Student Research: Sammy Davidson

MARC to Linked Data
Help libraries publish their MARC records as Linked Data.

The LOD-LAM KSU Research Group wants to help libraries, archives, and museums integrate linked data into their information systems. The project submitted to the LOD-LAM challenge focuses on the needs of small to medium sized libraries. Smaller libraries may not have the resources, knowledge, or access to participate in and benefit from linked data. In order to do this, we need to create a recipe for these libraries to publish their own linked data resources, generated from their MARC records. Our solution uses existing open source tools and proposes a prototype to automate the conversion of MARC fields to RDF links.

Downloads & Links
• MARC to Linked Data Source code available on GitHub: https://github.com/madlibrarian/AVE.edu.kent.edu.slis.lod-lam.marctordf

• LODLAM Challenge competition entry: http://summit2013.lodlam.net/2013/05/01/marc-to-linked-data/

• LODLAM Challenge Youtube video: http://www.youtube.com/watch?v=_Rkn8JSx5b8

SAM Utility Tool
LODLAM research

The Semantic Analysis Method (SAM) is an open source tool for identifying and analyzing unstructured descriptions of archives and special collections materials to generate potential access points suitable for linked data applications produced by the LOD-LAM Research team. Sammy Davidson played an instrumental role in the programming of the tool under the direction of Dr. Gracy and Dr. Zeng, the primary investigators in the study.

Downloads & Links
• More on the LOD-LAM research Group's development of the SAM tool: Semantic Analysis

• SAM Utility Tool Source available on GitHub: https://github.com/sammysemantics/SAM



This work was supported by a grant from IMLS. It is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. reserved.