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

<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 (1797-1911) 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

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 1910-1914 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