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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.

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.

Purpose – The integration of librarians and technologists to deliver information services represents a new and costly organizational challenge for many library administrators. To understand how to control the costs of integration, this study uses structural contingency theory to study the coordination of librarians and technologists within the information commons.

Design/methodology/approach – This study tests the structural contingency theory expectation that an organization will achieve higher levels of performance when there is a positive relationship between the degree of workflow interdependence and the complexity of coordinative structures necessary to integrate these workflows. This expectation was tested by (a) identifying and collecting a sample of information common; (b) developing and validating survey instruments to test the proposition; and (c) quantitatively analyzing the data to test the proposed contingency theory relationship.

Findings – The contingency theory expectations were confirmed by finding both a positive relationship between coordination and interdependence and a positive relationship between perceptions of performance and degree of congruency between interdependence and coordination.

Limitations – The findings of this study are limited to both the context of an information common and the structures tested. Future research should seek to both broaden the context in which these findings are applicable, and test additional structural relationships as proposed by contingency theory

Practical implications – This study contributes to the library profession in a number of ways. First, it suggests that managers can improve IC performance by matching coordination structures to the degree of interdependence. For instance, when librarians and technologists are strictly co-located, managers should coordinate workflows using less resource-intensive policies rather than meetings. Second, the instruments developed in this study will improve the library manager's ability to measure and report unit interdependence and coordination in a valid and reliable manner. Lastly, it also contributes to the study of structural contingency theory by presenting one of the first empirical confirmations of a positive relationship between interdependence and coordination.

Originality/value – This study represents one of the first empirical confirmations of the structural contingency theory expectations of both a positive relationship between workflow interdependence and coordination, and a positive relationship between performance and coordination's fit to workflow interdependence. These findings are of value to both organizational theorists and to administrators of information commons.

The interaction of systems through a designated control channel has improved communication, efficiency, management, storage, processing, etc. across several industries. The construction industry is an industry that thrives on a well-planned workflow rhythm; a change in the environmental dynamism will either have a positive or negative impact on the output of the project planned for execution. More so, raising the need for effective collaboration through workflow and project planning, grid application in construction facilitates the relationship between the project reality and the end users, all with the aim of improving resources and value management. However, decentralisation of close-domain control can cause uncertainty and incompleteness of data. And this can be a big factor, especially when a complex project is being executed.

In this chapter, I argue, contrary to some current views, that workflow process mapping can be an important and relevant tool for assessing and improving the effectiveness and efficiency of library Technical Services departments. I also propose that linking workflow process mapping to the “High Performance” style of organizational management of W. Edwards Deming underlines both the value of process mapping and how the latter can obviate the need for hierarchical managerial control, by building a cohesive and efficient technical services team. First, I describe the “High Performance” management style of Deming, focusing in particular on what is generally called the “Deming Cycle.” Second, I describe the process of mapping workflows and emphasize its value for highlighting waste, improving existing processes, and maintaining sustainability. Third, I argue that linking workflow mapping to this larger understanding of management style results in several positive consequences for technical services departments, such as a team-based rather than hierarchical style of management, increased departmental and interdepartmental effectiveness and efficiency, and a better return on investment. I illustrate these points by looking directly at an example of an acquisitions department.

Predictive analytics is the science of decision-making that eliminates guesswork out of the decision-making process and applies proven scientific procedures to find right solutions. Predictive analytics provides ideas on the occurrences of future downtimes and rejections thereby aids in taking preventive actions before abnormalities occur. Considering these advantages, predictive analytics is adopted in various diverse fields such as health care, finance, education, marketing, automotive, etc. Predictive analytics tools can be used to predict various behaviors and patterns, thereby saving the time and money of its users. Many open-source predictive analysis tools namely R, scikit-learn, Konstanz Information Miner (KNIME), Orange, RapidMiner, Waikato Environment for Knowledge Analysis (WEKA), etc. are freely available for the users. This chapter aims to reveal the best accurate tools and techniques for the classification task that aid in decision-making. Our experimental results show that no specific tool provides the best results in all scenarios; rather it depends upon the datasets and the classifier.

Project management techniques for digital initiatives must shift with the transformation of content from analog to digital, from singular projects to mass-digitization and large-scale digital preservation. How are project management methods employed across digital practices, from digitization, to online access, to preservation? How can project management methods evolve to create a collaborative workflow across collection and service areas of librarianship, centered on digital stewardship?

Solutions for these questions are illustrated in an explanation of the workflows implemented at the University of Maryland, College Park Libraries and reflected upon in a case study of a recent digital initiative.

Centered on the efforts of two departments in the Libraries’ Digital Systems and Stewardship division, this chapter outlines the origins, techniques, and integration of digital project management with a focus on Waterfall and Agile project management. Furthermore, the integration and transition of project management methodologies and tools between groups is emphasized, mirroring the transformation of analog media to digital formats and the requisite shifts in thinking such projects require.

These case studies are based on research across the profession and implementation at the University of Maryland, College Park Libraries. The local application of two established project management techniques, Waterfall and Agile, are summarized and compared. Though regularly employed in application development, applying Agile project management in libraries is a relatively new practice and has not been widely documented in library literature.