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This is a case study on the opportunities provided by Open Source library systems and the experience of delivering these systems through a shared service.

This chapter derives from desk research, interviews, and direct involvement in the project. The format is a case study, setting out a detailed timeline of events with information that can be applied in other settings.

This chapter presents reflections on the value and limitations of collaboration amongst libraries and librarians on an innovative approach to library systems and technologies. It also presents reflections on lessons learned from the processes and detailed discussion of the success factors for shared services and the reasons why such initiatives may not result in the outcomes predicted at the start.

Libraries and IT services considering Open Source and shared service approaches to provision will find material in this study useful when planning their projects.

The nature of collaboration and collaborative working is studied and observations made about the way that outcomes cannot always be predicted or controlled. In a genuine collaboration, the outcome is determined by the interactions between the partners and is unique to the specifics of that collaboration.

The case study derives from interviews, written material and direct observation not generally in the public domain, providing a strong insider’s view of the activity.

This chapter explores the different ways we share our research. The ways in which we are productive, again, help shape the tools in which productivity occurs. Archiving, storing, and sharing are crucial within the field of digital humanities and offer interesting perspectives on how we as humans share information with one another. The focus in this chapter is also on specific tools like timelines, e-portfolios, and the new generation of presentation applications.

Information overload is a norm in the era of big data. The threats and opportunities presented to organizations, institutions, and individuals have only increased in their volume and velocity. This chapter looks at how an individual’s scanning of environmental and external information is affected by bias. The term subscriber or subscription bias is introduced. Tools for increasing the speed of processing large new data relationships through visualization are evaluated. Additionally, the role and benefit of Cognitive Analytics in presenting fresh insight, as well as its role in mitigating publication and other biases, is reviewed. Last, some of the networked world tools and web services available to researchers and practitioners are considered in terms of how these emerging offerings can enhance productivity and their human capital with reusability of data and reproducibility of results.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.

Digital technologies provide an opportunity for the rail sector to achieve social, economic and environmental sustainability, if implemented correctly. Unlocking the full potential of technology, however, will require significant changes beyond the technological. Physical assets will need to link with digital assets, making best use of data, simulation and modelling. Transformational leadership informed by systems engineering will be necessary to deliver the change process required to innovate across the whole railway life cycle. Each of these digital railway elements – technology, data, simulation, transformational leadership and systems engineering – presents challenges to be overcome. The authors believe that by instilling core values alongside technical expertise, by being open, resilient, responsive, customer-centric and valuing people, the digital railway has the power to transform the sector. It will enable improved railway processes; safer, faster and more reliable trains; better customer experience; cost-effectiveness; and reduced carbon emissions and more. The digital railway will not just realise the current vision but form the foundation for a sustainable railway to meet changing mobility needs well beyond 2050.