data quality, collaborative information infrastructure work, and metadata standards work,” (Oliver & Harvey, 2016, p. 61).

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