NOTSL

Marcia Zeng – Linked Data and LAMs (Libraries, Archives, and Museums) Why and What?

Jennifer Bowen – Linked Data: Why Bother?

The deadline for registration was Friday, November 15.

NOTSL Fall Meeting
November 22, 2013
Kent State University
Kent Student Center, Room 306
Kent, OH 44242

Registration and light refreshments: 9:00 a.m. – 9:30 a.m.
Program: 9:30 a.m. – 3:00 p.m.

Northern Ohio Technical Services Librarians is pleased to present our Fall program on linked data and libraries.  Presented by…

Dr. Marcia Zeng, Professor of Library and Information Science at Kent State University, will be our morning speaker.  Dr. Zeng holds a Ph.D. from the School of Information Sciences at University of Pittsburgh and an M.A. from Wuhan University in China. Her major research interests include knowledge organization systems (taxonomy, thesaurus, ontology, etc), Linked Data, metadata and markup languages, database quality control, multilingual and multi-culture information processing, and digital libraries for cultural objects.  Dr. Zeng will provide an overview of Linked Data principles.

Jennifer Bowen, Assistant Dean, Information Management Services, University of Rochester and co-author of “RDA and the eXtensible Catalog” will address how linked data can be applied in libraries and why it is important. Ms. Bowen is the Chair of the eXtensible Cataloging Organization Board and was a principal investigator for the eXtensible Catalog Project at the University of Rochester.  She has written and spoken extensively on this topic. Ms. Bowen also was the American Library Association Representative to the Joint Steering Committee for the Revision of AACR2 from 2004-2007. Jennifer Bowen holds masters degrees in library science and historical musicology from the University of Michigan.  She has spent her career as a librarian working in the areas of cataloging and metadata, initially as a specialist in music cataloging.  In recent years she has focused her research on metadata standards development (RDA), the FRBR data model, and the use of legacy library metadata in next-generation discovery systems.