Title
Learning, Understanding, and Using Linked Data
Location
KIPJ Room C
Event Website
http://metadataetc.org/LOD/LOD-index.html
Session Type
Workshop
Start Date
23-4-2018 1:00 PM
End Date
23-4-2018 4:00 PM
Abstract
This workshop begins with a review of Linked Data fundamentals, focusing on the developments in the field that most impact libraries, archives, and museums (LAMs). Various Linked Data products created by LAMs will be used to demonstrate the capabilities of applying the Linked data approach to the information organization and discovery in the Semantic Web. In addition, the workshop will provide hands-on experience in which participants will access and wield Linked Data datasets as non-techy end-users, for the purpose of understanding the basics of Linked Data as well as the potential benefits of Linked Data approach.
The second part of the workshop will introduce a competency framework that defines the knowledge and skills necessary for professional practice in the area of Linked Data, developed by the Linked Data for Professional Educators (LD4PE) project funded by the Institute of Museum and Library Services (IMLS). The workshop will include an overview of the structure and content of the Competency Index for Linked Data and the LD4PE website (http://explore.dublincore.net). The hands-on part will explore the LD4PE website’s competency index and over 600 related learning resources aligned with the competencies, a number of roadmaps for various professionals, and a package of learning Linked Data through a OCLC provided WorldCat Linked Data dataset.
Learning, Understanding, and Using Linked Data
KIPJ Room C
This workshop begins with a review of Linked Data fundamentals, focusing on the developments in the field that most impact libraries, archives, and museums (LAMs). Various Linked Data products created by LAMs will be used to demonstrate the capabilities of applying the Linked data approach to the information organization and discovery in the Semantic Web. In addition, the workshop will provide hands-on experience in which participants will access and wield Linked Data datasets as non-techy end-users, for the purpose of understanding the basics of Linked Data as well as the potential benefits of Linked Data approach.
The second part of the workshop will introduce a competency framework that defines the knowledge and skills necessary for professional practice in the area of Linked Data, developed by the Linked Data for Professional Educators (LD4PE) project funded by the Institute of Museum and Library Services (IMLS). The workshop will include an overview of the structure and content of the Competency Index for Linked Data and the LD4PE website (http://explore.dublincore.net). The hands-on part will explore the LD4PE website’s competency index and over 600 related learning resources aligned with the competencies, a number of roadmaps for various professionals, and a package of learning Linked Data through a OCLC provided WorldCat Linked Data dataset.
https://digital.sandiego.edu/symposium/2018/2018/2
Comments
Marcia Lei Zeng is Professor at School of Information, Kent State University. She holds a Ph.D. from the School of Information Sciences at the University of Pittsburgh. Her major research interests include knowledge organization structures/systems/services (KOS), Linked Data, metadata, semantic technologies, and digital humanities. Her scholarly publications consist of more than 90 papers and five books, as well as over 200 national and international conference presentations, invited lectures, and keynote speeches. Her research projects have received funding from the National Science Foundation (NSF), Institute of Museum and Library Services (IMLS), OCLC Online Computer Library Center, Fulbright Scholar Program, and other foundations. She was an Invited Expert on the W3C Library Linked Data (LOD) Incubator Group and has held office in numerous international library and information science associations. Currently she is serving as an Executive Board Member of the International Society for Knowledge Organization (ISKO).