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This chapter presents the Trusted Integrated Knowledge Dataspace (TIKD)—a trusted data sharing approach, based on Linked Data technologies, that supports compliance with the General Data Privacy Regulation (GDPR) for personal data handling as part of data security infrastructure for sensitive application environments such as healthcare. State-of-the-art shared dataspaces typically do not consider sensitive data and privacy-aware log records as part of their solutions, defining only how to access data. TIKD complements existing dataspace security approaches through trusted data sharing that includes personal data handling, data privileges, pseudonymization of user activity logging, and privacy-aware data interlinking services. TIKD was implemented on the Access Risk Knowledge (ARK) Platform, a socio-technical risk governance system, and deployed as part of the ARK-Virus Project which aims to govern the risk management of personal protection equipment (PPE) across a group of collaborating healthcare institutions. The ARK Platform was evaluated, both before and after implementing the TIKD, using both the ISO 27001 Gap Analysis Tool (GAT), which determines information security standard compliance, and the ISO 27701 standard for privacy information. The results of the security and privacy evaluations indicated that compliance with ISO 27001 increased from 50% to 85% and compliance with ISO 27701 increased from 64% to 90%. This shows that implementing TIKD provides a trusted data security dataspace with significantly improved compliance with ISO 27001 and ISO 27701 standards to share data in a collaborative environment.

Three key challenges to a whole-system approach to process improvement in health systems are the complexity of socio-technical activity, the capacity to change purposefully, and the consequent capacity to proactively manage and govern the system. The literature on healthcare improvement demonstrates the persistence of these problems. In this project, the Access-Risk-Knowledge (ARK) Platform, which supports the implementation of improvement projects, was deployed across three healthcare organisations to address risk management for the prevention and control of healthcare-associated infections (HCAIs). In each organisation, quality and safety experts initiated an ARK project and participated in a follow-up survey and focus group. The platform was then evaluated against a set of fifteen needs related to complex system transformation. While the results highlighted concerns about the platform’s usability, feedback was generally positive regarding its effectiveness and potential value in supporting HCAI risk management. The ARK Platform addresses the majority of identified needs for system transformation; other needs were validated in the trial or are undergoing development. This trial provided a starting point for a knowledge-based solution to enhance organisational governance and develop shared knowledge through a Community of Practice that will contribute to sustaining and generalising that change.

In this demonstration we present the Access Risk Knowledge (ARK) Platform - a socio-technical risk governance system. Through the ARK Virus Project, the ARK Platform has been extended for risk management of personal protective equipment (PPE) in healthcare settings during the COVID-19 pandemic. ARK demonstrates the benefits of a Semantic Web approach for supporting both the integration and classification of qualitative and quantitative PPE risk data, across multiple healthcare organisations, in order to generate a unique unified evidence base of risk. This evidence base could be used to inform decision making processes regarding PPE use.

By interlinking internal Linked Data (LD) entities to related LD entities published by authoritative creators and holders of data, libraries have the potential to expose their collections to a larger audience and to allow for richer user searches. While increasing numbers libraries are devoting time to publishing LD, the full potential of these datasets has not been explored due to limited LD interlinking. In 2018 we conducted a survey which explored the position of Information Professionals (IPs), such as librarians, archivists and cataloguers, with regards to LD. Results indicated that IPs find the process of data interlinking to be a particularly challenging step in the creation of Five Star LD. Consequently, we developed NAISC, an interlinking approach designed specifically for the library domain aimed at facilitating increased IP engagement in the LD interlinking process. Our paper provides an overview of the design and user-evaluation of NAISC. Results indicated that IPs found NAISC easy-to-use and useful for creating LD interlinks.

In this paper we provide an in-depth analysis of a survey related to Information Professionals (IPs) experiences with Linked Data quality. We discuss and highlight shortcomings in linked data sources following a survey related to the quality issues IPs find when using such sources for their daily tasks such as metadata creation.