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This chapter discusses how digital project management has fundamentally changed the nature of collection service models in university archives and special collections.

Through a conceptual overview of case studies, this chapter examines the establishment of “digital content hubs,” with a special focus on the ways in which a variety of library units share the work of surfacing distinctive collections through cross-functional team-building.

To successfully build “digital content hubs,” academic libraries have embraced a new alignment to incorporate special collections and archives staff, services, and collections more holistically into larger library collecting initiatives and organizational structures. This chapter posits that, through the stewardship of digital projects, archivists and librarians have had to sharpen and expand requisite managerial and technical skills to support “distinctive collection teams” who work cross-functionality with outward-facing approaches to integrated collection building. In addition to embracing assessment tools and diversified funding strategies, archives and special collections have also adopted new collaboration models reliant on centralized but flexible project management structures that emphasize cross-training, complementary subject and technological specializations, and a team-based focus in order to ensure interoperability, sustainability, and broad accessibility of digital collections.

This chapter offers readers a new way of conceptualizing “distinctive collection teams,” proposes some strategies for marshaling resources from across library units, and suggests ways in which librarians and archivists can collaborate on content selection, copyright clearance, metadata creation, and web design and information technology development.

Financial technologies form the heart of considerable disruptive innovation. Fintech is the emerging financial infrastructure for modern business. Big data are the feedstock for artificial intelligence (AI) that drives many fintech sectors – start-up finance, commodities and investment instrumentation, payment systems, currencies, exchange markets/trading platforms, market-failure response forensics, underwriting, syndication, risk assessment, advisory services, banking, financial intermediaries, transaction settlement, corporate disclosure, and decentralized finance. This chapter demonstrates how analyzing big data, largely processed through cloud computing, drives fintech innovations, scholarship, forensics, and public policy. Despite their apparent virtues, some fintech mechanisms can externalize various social costs: flawed designs, opacity/obscurity, social media (SM) influences, cyber(in)security, and other malfunctions. Fintech suffers regulatory lag, the delay following the introduction of novel fintechs and later assessment, development, and deployment of reliable regulatory mechanisms. Big data can improve fintech practices by balancing three key influences: (1) fintech incentives, (2) market failure forensics, and (3) developing balanced public policy resolutions to fintech challenges.

This chapter helps us to understand the staffing and workflow ramifications of Linked Data. A survey of the current state of metadata work, compared to the possibilities and intentions of Linked Data modeling and technology, allows us to make a needs assessment for future planning. Findings are that current trends in metadata work – distributed production alongside centralized management, iterative and collaborative resource description – are appropriate in a Linked Data environment, and should be further cultivated. A plan for training staff on the conceptual modeling of Linked Data is also outlined, together providing a launching pad to begin organizational planning for Linked Data.

The aim of this chapter is to emphasize the importance of archival material and how, despite its secondary nature, it is capable of providing first-hand information for researchers. By providing a variety of examples from tourism, hospitality and leisure, this chapter demonstrates how this underused data can be a valuable resource for these areas of study. In order to illustrate how to use archival material as data, a step-by-step process to analyzing archival photographs is provided. The chapter discusses the challenges and ethical considerations associated with using archival material while also providing suggestions for the use of this data source in future studies.

Purpose – For decades, archivists have been appraising, preserving, and providing access to digital records by using archival theories and methods developed for paper records. However, production and consumption of digital records are informed by social and industrial trends and by computer and data methods that show little or no connection to archival methods. The purpose of this chapter is to reexamine the theories and methods that dominate records practices. The authors believe that this situation calls for a formal articulation of a new transdiscipline, which they call computational archival science (CAS).

Design/Methodology/Approach – After making a case for CAS, the authors present motivating case studies: (1) evolutionary prototyping and computational linguistics; (2) graph analytics, digital humanities, and archival representation; (3) computational finding aids; (4) digital curation; (5) public engagement with (archival) content; (6) authenticity; (7) confluences between archival theory and computational methods: cyberinfrastructure and the records continuum; and (8) spatial and temporal analytics.

Findings – Each case study includes suggestions for incorporating CAS into Master of Library Science (MLS) education in order to better address the needs of today’s MLS graduates looking to employ “traditional” archival principles in conjunction with computational methods. A CAS agenda will require transdisciplinary iSchools and extensive hands-on experience working with cyberinfrastructure to implement archival functions.

Originality/Value – We expect that archival practice will benefit from the development of new tools and techniques that support records and archives professionals in managing and preserving records at scale and that, conversely, computational science will benefit from the consideration and application of archival principles.

In the decades since the founding of the Society of American Archivists (SAA) in 1938, the array of functions considered core to archival work have grown and evolved. In the early years of SAA, the profession was largely focused on issues of collection maintenance, heavily emphasizing preservation as the fundamental mission of the archivist. Yet, at this time, there were archivists calling on their colleagues to engage with audiences outside of the archival reading room. It was not until the social history movements in the 1970s, however, that discussions of outreach as a core function of the archivist's work took hold in the profession. From the 1970s and moving through to today, outreach and proactive engagement with external communities has moved from a peripheral activity of the archivist to one seen as essential to the overall success of an archival program. In this chapter, we examine the evolving discourse surrounding outreach and engagement activities by archivists, focusing on how outreach has been discussed in professional literature. We also explore ways in which this shift in professional perspective is reflected in the work done today by archivists at the University of North Carolina at Greensboro.

Outreach in libraries has traditionally been considered the realm of public services, where librarians interact one-on-one with our patrons at the reference desk, run social media accounts, and other activities of a similar vein. In today's evolving library world, it is time to challenge outreach in its traditional sense and consider technical services work and its associated duties as outreach. This article delves into technical services work (including cataloging, archival processing, shelf maintenance, etc.) and how the results (bibliographic records, metadata, authority control etc.) are in themselves outreach.