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Because of online digital resources, academic libraries no longer need to spend as much time and energy organizing their own collections as they used to. They now have an opportunity to pivot their expertise in organizing information outward. “Inside-out” library services can include support for special collections, digital scholarship, scholarly communication, and data management. A key characteristic of such services is that an academic library takes on broader information management challenges at their college or university. This chapter will examine what it takes to build successful inside-out library services by looking at their cost, how well they complement existing library expertise and culture, and their impact on teaching, research, and the wider community.

This paper aims to explore the accelerations and constraints libraries, archives, museums and heritage organisations (“collections-holding organisations”) face in their role as collection data providers for digital infrastructures. To date, digital infrastructures operate within the cultural heritage domain typically as data aggregation platforms, such as Europeana or Art UK.

Semi-structured interviews with 18 individuals in 8 UK collections-holding organisations and 2 international aggregators.

Discussions about digital infrastructure development often lay great emphasis on questions and problems that are technical and legal in nature. As important as technical and legal matters are, more latent, yet potent challenges exist too. Though less discussed in the literature, collections-holding organisations' capacity to participate in digital infrastructures is dependent on a complex interplay of funding allocation across the sector, divergent traditions of collection description and disciplinaries’ idiosyncrasies. Accordingly, we call for better social-cultural and trans-sectoral (collections-holding organisations, universities and technological providers) understandings of collection data infrastructure development.

The authors recommend developing more understanding of the social-cultural aspects (e.g. disciplinary conventions) and their impact on collection data dissemination. More studies on the impact and opportunities of unified collections for different audiences and collections-holding organisations themselves are required too.

Sustainable financial investment across the heritage sector is required to address the discrepancies between different organisation types in their capacity to deliver collection data. Smaller organisations play a vital role in diversifying the (digital) historical canon, but they often struggle to digitise collections and bring catalogues online in the first place. In addition, investment in existing infrastructures for collection data dissemination and unification is necessary, instead of creating new platforms, with various levels of uptake and longevity. Ongoing investments in collections curation and high-quality cataloguing are prerequisites for a sustainable heritage sector and collection data infrastructures. Investments in the sustainability of infrastructures are not a replacement for research and vice versa.

The authors recommend establishing networks where collections-holding organisations, technology providers and users can communicate their experiences and needs in an ongoing way and influence policy.

To date, the research focus on developing collection data infrastructures has tended to be on the drive to adopt specific technological solutions and copyright licensing practices. This paper offers a critical and holistic analysis of the dispersed experience of collections-holding organisations in their role as data providers for digital infrastructures. The paper contributes to the emerging understanding of the latent factors that make infrastructural endeavours in the heritage sector complex undertakings.

The purpose of this study is to offer a checklist that can be used for both creating and evaluating digital collections, which are also sometimes referred to as data sets as part of the collections as data movement, suitable for computational use.

The checklist was built by synthesising and analysing the results of relevant research literature, articles and studies and the issues and needs obtained in an observational study. The checklist was tested and applied both as a tool for assessing a selection of digital collections made available by galleries, libraries, archives and museums (GLAM) institutions as proof of concept and as a supporting tool for creating collections as data.

Over the past few years, there has been a growing interest in making available digital collections published by GLAM organisations for computational use. Based on previous work, the authors defined a methodology to build a checklist for the publication of Collections as data. The authors’ evaluation showed several examples of applications that can be useful to encourage other institutions to publish their digital collections for computational use.

While some work on making available digital collections suitable for computational use exists, giving particular attention to data quality, planning and experimentation, to the best of the authors’ knowledge, none of the work to date provides an easy-to-follow and robust checklist to publish collection data sets in GLAM institutions. This checklist intends to encourage small- and medium-sized institutions to adopt the collection as data principles in daily workflows following best practices and guidelines.

The purpose of this paper is to suggest an approach to data value considerations that is related to the generalized notion of authenticity and can be applied to the design of preservation policies. There has been considerable progress in the scalable architectures for policy-driven digital collection preservation as well as in modeling preservation costs. However, modeling the value of both digital artifacts and collections seems a more elusive topic that has yet to find a proper methodology and means of expression.

A top-down conceptual analysis was developed and the principles of information technology service management and quality management were applied to the domain of digital preservation. Then, in a bottom-up analysis, the various notions of authenticity in digital preservation projects, reference models and conceptual papers were reviewed.

The top-down and bottom-up analyses have a meeting point, establishing a close relation between the concepts of data authenticity and data value.

The generalized understanding of authenticity can support the design of sensible preservation policies and their application to the formation and long-term maintenance of digital collections.

This paper describes the unintended and unanticipated ways an iPhone as a data collection tool created distractions during observations of five-year-old twins' digital literacy practices while in their home.

Situated in sociocultural theories of learning and development and new literacy studies, the 12-month-long case study examined young children's digital literacy practices in their homes before and during their transition into kindergarten. The article focuses on the data collection of five-year-old twins in their home with their parents, a family the author called the Skywalkers. Data sources included semistructured interviews, participant observations and informal conversations.

The mother was a low-technology user and preferred her children to engage in nondigital activities. The children were permitted 10 min every other day of “digital time.” The iPhone as a data collection tool provided them with digital access they would otherwise not have. The mother knew the focus of the study was digital engagement and that the iPhone was used for data collection (i.e. photographs and videos). Although the iPhone was intended to be used in establishing rapport and taking photographs, the children frequently asked to video record their play and therefore the iPhone became a distraction.

