Sharing the awesome news from the Collections as Data – Part to Whole site:
✌️ Announcing Collections as Data Cohort 2 ✌️
In late 2018, Collections as Data: Part to Whole was awarded $750,000 by the Andrew W. Mellon Foundation. $600,000 of this award is being regranted, across two cohorts, to foster development of models that support collections as data implementation and use. Cohort 1 activity is nearing completion – be on the lookout for a livestreamed summative forum January 17, 2020 and a full release of all cohort 1 project deliverables by April 2020.
The cohort 2 funding opportunity was reshaped in light of what we learned from cohort 1. We received a number of very strong proposals from across the country and today we are super excited to announce the formation of cohort 2.
Cohort 2 projects come from a range of institutional contexts, grounded by a desire to re-imagine roles and services so that we and users can explore the potential of collections as data. In addition to using regranted funds to pursue their projects, teams will engage in joint developmental activities that culminate in a public facing forum and the release of a series of open resources that aim to advance collections as data work across the cultural heritage community.
Please join us in congratulating these teams!
Thomas Padilla (University of Nevada Las Vegas)
Hannah Scates Kettler (Iowa State University)
Stewart Varner (University of Pennsylvania)
Yasmeen Shorish (James Madison University)
…And 25 of our closest friends: The Louisiana Digital Library as Community-Focused Data
Louisiana State University
Scott Ziegler, Gina Costello, Leah Powell, Elizabeth Joan Kelly
The Louisiana Digital Library (LDL) is a state-wide resource for sharing digital heritage content from public libraries, academic libraries, museums, and archives. Our project enables librarians, archivists, and curators from across Louisiana to gather as a community of practice and explore the policy, practice, and ethics of reconceptualizing the LDL as data. By producing a series of sample collections as data, this project will foster community around a state-wide goal of building computationally meaningful collections that are ethically-grounded and culturally relevant.
Using Newspapers as Data for Collaborative Pedagogy: A Multidisciplinary Interrogation of the Borderlands in Undergraduate Classrooms
University of Arizona
Mary Feeney, Sarah Shreeves, Anita Huizar-Hernández
Using Newspapers as Data for Collaborative Pedagogy: A Multidisciplinary Interrogation of the Borderlands in Undergraduate Classrooms explores how historical newspapers packaged as a single “collection as data” can act as a point of convergence for collaborative pedagogy in the undergraduate classroom. The dataset will include selections from the University of Arizona Libraries’ Historic Mexican and Mexican American Press digital collection and Arizona newspapers digitized for the National Digital Newspaper Program, including Spanish-language newspapers, newspapers of African American communities, and newspapers from predominantly white English-speaking communities, all located within the Southwest during two periods from 1915 to 1922 and 1941 to 1959. Faculty members participating in the project will use newspapers as data to explore topics in their courses in History, Journalism, English, and Spanish and Portuguese during the Fall 2020 semester. The project will culminate in an undergraduate symposium and a white paper with recommendations based on lessons learned.
Images as Data: Processing, Exploration, and Discovery at Scale
Harvard University and University of Richmond
Carol Chiodo, Lidia Uziel, Lauren Tilton, Taylor Arnold
Images as Data will increase the means of access and discovery of born-digital collections of photography and moving images. The project will draw from three born-digital collections of European ephemera from Harvard University Library and two digitized collections from the Harvard Art Museums. These contemporary materials provide unique testimony on political unrest and the culture of protest in Europe, in the context of rising nationalism, anti-immigration movements, globalism and international migration. Through the implementation of computer vision techniques, including the distant viewing framework, the project will provide a model for expanding the processing of digital images and subsequent algorithmic discovery of connections across collections. It will also illustrate how distant viewing can offer a paradigm for addressing the social and ethical challenges of using machine learning with images, particularly of sensitive topics.
LGBTQ+ Audio Archive Mining Project
University of Wisconsin Milwaukee
Ann Hanlon, Dan Siercks, Marcy Bidney, Cary Costello
The UWM Libraries house one of the largest collections of historical and contemporary LGBTQ+ materials in Wisconsin and the Midwest, including a rich record of Milwaukee’s LGBTQ+ communities. The LGBTQ+ Audio Archive Mining Project will use machine learning tools and data analysis and visualization to build and process text datasets extracted from a variety of AV materials in these collections, including collections of oral histories, local television news and radio broadcasts, and early LGBTQ+ community cable programming. The LGBTQ+ Audio Archive Mining Project will aid in better understanding the contents of these collections, and enhance discoverability of previously unrecognized topics, relationships, and patterns that shed light on the history of the LGBTQ+ community in Milwaukee and the Midwest.
Surfacing hidden water data: Water, people, displacement in Southern California
Jeanine Finn, Jessica Dávila Greene, Char Miller
With this grant, the Claremont Colleges Library will bring computational accessibility to the digitized materials in its wide-ranging California Water Documents collection. This collection includes over 13,000 digital files of mixed archival materials, including journals, ledgers, correspondence, field notes, and maps documenting the history of water use in Southern California in the late 19th and early 20th centuries. This rich collection has the potential to surface the histories of the earliest inhabitants of the west (including the Cahuilla and Paiute peoples) who utilized local waterways to those who exploited the First People’s knowledge and labor to build the region’s modern agriculture and urban economy. The project team will collaborate with community partners to attach appropriate indigenous place names, include coordinates for geographic materials, and make PDF and image files fully discoverable and computationally useful.
dLOC as Data: A Thematic Approach to Caribbean Newspapers
Florida International University
Miguel Asencio, Jamie Rogers, Perry Collins, Hadassah St. Hubert
Digital Library of the Caribbean (dLOC) intends to enhance access to its existing Caribbean newspaper collections by making texts available for bulk download to its users. This will facilitate modes of scholarship that depend on access to image and textual data at scale and will enable a new level of access to titles not included in newspaper data resources such as Chronicling America. To meet the needs of the dLOC community for teaching and research, we will demonstrate the potential of newspaper data by creating a pilot thematic tool kit focused on hurricanes and tropical cyclones. The toolkit will provide multilingual datasets focused on these disasters from several countries and islands in the Caribbean, such as the Bahamas, Belize, Cuba, the Dominican Republic, Grenada, Haiti, Jamaica, and Martinique.
Code of Conduct
All project activity, both in person and online, aims to foster a welcoming and inclusive experience for everyone, regardless of gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race, age, religion, nationality, or political beliefs. Harassment of participants will not be tolerated in any form. Harassment includes any behavior that participants find intimidating, hostile or offensive. Participants asked to stop any harassing behavior are expected to comply immediately. Please contact any member of the project team if you have concerns.