Linked Data | Stanford Libraries

Linked Data

The Stanford University Libraries (SUL) with the Council on Library and Information Resources (CLIR) conducted a week-long workshop on the prospects for a large scale, multi-national, multi-institutional prototype of a Linked Data environment for discovery of and navigation among the rapidly, chaotically expanding array of academic information resources.

As preparation for the workshop, CLIR sponsored a literature survey by Jerry Persons, Chief Information Architect emeritus of SUL, that was published originally for workshop participants as background to the workshop and is now publicly available.

The original intention of the workshop was to devise a plan for such a prototype. However, such was the diversity of knowledge, experience, and views of the potential of Linked Data approaches that the workshop participants turned to two more fundamental goals: building common understanding and enthusiasm on the one hand and identifying opportunities and challenges to be confronted in the preparation of the intended prototype and its operation on the other. In pursuit of those objectives, the workshop participants produced: 

  1. a value statement addressing the question of why a Linked Data approach is worth prototyping; 
  2. a manifesto for Linked Libraries (and Museums and Archives and …); 
  3. an outline of the phases in a life cycle of Linked Data approaches; 
  4. a prioritized list of known issues in generating, harvesting & using Linked Data; 
  5. a workflow with notes for converting library bibliographic records and other academic metadata to URIs; 
  6. examples of potential “killer apps” using Linked Data: and 
  7. a list of next steps and potential projects. 

Manifesto for Linked Libraries (and Museums and Archives and …)

We in the cultural heritage and knowledge management institutions are discovering better ways of publishing, sharing, and using information by linking data and helping others do the same. Through this work, we have come to value and to promote the following practices: 

  1. Publishing data on the web for discovery and use, rather than preserving it in dark, more or less unreachable archives that are often proprietary and profit driven; 
  2. Continuously improving data and Linked Data, rather than waiting to publishing “perfect” data; 
  3. Structuring data semantically, rather than preparing flat, unstructured data; 
  4. Collaborating, rather than working alone; 
  5. Adopting Web standards, rather than domain specific ones; 
  6. Using open, commonly understood licenses, rather than closed and/or local licenses. 

While we recognize the need for both approaches in each "couplet," we value the initial ones more. 

 

 

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