1. LEADS-4-NDP: Fellowship
LEADS Fellow: Sam Grabus, Drexel University,
Metadata Research Center
LEADS Site: Temple University Library, Digital Scholarship Center
Mentor: Peter Logan

2. <Indexing the Data Set of 19th Century Knowledge> Sam Grabus, Drexel University; Peter Logan, Temple University; Jane Greenberg
PROJECT GOALS
Temple’s broad data science question: Investigate how the specification of concepts change over time across 4 historical Encyclopedia Britannicas ( )
Use automatic indexing to create individual entry descriptive metadata that can be used for analysis across all 4 editions
APPROACH
Identify encyclopedia entry terms that exist in all 4 editions of the Encyclopedia Britannica
Automatically index entries with HIVE using contemporary LCSH and keyword extraction algorithms
ACCOMPLISHMENTS
Data cleaning with R
Intersected 4 lists of entry terms to determine which terms appear in all 4 editions of the encyclopedia; created TXT files for each entry
Ran sample TXT files through HIVE to generate automatic indexing results
Tested 3 keyword extraction algorithms: Kea, Maui, & RAKE
Compared LCSH and Agrovoc vocabularies
Identified challenges & next steps for optimizing RAKE algorithm parameters & addition of historical controlled vocabularies to HIVE
AUTOMATIC INDEXING WITH HIVE
*Acknowledgements to Joan Boone

3. Moving onwards with an NEH grant
Next Steps:
Moving onwards with an NEH grant
Identifying appropriate historical knowledge organization systems
Challenges of using contemporary LCSH for 19th century text
e.g., Encyclopedia entries for Raleigh (Sir Walter), 
SIR (Information Retrieval System)
Digitize one or more of the historical vocabularies into XML or SKOS
LCSH
Universal Decimal Classification (UDC)
Dewey Decimal Classification (DDC) e.g., SKOS for “Rum” in LCSH 
Relevancy testing to identify most effective vocabularies for indexing these encyclopedia entries