Issue 46, 2019-11-05


Sara Amato

If you build it, I’ll probably come.

MatchMarc: A Google Sheets Add-on that uses the WorldCat Search API

Michelle Suranofsky and Lisa McColl

Lehigh University Libraries has developed a new tool for querying WorldCat using the WorldCat Search API.  The tool is a Google Sheet Add-on and is available now via the Google Sheets Add-ons menu under the name “MatchMarc.” The add-on is easily customizable, with no knowledge of coding needed. The tool will return a single “best” OCLC record number, and its bibliographic information for a given ISBN or LCCN, allowing the user to set up and define “best.” Because all of the information, the input, the criteria, and the results exist in the Google Sheets environment, efficient workflows can be developed from this flexible starting point. This article will discuss the development of the add-on, how it works, and future plans for development.

Designing Shareable Tags: Using Google Tag Manager to Share Code

Tabatha Farney

Sharing code between libraries is not a new phenomenon and neither is Google Tag Manager (GTM). GTM launched in 2012 as a JavaScript and HTML manager with the intent of easing the implementation of different analytics trackers and marketing scripts on a website. However, it can be used to load other code using its tag system onto a website. It’s a simple process to export and import tags facilitating the code sharing process without requiring a high degree of coding experience. The entire process involves creating the script tag in GTM, exporting the GTM content into a sharable export file for someone else to import into their library’s GTM container, and finally publishing that imported file to push the code to the website it was designed for. This case study provides an example of designing and sharing a GTM container loaded with advanced Google Analytics configurations such as event tracking and custom dimensions for other libraries using the Summon discovery service. It also discusses processes for designing GTM tags for export, best practices on importing and testing GTM content created by other libraries and concludes with evaluating the pros and cons of encouraging GTM use.

Reporting from the Archives: Better Archival Migration Outcomes with Python and the Google Sheets API

David W. Hodges and Kevin Schlottmann

Columbia University Libraries recently embarked on a multi-phase project to migrate nearly 4,000 records describing over 70,000 linear feet of archival material from disparate sources and formats into ArchivesSpace. This paper discusses tools and methods brought to bear in Phase 2 of this project, which required us to look closely at how to integrate a large number of legacy finding aids into the new system and merge descriptive data that had diverged in myriad ways. Using Python, XSLT, and a widely available if underappreciated resource—the Google Sheets API—archival and technical library staff devised ways to efficiently report data from different sources, and present it in an accessible, user-friendly way,. Responses were then fed back into automated data remediation processes to keep the migration project on track and minimize manual intervention. The scripts and processes developed proved very effective, and moreover, show promise well beyond the ArchivesSpace migration. This paper describes the Python/XSLT/Sheets API processes developed and how they opened a path to move beyond CSV-based reporting with flexible, ad-hoc data interfaces easily adaptable to meet a variety of purposes.

Natural Language Processing in the Humanities: A Case Study in Automated Metadata Enhancement

Erin Wolfe

The Black Book Interactive Project at the University of Kansas (KU) is developing an expanded corpus of novels by African American authors, with an emphasis on lesser known writers and a goal of expanding research in this field. Using a custom metadata schema with an emphasis on race-related elements, each novel is analyzed for a variety of elements such as literary style, targeted content analysis, historical context, and other areas. Librarians at KU have worked to develop a variety of computational text analysis processes designed to assist with specific aspects of this metadata collection, including text mining and natural language processing, automated subject extraction based on word sense disambiguation, harvesting data from Wikidata, and other actions.

“With One Heart”: Agile approaches for developing Concordia and crowdsourcing at the Library of Congress

Meghan Ferriter, Kate Zwaard, Elaine Kamlley, Rosie Storey, Chris Adams, Lauren Algee, Victoria Van Hyning, Jamie Bresner, Abigail Potter, Eileen Jakeway, and David Brunton

In October 2018, the Library of Congress launched its crowdsourcing program By the People. The program is built on Concordia, a transcription and tagging tool developed to power crowdsourced transcription projects. Concordia is open source software designed and developed iteratively at the Library of Congress using Agile methodology and user-centered design. Applying Agile principles allowed us to create a viable product while simultaneously pushing at the boundaries of capability, capacity, and customer satisfaction. In this article, we share more about the process of designing and developing Concordia, including our goals, constraints, successes, and next steps.

Talking Portraits in the Library: Building Interactive Exhibits with an Augmented Reality App

Brandon Patterson

With funding from multiple sources, an augmented-reality application was developed and tested by researchers to increase interactivity for an online exhibit. The study found that augmented reality integration into a library exhibit resulted in increased engagement and improved levels of self-reported enjoyment. The study details the process of the project including describing the methodology used, creating the application, user experience methods, and future considerations for development. The paper highlights software used to develop 3D objects, how to overlay them onto existing exhibit images and added interactivity through movement and audio/video syncing.

Factor Analysis For Librarians in R

Michael Carlozzi

This paper offers a primer in the programming language R for library staff members to perform factor analysis. It presents a brief overview of factor analysis and walks users through the process from downloading the software (R Studio) to performing the actual analysis. It includes limitations and cautions against improper use.

ISSN 1940-5758