Given the prevalence of smartphones in Western society, the recruitment of a family with such low-technology use was unforeseen. As digital data collection increases in qualitative research, researchers should not assume that a smartphone is always appropriate for gathering photographic data. This is particularly important when investigating digital literacy practices of families in their homes.

The purpose of this paper is to consider how digital preservation system architectures will support business analysis of large-scale collections of preserved resources, and the use of Big Data analyses by future researchers.

This paper reviews the architecture of existing systems, then discusses experimental surveys of large digital collections using existing digital preservation tools at Big Data scales. Finally, it introduces the design of a proposed new architecture to work with Big Data volumes of preserved digital resources – also based upon experience of managing a collection of 30 million digital images.

Modern visualisation tools enable business analyses based on file-related metadata, but most currently available systems need more of this functionality “out-of-the-box”. Scalability of preservation architecture to Big Data volumes depends upon the ability to run preservation processes in parallel, so indexes that enable effective sub-division of collections are vital. Not all processes scale easily: those that do not require complex management.

The complexities caused by scaling up to Big Data volumes can be seen as being at odds with preservation, where simplicity matters. However, the sustainability of preservation systems relates directly to their usefulness, and maintaining usefulness will increasingly depend upon being able to process digital resources at Big Data volumes. An effective balance between these conflicting situations must be struck.

Preservation systems are at a step-change as they move to Big Data scale architectures and respond to more technical research processes. This paper is a timely illustration of the state of play at this pivotal moment.

Digital trace data provide new opportunities to study how individuals act and interact with others online. One advantage of this type of data is that it measures behavior in a less obtrusive way than surveys, potentially reducing measurement error. However, it is well documented that in observational studies, participants' awareness of being observed can change their behavior, especially when the behavior is considered sensitive. Very little is known regarding this effect in the online realm. Against this background, we studied whether people change their online behavior because digital trace data are being collected.

We analyzed data from a sample of 1,959 members of a German online panel who had consented to the collection of digital trace data about their online browsing and/or mobile app usage. To identify reactivity, we studied change over time in five types of sensitive online behavior.

We found that the frequency and duration with which individuals engage in sensitive behaviors online gradually increases during the first couple of days after the installation of a tracker, mainly individuals who extensively engage in sensitive behavior show this pattern of increase after installation and this change in behavior is limited to certain types of sensitive online behavior.

There is an increased interest in the use of digital trace data in the social sciences and our study is one of the first methodological contributions measuring reactivity in digital trace data measurement.

Upcycling is conceptualised as a digital historical research practice aimed at increasing the scientific value of historical data collections produced in print or in electronic form between the eighteenth and the late twentieth centuries. The concept of upcycling facilitates data rescue and reuse as well as the study of information creation processes deployed by previous generations of researchers.

Based on a selection of two historical reference works and two legacy collections, an upcycling workflow consisting of three parts (input, processing and documentation and output) is developed. The workflow facilitates the study of historical information creation processes based on paradata analysis and targets the cognitive processes that precede and accompany the creation of historical data collections.

The proposed upcycling workflow furthers the understanding of computational methods and their role in historical research. Through its focus on the information creation processes that precede and accompany historical research, the upcycling workflow contributes to historical data criticism and digital hermeneutics.

Many historical data collections produced between the eighteenth and the late twentieth century do not comply with the principles of FAIR data. The paper argues that ignoring the work of previous generations of researchers is not an option, because it would make current research practices more vulnerable and would result in losing access to the experiences and knowledge accumulated by previous generations of scientists. The proposed upcycling workflow takes historical data collections seriously and makes them available for future generations of researchers.

The terms “digital curation” and “cyberinfrastructure” have been coined in the last decade to describe distinct but related concepts of how data can be managed, preserved, manipulated and made available for long‐term use. This paper aims to examine these.

The paper considers the origins of both terms and the communities that have been engaged with each of them, traces the development of the present digital environment in the USA and considers what this may mean for the future.

The paper reveals that each term has important attributes that contribute to a comprehensive understanding of the digital knowledge universe.

The paper reveals information about the development of digital preservation.

The purpose of this paper is to determine whether TAMS Analyzer and Viewshare are viable free and open source software data sharing and creation tools for those with limited funding and technological skills.

The participant observer method was used to collect experiential evidence while applying the tools to a collection of text-, image-, and video-based digital cultural records.

TAMS Analyzer was found to be a low barrier to entry tool for those with coding and qualitative data analysis experience. Those with general experience will be able to create datasets with the support of manuals and tutorials, while those with limited experience may find it difficult to use. Viewshare was found to be a low barrier to entry tool for sharing data online, and accessible for all skill levels.

TAMS Analyzer supports Mac and Linux platforms only, so a low-cost software recommendation was made for those in Windows environments.

Librarians can use these tools to address data access gaps while promoting library digital collections.

With a greater understanding of data tools, librarians can be advisors, collaborators, agents for data culture, and relevant participants in digital humanities scholarship.

The research evaluates both the capabilities of the tools and the barriers to using or accessing them, which are often neglected. The paper addresses a need in the literature for greater scrutiny of tools that are a critical component of the data ecology, and will further assist librarians when connecting scholars to tools of inquiry in an environment with limited funding and technical support.