A framework for generating aviation risk information mobile user interfaces from knowledge graphs

In this paper, we introduce a new framework called Flight Planner for generating Aviation Risk Information mobile-compatible user interfaces from Knowledge Graphs. The framework is divided into three components, a templating engine, a Linked Data Knowledge Graph and a mobile app.Traditional Linked Data frameworks provide poor support for user interface generation and common web frameworks do not natively support Linked Data-based Knowledge Graphs. Moreover,Aviation Risk Information systems is specialised area mainly studied by organisational psychologists or experts in human factors and it has received little attention by computer scientists.Thus, a flexible, efficient, and usable framework for Aviation Risk Information is needed. A comparative evaluation was done with Linked Data Reactor framework as a benchmark.It is observed that Flight Planner produces equivalently flexible and efficient, but less usable results despite being an early prototype

ARK-Virus: an ARK platform extension for mindful risk governance of personal protective equipment use in healthcare

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

The ARK platform: enabling risk management through semantic web technologies

This paper describes the Access Risk Knowledge (ARK) platform and ontologies for socio-technical risk analysis using the Cube methodology. Linked Data is used in ARK to integrate qualitative clinical risk management data with quantitative operational data and analytics. This required the development of a novel clinical safety management taxonomy to annotate qualitative risk data and make it more amenable to automated analysis. The platform is complemented by other two ontologies that support structured data capture for the Cube sociotechnical analysis methodology developed by organisational psychologists at Trinity College Dublin. The ARK platform development and trials have shown the benefits of a Semantic Web approach to flexibly support data integration, making qualitative data machine readable and building dynamic, high-usability web applications applied to clinical risk management. The main results so far are a self-annotated, standards-based taxonomy for risk and safety management expressed in the W3C’s standard Simple Knowledge Organisation System (SKOS) and a Cube data capture, curation and analysis platform for clinical risk management domain experts. The paper describes the ontologies and their development process, our initial clinical safety management use case and lessons learned from the application of ARK to real-world use cases. This work has shown the potential for using Linked Data to integrate operational and safety data into a unified information space supporting more continuous, adaptive and predictive clinical risk management