Toward an Interactive Directory for Norfolk, Nebraska: 1899-1900

We describe steps toward an interactive directory for the town of Norfolk, Nebraska for the years 1899 and 1900. This directory would extend the traditional city directory by including a wider range of entities being described, much richer information about the entities mentioned and linkages to mentions of the entities in material such as digitized historical newspapers. Such a directory would be useful to readers who browse the historical newspapers by providing structured summaries of the entities mentioned. We describe the occurrence of entities in two years of the Norfolk Weekly News, focusing on several individuals to better understand the types of information which can be gleaned from historical newspapers and other historical materials. We also describe a prototype program which coordinates information about entities from the traditional city directories, the federal census, and from newspapers. We discuss the structured coding for these entities, noting that richer coding would increasingly include descriptions of events and scenarios. We propose that rich content about individuals and communities could eventually be modeled with agents and woven into historical narratives

Increasing Our Vision for 21st-Century Digital Libraries

This presentation Reads digital library interfaces—or their main door interfaces—as glimpses into what we have thus far valued in the development of digital libraries Frames a visual way of thinking about textual materials Introduces the work of our research team—where we are now, and where we\u27re headed Draws some connections between the parts This presentation is very much a look into thinking in process and work in progress and proposes the following ideas: As a community, we can do much more with the digital images we\u27re creating of textual materials than we\u27ve heretofore done. We aspire to have additional layers or levels of image analysis become part of the default processing work in the creation of digital libraries, not only as something that happens external or parallel to digital libraries, and not only toward the purpose of generating text. We aspire to more processing up front and iterative processing of materials—so that digital libraries\u27 materials are not once and done —and that this more processing is presented to users as additional options for how they can explore digital libraries, find materials of relevance, and imagine new possibilities Even as the digital libraries community focuses on supporting computational use of digital libraries—and our research team recognizes that our project very much depends on that computational use being supported—we should not leave behind, in 1998, those users of digital libraries for whom computational use is not their point of entry. (More on that date in a moment.

Toward an Interactive Directory for Norfolk, Nebraska: 1899-1900

We describe steps toward an interactive directory for the town of Norfolk, Nebraska for the years 1899 and 1900. This directory would extend the traditional city directory by including a wider range of entities being described, much richer information about the entities mentioned and linkages to mentions of the entities in material such as digitized historical newspapers. Such a directory would be useful to readers who browse the historical newspapers by providing structured summaries of the entities mentioned. We describe the occurrence of entities in two years of the Norfolk Weekly News, focusing on several individuals to better understand the types of information which can be gleaned from historical newspapers and other historical materials. We also describe a prototype program which coordinates information about entities from the traditional city directories, the federal census, and from newspapers. We discuss the structured coding for these entities, noting that richer coding would increasingly include descriptions of events and scenarios. We propose that rich content about individuals and communities could eventually be modeled with agents and woven into historical narratives

Digital Libraries, Intelligent Data Analytics, and Augmented Description: A Demonstration Project

