Location

Texas Conference on Institutional Repositories - held at SMU

Event Website

http://scholar.smu.edu/tcir/

Abstract

Ever look at a signature and realize you can’t read the name, even though the letters look almost legible? Now imagine there is not a printed name near that signature. Multiply this issue by 2-4 names per item in a collection of thousands. The University of North Texas Libraries recently ran into this problem when adding metadata to recently-digitized theses and dissertations (ETDs) from the 1930s to 1990s. Deciphering the signatures proved difficult and time-consuming because centralized employee rosters do not exist for every year spanning the scope of the ETDs. Without these rosters, the UNT Library catalogers could not compare employee signatures for proper spelling and identification. The catalogers tried several methods to organize signatures including signature screenshots combined with a spreadsheet of authorized name formats and a Word document that held a table of signature images, departments, dates, and authorized name formats. As our list of names grew, each tool became too unwieldy and required an upgrade. This presentation explains how the catalogers addressed the signature problem by ultimately creating a database with increased functionality in order to organize signatures for easier identification. Participants will learn exactly what database characteristics worked for us, while getting to skip all of our less-successful iterations. They will also be able to apply these ideas for their own needs.

Share

COinS
 

Deciphering Signatures for Improved Discoverability of ETDs

Texas Conference on Institutional Repositories - held at SMU

Ever look at a signature and realize you can’t read the name, even though the letters look almost legible? Now imagine there is not a printed name near that signature. Multiply this issue by 2-4 names per item in a collection of thousands. The University of North Texas Libraries recently ran into this problem when adding metadata to recently-digitized theses and dissertations (ETDs) from the 1930s to 1990s. Deciphering the signatures proved difficult and time-consuming because centralized employee rosters do not exist for every year spanning the scope of the ETDs. Without these rosters, the UNT Library catalogers could not compare employee signatures for proper spelling and identification. The catalogers tried several methods to organize signatures including signature screenshots combined with a spreadsheet of authorized name formats and a Word document that held a table of signature images, departments, dates, and authorized name formats. As our list of names grew, each tool became too unwieldy and required an upgrade. This presentation explains how the catalogers addressed the signature problem by ultimately creating a database with increased functionality in order to organize signatures for easier identification. Participants will learn exactly what database characteristics worked for us, while getting to skip all of our less-successful iterations. They will also be able to apply these ideas for their own needs.

http://scholar.smu.edu/tcir/Presentations/2017/6