Reading Critically from the Archives: James Merrill Linn’s Diary as a Gateway to the Past

Archival research and reading from the archives have long been embraced as a scholarly research practice in humanities disciplines. While scholars may spend weeks or months poring over hidden treasures found in archives, undergraduate students are often not exposed to these materials in a hands-on way. However, college and university libraries often have archival collections tucked away that can facilitate learning when used in thoughtfully crafted assignments. In this chapter, we discuss how we used Text Encoding Initiative (TEI) and archival materials to provide students with an opportunity to engage in a close and critical reading of excerpts from the Civil War era diary of James Merrill Linn

Collaborating on Machine Reading: Training Algorithms to Read Complex Collections

Interdisciplinary collaboration between two faculty members in the humanities and computer science, a research librarian, and an undergraduate student has led to remarkable results in an ongoing international DH research project that has at its core 18th century manuscripts. The corpus stems from a vast collection of archival materials held by the Moravian Church in the UK, Germany, and the US. The number of pages to be transcribed, differences in handwriting styles, paper quality, and original language pose enormous problems for the feasibility of human transcription. This presentation will review the hypothesis, process, and findings of a summer research project that builds upon the Transkribus (Transkribus.eu) platform and seeks to refine the process for creating handwriting training recognition (HTR) models to further improve accuracy. An undergraduate student working with a faculty member in computer science developed a deep learning model to help overcome challenges of accuracy in computer transcription

Bridging Communities of Practice: Cross-Institutional Collaboration for Undergraduate Digital Scholars

At Bucknell University and Gettysburg College, an increasing focus on supporting creative undergraduate research as intensive, high-impact experiences has resulted in both institutions implementing library-led digital scholarship fellowships for their students. Gettysburg’s Digital Scholarship Summer Fellowship began in 2016, and Bucknell’s Digital Scholarship Summer Research Fellowship in 2017. While academic libraries have emerged as leaders on college campuses for digital humanities (DH) services, the programs at Gettysburg and Bucknell are distinctive in their structured curricula, a focus on independent student research, and the development of a local community of practice. In this chapter, we explore the development of cross-institutional communities of practice grounded in the digital humanities, and the ways in which we brought students in our two programs together

Enhancing Subject Access to Materials in Library OPACs: Are Folksonomies the Answer?

This research will examine a given set of books and compare their LibraryThing folksonomic tags with their assigned Library of Congress Subject Headings. In particular, I am looking for commonalities and differences in the ways in which these subject languages describe the materials to which they are applied. Can folksonomies be used to enhance subject access to materials in library catalogs? What does user tagging tell us about the way that people think about the subjects of a book? In an information environment where students are so attuned to keyword and Google-style searching, does the application of folksonomic tags increase the findability of library materials

Using Tags to Improve Findability in Library OPACs: A Usability Study of LibraryThing for Libraries

Library of Congress Subject Headings (LCSH), one of the standard descriptive languages used in library catalogs, are often criticized for their lack of currency, biased language, and atypical syndetic structure. Conversely, folksonomies, which rely on the natural language of their users, offer a flexibility often lacking in controlled vocabularies and as such may offer an alternative to or a means of augmenting more rigid controlled vocabularies such as LCSH. Content analysis studies have already demonstrated the potential for folksonomies to be used as a means of enhancing subject access to materials. Despite a sizable number of libraries now using the LibraryThing for Libraries catalog enhancements, and the development by some libraries of their own tagging systems (e.g., PennTags, MTagger), little research has been undertaken to determine the effectiveness of folksonomies as a means of enhancing item discovery in library catalogs. This project examines the utility of folksonomies as a means of enhancing subject access to materials in library OPACs through usability testing with the LibraryThing for Libraries catalog enhancements. Initial findings from the usability test indicate that while they cannot replace LCSH, folksonomies do show promise for aiding information seeking in OPACs. Overall, participants indicated that folksonomies could be useful for surveying broad subject areas or for exploring materials in a topic area with which the user is not familiar, while subject headings remained the preferred access mechanism for information seeking that is tied to more focused research. In the context of information systems design, the study revealed that while folksonomies have the potential to enhance subject access to materials, that potential is severely limited by the current inability of catalog interfaces to support tag-based searches alongside standard catalog searches.unpublishednot peer reviewe

2016 Primary Election and Caucus Data

The data contained in this dataset cover the 2016 Presidential Primary and Caucus election season. Results are reported for Democratic and Republican candidates only. Data were sourced from finalized (certified) state election board results wherever possible. All data is reported at the county level unless otherwise noted. Refer to the 2016 Primary Election Data Sources document for a full list of data sources. Results for Alaska, Colorado (Democratic only), Hawaii, Iowa, Maine, Minnesota, and Washington state are for these states caucuses. The vote totals reported are raw numbers of votes. Data for North Dakota, Utah, and Wyoming is not included in this dataset, due to the inability to find complete results for these states

Using ACS data to study the 2016 election in the classroom: A case study from Bucknell University

Presenting complex data to an audience which is unfamiliar with the intricacies of data acquisition and management is a challenge for many professionals. Education faculty and staff are no different. Staff at Bucknell University library were approached in 2015 by a faculty member from the economics department for assistance with a class on economic history. The syllabus called for the class to analyze and map the development of the 2016 presidential campaign. Through the course of this project data was gathered from multiple sources, including the American Community Survey. Tools such as ArcGIS, R, and the American FactFinder were integrated into the class, but finding an appropriate balance between self-directed student exploration and expert curation was a challenge. The time constraints of the classroom only allowed for a limited introduction to the nuances of data from disparate sources. This paper will present a case study of the difficulties faced when trying to incorporate data from the ACS into undergraduate education. It will address questions on 1. How different tools can be used to present data to students and which tools can be used by students to perform their own exploratory data analysis? 2. How different data sources can be integrated to further the mission of college education? and 3. the challenges of teaching data literacy to an undergraduate population