Linked Data

Linked Data is about communities agreeing on the meaning of their data and sharing it in a massively networked information space. This vision is taking shape in many sectors, including e-commerce, medicine, scientific research, and government services. OCLC Research is a leader in driving this transformation in the library community.

Linked Data Research

The goal of the OCLC's research program is to advance the state of the art in modeling, storage, and delivery of linked data in the service of the library community's use cases: creating cleaner, more normalized, more machine-understandable data that works harder to connect library patrons to the resources they seek. Outcomes of our work include publications, presentations, webinars, datasets, and software demos that address researchers, engineers, and subject-matter experts engaged in the same work. The list on this page highlights key outcomes not discussed in Library Linked Data in the Cloud.

Experiments with Wikibase


Prototyping a Linked Data Platform for Production Cataloging Workflows
Presentation (.pdf)  |  13 April 2018
By Andrew Pace and Jason Kovari.
Wikibase, the open-source platform that powers Wikidata, offers many advantages for prototyping a library resource description platform built natively from linked data. More details are available on the project page.
Presented at the Coalition for Networked Information Spring Membership Meeting, San Diego, CA.

Using the Semantic Web to Improve Knowledge of Translations
Presentation (.ppt)  |  26 October 2017
By Karen Smith-Yoshimura
Representations of works and their translations can be enriched by merging RDF graphs derived from WorldCat records with corresponding Wikidata descriptions.  More details are available on the Multilingual Bibliographic Structure project page.
Presented at the International Conference on Dublin Core and Metadata Applications, Washington DC.

 

The International Image Interoperability Format


IIIF at OCLC
Presentation (.ppt)  |  27 March 2018
By Jeff Mixter
OCLC is engaged in two activities involving the International Image Interoperability Format (IIIF), a linked-data-aware standard for the description and presentation of digitized images:

  1. The IIIF Presentation API has been implemented in CONTENTdm; and
  2. Jeff Mixter and Bruce Washburn are serving on an advisory board that guides   IIIF’s development.

Presented at the Visual Resources Association (VRA) Annual Conference, Philadelphia PA.

 

From Headings to Identities


National Strategy for Shareable Local Name Authorities National Forum: White Paper
White paper  |  March 2018
By Michele Casalini, Chew Chiat Naun, Chad Cluff, Michelle Durocher, Steven Folsom, Paul Frank, Janifer Gatenby, Jean Godby, Jason Kovari, Nancy Lorimer, Clifford Lynch, Peter Murray, Jeremy Myntti, Anna Neatrour, Cory Nimer, Suzanne Pilsk, Daniel Pitti, Isabel Quintana, Jing Wang, and Simeon Warner
The white paper identifies the need to increase the quality, quantity, and efficiency of workflows that produce disambiguated names of people, organizations, and other important entities associated with library resources. In the process, the practice of library authority control will be modernized to focus on the management of identities instead of authorized name strings. The result is more congruent with principles of linked data. Follow-up work is being conducted in the PCC Task Group on Identity Management in NACO (.pdf). Jean Godby and Diane Vizine-Goetz are participating.
An outcome of the IMLS grant Shareable Local Authorities awarded to Cornell University; Chew Chiat Naun and Jason Kovari, principal investigators.


Creating Linked Data for Use


Linking Your Data
Presentation (.pdf)  |  2016
By Jeff Mixter
Mixter describes an editing environment that was prototyped with CONTENTdm users, which allows metadata subject-matter experts to improve collections of Dublin Core descriptions by normalizing or remediating text strings and associating them with URIs. Results are available either as enriched Dublin Core records, or as linked data expressed in Schema.org.
Presented at the Canadian Linked Data Summit, 24-25 October 2016, Montréal (Canada).

Looking Inside the Library Knowledge Vault
Works in Progress Webinar  |  12 August 2015
By Bruce Washburn and Jeff Mixter
The webinar evaluates Google research as the basis for an experimental Library Knowledge Vault, a resource containing clean, authoritative data organized as entities and relationships and expressed as linked data. This resource is exposed through the EntityJS prototype, which supports a rich user experience for browsing and knowledge discovery. Experts can use EntityJS as an editing interface, thus enriching the Vault by filling in gaps and correcting errors.
Presented by OCLC Research.

"Exploring Ways to Use Linked Data" from the webinar Looking Inside the Library Knowledge Vault by OCLC Research, CC BY 4.0

 

The Transition from MARC and Other Legacy Standards


From Records to Things: Managing the Transition from Legacy Library Metadata to Linked Data
Article  |  2017
By Jean Godby and Karen Smith-Yoshimura
Using translated works as an example, the authors show how MARC can be converted to linked data more easily if catalogers use MARC’s machine-understandable features to encode descriptions of important entities and relationships. To enact the changes, the Program for Cooperative Cataloging (PCC) can be enlisted to promote the recommendations of individuals to best practices that can be implemented on a large scale. This article is a follow-up to the November 2015 webinar How You Can Make the Transition from MARC to Linked Data Easier, which was a springboard for Jean’s participation in the PCC Task Group for URIs in MARC.
Published in the Bulletin of the Association for Information Science and Technology. 43 (2): 18-23.

