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Harvard will work in 2 areas:

  • Cartographic Materials
  • Moving Images from the Harvard Film Archive, as part our Linked Data for Libraries-Labs companion project.

Cartographic Materials

Overview

This sub-project of the Linked Data for Libraries/Production will explore best practices for creating native Linked Data descriptions for library cartographic resources including printed maps, atlases, digital geospatial datasets, and other cartographic information resources. The project will evaluate BIBFRAME’s effectiveness as a data model for describing cartographic materials for research needs and will compare BIBFRAME’s effectiveness versus other available Linked Data descriptive schemas. In addition the group will evaluate the thesauri and controlled vocabularies associated with the description of cartographic resources to identify those vocabularies best suited to describe cartographic resources in a linked data environment. The group’s deliverables will include: a BIBFRAME profile for cartographic resources; a set of published BIBFRAME descriptions for a variety of cartographic resource types; a written evaluation of the project and set of recommendations for future research and development; and presentation of project findings to appropriate library cartographic materials and linked data communities.

Objectives

  • Identify library cartographic resources metadata: use cases, user stories, research needs.
  • Evaluate the existing BF schema for suitability for describing cartographic resources.
  • Evaluate other available LOD vocabularies for describing properties of cartographic resources.
  • Develop and document a BF profile for the description of cartographic resources.
  • Inform the development of metadata production tools to ensure compatibility for describing cartographic resources.
  • Catalog and convert a representative selection of cartographic resources using the developed BF profile (rare materials to born-digital, varying languages) and contribute descriptions to project triple store.
  • Evaluate results of project and share set of recommendations for further research and development.
  • Engage with cartographic resources community to develop BF best practices for description of cartographic resources.

Community

  • Harvard Library
    • Geospatial Metadata Librarian (Project Coordinator)
    • Metadata Creation unit catalogers
    • Metadata Technologies Program Manager
    • Head, Metadata Management and Metadata Creation units
  • Harvard University Information Technology, Library Technology Services
    • Senior Software Engineer
  • LD4L/P partner institution members
    • Stanford metadata librarians and catalogers
    • Library of Congress Geography and Map Division catalogers
  • Selection of project Working Group contributors from the greater community of geospatial metadata and linked data professionals including
    • OpenGeoMetadata digital geospatial data representative
    • GeoHumanities Special Interest Group representative
    • ALA MAGIRT Cataloging and Classification Committee representative
    • ALA MAGIRT GeoTech Committee representative

Deliverables

  • Define a BIBFRAME profile for describing cartographic resources.
  • Publish a representative selection of BIBFRAME descriptions to the project triple store.
  • Work with LD4L to convert a set of OpenGeoMetadata records to linked data descriptions using the cartographic material ontology and to inform the development of a cartographic materials metadata visualization tool.
  • Write an evaluation of the project findings including a description of community use cases and a set of recommendations for further research and development.
  • Present project findings to appropriate library and linked data communities such as the ALA Map and Geospatial Information Round Table (MAGIRT), Program for Cooperative Cataloging (PCC), DLF, Alliance of Digital Humanities Organizations

 

Moving Images

As part the Linked Data for Libraries-Labs companion project, Harvard will explore best practices for creating linked data descriptions for moving image resources including a variety of formats (film prints, negatives, DVDs, VHS, Super 8, and others) and content (feature films, trailers, home movies, ethnographic films, propaganda) and related archival materials (including production elements, artwork, film stills, and promotional ephemera) held by the Harvard Film Archive. The project will evaluate BIBFRAME/LD4L’s effectiveness as a data model for describing moving image materials for research needs and the lifecycle of moving image materials, and identify vocabularies for description of these materials in a linked data environment. The project will create mappings for records from the HFA’s film print database, focusing on a subset of moving image materials by women directors. Wherever possible, entities will be reconciled to linked data URIs, including personal and corporate names (ISNI, LCNAF), place names (GeoNames), genres (LC genre/form, Getty AAT), and works. The project deliverables will include: a BIBFRAME/LD4L profile for moving image resources; a set of published descriptions for moving image materials and related archival collections; deployment of descriptions as linked data in the triplestore; a user interface and visualization for film researchers based on an Omeka or Harvard Geospatial Library on-line collection; and a written evaluation of the project and set of recommendations for future research and development.

Objectives

  • Create and pilot a software tool for converting existing HFA metadata into BIBFRAME RDF, including entity resolution.
  • Identify BIBFRAME extensions, if any.
  • Load the HFA linked data into the Harvard linked data infrastructure to support SPARQL queries defining relevant subgraphs.
  • Create or repurpose a linked data visualization tool for displaying relevant portions of the HFA RDF graph for each described item.
  • Assess the end-user value for discovery and research of the HFA linked data, including a written summary of project findings disseminated to appropriate moving image and linked data communities with a set of recommendations for future research and development.

 

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