Program Announcement: LITA/ALCTS Linked Library Data Interest Group Meeting @
ALA Annual
Time: Saturday, June 23, 2018, 9:00-10:00 AM
Location: Ernest N. Morial Convention Center Convention Center, Rm 265-268
Please join us for three exciting presentations describing linked data
projects. After our speaker presentations, the group will have an opportunity
for questions and discussion.
Evidence-Building using Linked Administrative Data at the Census Bureau
Kate McNamara, Census Bureau
The Census Bureau is expanding its Data Linkage Infrastructure to improve
access for evaluators, program and policy analysts, and researchers. The new
data linkage initiative improves access to these data, increases the
discoverability of data with inventories and metadata, and leverages new
technology. We are currently conducting a variety of research projects
leveraging administrative records linked to demographic and economic survey
data. Census has also played a role in collaborative efforts to create best
practices for data sharing and access, including the Commission on
Evidence-Based Policymaking and the Administrative Data Research Facilities
Network. Audience members will come away with an understanding of data linkage
at Census and learn how librarians can play a role in the evolving landscape of
administrative data.
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Who Will be Our bf: Comparing techniques for conversion from MARC to BIBFRAME
Sharon Farnel, Abigail Sparling, Ian Bigelow, and Danoosh Davood
University of Alberta Libraries
The University of Alberta Libraries is actively ramping up for linked data
implementation through local experimentation, research and external
partnerships. Though BIBFRAME is still in development, several transformation
tools have already been created, and with many libraries planning for a future
move to linked data it would seem timely to compare approaches to moving legacy
MARC data to BIBFRAME. Setting aside the question of whether BIBFRAME should be
the vehicle for libraries to move to linked data, this investigation is aimed
at comparing two approaches to converting MARC to bf:2.0: LC MARC to BIBFRAME
XSLT: An XSLT 1.0 application aimed at converting MARC to RDF/XML released in
March 2017 and Casalini SHARE Virtual Discovery Environment: A project by
Casalini Libri and @Cult to develop a linked data discovery environment,
including a conversion tool for MARC to bf:2.0 RDF.
Through the comparison and analysis of these two transformation approaches
several topics will be explored: Comparison of data mapping through conversion,
Implications for conversions for monograph and serial formats, Approaches to
reconciliation through both processes, and In house and vendor workflow
implications.
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Demonstrating the Production Value of Linked Data Services
John Chapman, OCLC
Xiaoli Li, University of California Davis
Cornell University, University of California, Davis, and the Montana State
Library have partnered with OCLC in a joint research project prototyping a new
suite of linked data services. This unique project uses the out-of-the-box
services from Wikibase and a high-quality set of entities from multiple linked
data sources. The prototype comprises services for 1) reconciling strings
representing people, organizations, concepts, places, and events against an
index based on entities, providing persistent identifiers; and 2) creating,
editing, and sharing entity descriptions, while also allowing for the
contribution of additional contextual relationships between entities, beyond
those that can be found by mining structured data in bibliographic and
authority data.
In this presentation, Xiaoli Li, Department Head - Content Support Services,
from the University of California, Davis and John Chapman, Senior Product
Manager - Metadata Services, from OCLC will give an update on project progress,
demonstrate the interfaces and underlying data, and cover technical challenges
and achievements. As the project has focused on meeting real library use cases,
the speakers will also discuss insights into the efficacy and efficiency of
introducing linked data tools in metadata management workflows.
