Fellow for Linked Data Management

The Hanna Holborn Gray Graduate Student Fellowship for Linked Data Management

Division/Department: Technical Services, University of Chicago Library

Fellowship coordinator: Head of Data Management Services

General Summary:

The Hanna Holborn Gray Graduate Student Fellowship for Linked Data Management is responsible for analyzing the bibliographic metadata for the library’s collection and evaluating data enrichment workflows with an emphasis on how persons, other agents, and subjects are applied and managed. The fellow will work closely with the Head of Data Management Services to review current and legacy data practices around library metadata, review tools and workflows for the reconciliation and enrichment of data, and evaluate the quality of automated processes. As a result of these investigations, the fellow will explore and recommend potential pathways for the expansion of current activities. There are opportunities to narrow the focus of the project based on the initial analysis and the skills and interests of the fellow.

The fellow will develop and apply skills in data analysis and processing, working with a dataset of over 14 million records containing more than 53 million name and subject headings. The experience will provide the fellow with knowledge of metadata standards, controlled vocabularies, and linked data principles that contributes to their development as a scholar regardless of their particular field of study. Fellows are expected to make a presentation to Library staff about their activities/project near the completion of their fellowship experience.

While initial appointment is for a single academic quarter, reappointment for additional quarters and/or summer term is anticipated for the successful fellow.

Activities:

  • Become familiar with library descriptive metadata standards such as BIBFRAME, MARC, RDA, and AACR2.
  • Become familiar with authorities and controlled vocabularies for agents/persons and concepts/subjects.
  • Become familiar with goals for the consumption and distribution of linked open data in the research library setting.
  • Master current workflows for data reconciliation and application of URIs to local headings.
  • Use data analysis methods and tools to characterize the state of the library’s data, specifically in the application of names and subject headings.
  • Recommend changes to existing workflows or enhanced workflows for data reconciliation and application of URIs for authorities and terms from controlled vocabularies.
  • Prepare report and presentation on project at the end of fellowship.

Qualifications:

  • Currently enrolled in a UChicago graduate program in good standing during the period of the fellowship
  • Familiarity with SQL and Python, or other querying and scripting languages
  • Ability to analyze large data sets
  • Experience working with metadata or other structured data
  • Excellent written and oral communication skills