Now showing items 1-5 of 27

    • Shareable Local Name Authority Reference Model (Draft) 

      Wang, Jing (2018-04)
      Reference model developed for shareable name authorities, extending the OAIS Reference model; this model is related to the National Strategy for Shareable Local Name Authorities National Forum (SLNA-NF) White Paper. The ...
    • National Strategy for Shareable Local Name Authorities National Forum : White Paper 

      Casalini, Michele; Chew, Chiat Naun; Cluff, Chad; Durocher, Michelle; Folsom, Steven; Frank, Paul; Gatenby, Janifer; Godby, Jean; Kovari, Jason; Lorimer, Nancy; Lynch, Clifford; Murray, Peter; Myntti, Jeremy; Neatrour, Anna; Nimer, Cory; Pilsk, Suzanne; Pitti, Daniel; Quintana, Isabel; Wang, Jing; Warner, Simeon (2018-03-29)
      White paper for the National Strategy for Shareable Local Name Authorities National Forum (SLNA-NF), an Institute of Museum and Library Services funded-project [LG-73-16-0040-16]. Details issues raised through discussions ...
    • Shareable Authorities : Research Questions & Directions in the National Strategy for Shareable Local Name Authorities 

      Kovari, Jason (2016-11-08)
      Slides from the 2016 Digital Library Federation conference presentation concerning background, discussion topics and projected outcomes of the IMLS-funded National Strategy for Shareable Local Name Authorities, a year-long ...
    • Capturing the Web : Web Archiving in Cultural Heritage Institutions 

      Kovari, Jason; Dooley, Jackie M.; Peterson, Christie; Yarmey, Kristen (2016-06-23)
      Presentation on web archiving from four perspectives: technology, collection development, metadata and limited resources. Presented as a seminar as part of the 2016 RBMS (Rare Books and Manuscript Section of the Association ...
    • Linked Data for Production : Research Questions and Project Goals 

      Kovari, Jason; Lorimer, Nancy; Bell, Joyce; Folsom, Steven; McCallum, Sally; Wacker, Melanie (2016-06-25)
      Presentation on project goals and research questions of Linked Data for Production (LD4P), an Andrew W. Mellon Foundation funded collaborative project between six institutions (Columbia, Cornell, Harvard, Library of ...