"Making MARC 'Linked Data Ready'" from the webinar How You can make the Transition
from MARC to Linked Data Easier
by OCLC Research, CC BY 4.0

Challenges of Mapping Digital Collections Metadata to Schema. org: Working with CONTENTdm
Conference Paper  |  2016
By Patricia Lampron, Jeff Mixter and Myung-Ja K Han
This paper describes the challenges of mapping unique digital collections metadata to Schema.org and identifies lessons learned from linked data experiments on CONTENTdm metadata at the University of Illinois at Champaign-Urbana Library and OCLC.
Presentation at the Metadata and Semantics Research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016. Proceedings edited by Emmanouel Garoufallou, Imma Subirats Coll, Armando Stellato and Jane Greenberg,181-186. Cham, Switzerland.

Using a Common Model: Mapping VRA Core 4.0 Into an RDF Ontology
Article  |  2014
By Jeff Mixter
Mixter describes a procedure for creating an RDF ontology for VRA Core, a vocabulary maintained by the Visual Resources Association and used for describing works of visual culture and associated images. The ontology is expressed in Schema.org, with extensions from several commonly used RDF vocabularies. This work is a foundation for Jeff’s continued involvement in the VRA community.
Published in the Journal of Library Metadata, Volume 14, 2014, Issue 1.

 

Ontologies and Models


BIBFRAME and OCLC Works: Defining Models and Discovering Evidence
Presentation (.pptx)  |  25 June 2017
By Jean Godby and Diane Vizine-Goetz
This presentation describes the alignment of OCLC's and LCs "work" clusters algorithmically derived from MARC bibliographic records and is a companion to OCLC's Work on Works (.ppt), which gives a brief overview of work descriptions in VIAF. Both presentations contain material that is described in the white paper (pdf) being prepared by the PCC SCS/LDAC Task Group on the Work Entity.
Presented at the BIBFRAME Update Forum at ALA Annual Conference, Chicago, IL (USA).

"OCLC's models of 'Work'" from BIBFRAME and OCLC Works by OCLC Research, CC BY 4.0

A Division of Labor: The Role of Schema.org in a Semantic Model of Library Resources
Book chapter (.pdf)  |  2016
By Carol Jean Godby
Books, sound recordings, and other objects in a library collection can be described in ordinary language. But librarians also need a specialist’s language that defines concepts involved in their curation. Since current library linked data models are less focused on curation than the ordinary user’s experience of library resources, Schema.org (the language of webmasters) easily matches the expressiveness of ontologies designed for librarianship. This relationship is expected to change as curation models mature.
Published as part of Linked Data for Cultural Heritage, an ALCTS Monograph, edited by Ed Jones and Michele Seikel. Chicago, IL: ALA Editions, an imprint of the American Library Association. 

Common Ground: Exploring Compatibilities Between the Linked Data Models of the Library of Congress and OCLC
OCLC Research Report (.pdf)  |  2015
By Carol Jean Godby and Ray Denenberg
A joint statement with the Library of Congress discusses the high-level alignment between BIBFRAME and OCLC’s model of creative works based on Schema.org.
Published by Library of Congress and OCLC Research.

Describing Theses and Dissertations Using Schema.org 
Conference paper (.pdf)  |  2014
By Jeff Mixter, Patrick OBrien, and Kenning Arlitsch
The authors describe an extension vocabulary for expressing a model of theses and dissertations, using Schema.org as a foundation. This work is a deliverable from the IMLS grant Getting Found, awarded to Kenning Arlitsch, Dean of the Library, Montana State University.
Published in DCMI'14 Proceedings of the 2014 International Conference on Dublin Core and Metadata Applications, Austin, Texas, October 8-11, 2017.

 

 

Getting Started

New to linked data? No problem. We've pulled together some resources to help you get started with linked data. Check them out:

Get Started

Join the Linked Data Conversation

Find OCLC Research's latest Linked Data ideas, thoughts, data, and projects on our blog Hanging Together.

Read Linked Data Posts

Linked Data Team

Team Lead

Jean Godby

Team Members

Ralph LeVan
Jeff Mixter
Stephan Schindehette
Karen Smith-Yoshimura
Roy Tennant
Shenghui Wang
Bruce Washburn
Jeff Young

OCLC and Linked Data Strategic Approach

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