From July 16-to November 8, 2019, the Aida digital libraries research team at the University of Nebraska-Lincoln collaborated with the Library of Congress on “Digital Libraries, Intelligent Data Analytics, and Augmented Description: A Demonstration Project.“ This demonstration project sought to (1) develop and investigate the viability and feasibility of textual and image-based data analytics approaches to support and facilitate discovery; (2) understand technical tools and requirements for the Library of Congress to improve access and discovery of its digital collections; and (3) enable the Library of Congress to plan for future possibilities. In pursuit of these goals, we focused our work around two areas: extracting and foregrounding visual content from Chronicling America (chroniclingamerica.loc.gov) and applying a series of image processing and machine learning methods to minimally processed manuscript collections featured in By the People (crowd.loc.gov). We undertook a series of explorations and investigated a range of issues and challenges related to machine learning and the Library’s collections. This final report details the explorations, addresses social and technical challenges with regard to the explorations and that are critical context for the development of machine learning in the cultural heritage sector, and makes several recommendations to the Library of Congress as it plans for future possibilities. We propose two top-level recommendations. First, the Library should focus the weight of its machine learning efforts and energies on social and technical infrastructures for the development of machine learning in cultural heritage organizations, research libraries, and digital libraries. Second, we recommend that the Library invest in continued, ongoing, intentional explorations and investigations of particular machine learning applications to its collections. Both of these top-level recommendations map to the three goals of the Library’s 2019 digital strategy. Within each top-level recommendation, we offer three more concrete, short- and medium-term recommendations. They include, under social and technical infrastructures: (1) Develop a statement of values or principles that will guide how the Library of Congress pursues the use, application, and development of machine learning for cultural heritage. (2) Create and scope a machine learning roadmap for the Library that looks both internally to the Library of Congress and its needs and goals and externally to the larger cultural heritage and other research communities. (3) Focus efforts on developing ground truth sets and benchmarking data and making these easily available. Nested under the recommendation to support ongoing explorations and investigations, we recommend that the Library: (4) Join the Library of Congress’s emergent efforts in machine learning with its existing expertise and leadership in crowdsourcing. Combine these areas as “informed crowdsourcing” as appropriate. (5) Sponsor challenges for teams to create additional metadata for digital collections in the Library of Congress. As part of these challenges, require teams to engage across a range of social and technical questions and problem areas. (6) Continue to create and support opportunities for researchers to partner in substantive ways with the Library of Congress on machine learning explorations. Each of these recommendations speak to the investigation and challenge areas identified by Thomas Padilla in Responsible Operations: Data Science, Machine Learning, and AI in Libraries. This demonstration project—via its explorations, discussion, and recommendations—shows the potential of machine learning toward a variety of goals and use cases, and it argues that the technology itself will not be the hardest part of this work. The hardest part will be the myriad challenges to undertaking this work in ways that are socially and culturally responsible, while also upholding responsibility to make the Library of Congress’s materials available in timely and accessible ways. Fortunately, the Library of Congress is in a remarkable position to advance machine learning for cultural heritage organizations, through its size, the diversity of its collections, and its commitment to digital strategy

Cultural Heritage Information: Artefacts and Digitization Technologies

Since the 1970s, the gallery, library, archive, and museum sector has promoted and encouraged digitization - the conversion of analog into digital information - to increase access to cultural heritage material through various incarnations of digital media. Indeed, it is now expected by both users and professionals that institutions should be undertaking digitization programs, and best practices in this area are now well documented and understood. This chapter scopes out the background to the current digitization environment, giving an overview of the methods and approaches involved. It points to current developments, highlighting the use of both two and three dimensional capture methods for the creation of digital surrogates of objects and artefacts, indicating the potential for further development in the sector, whilst drawing attention to current issues faced when digitizing objects and artefacts including cost, sustainability, impact evaluation, and expectation management in the changing information environment. The affordances of previously prohibitively expensive techniques – such as multi-spectral imaging and 3D scanning – are now available at relatively inexpensive rates, which also raises questions about digital literacy and our understanding of what it means, for both the end user and information professional, to create digital versions of our cultural inheritance

Supporting Research in Area Studies: a guide for academic libraries

The study of other countries or regions of the world often crosses traditional disciplinary boundaries in the humanities and social sciences. Supporting Research in Area Studies is a comprehensive guide for academic libraries supporting these communities of researchers. This book explores the specialist requirements of these researchers in information resources, resource discovery tools, and information skills, and the challenges of working with materials in multiple languages. It makes the case that by adapting their systems and procedures to meet these needs, academic libraries find themselves better placed to support their institution's�� international agenda more widely. The first four chapters cover the academic landscape and its history, area studies librarianship and acquisitions. Subsequent chapters discuss collections management, digital products, and the digital humanities, and their role in academic projects. The final chapter explores information skills and the various disciplinary skills that facilitate the needs of researchers during their careers