University College Dublin (UCD)

Open Access Risk Knowledge (OpenARK) Project

The project

Introduction

The ARK platform will deliver evidence-based risk management capabilities to operational, project and strategic levels within organisations. The project will develop the ARK risk governance platform, using a common analytic framework that provides the basis for the following:

  • Mixed method risk analysis, leveraging statistical methods, Artificial Intelligence (knowledge graphs, ontological inference, machine learning, natural language processing) and qualitative analysis to provide a comprehensive and reliable risk pattern, informing decisions of operations crew.
  • Combination of multiple cases to create a practical improvement agenda which is supported and tracked through its phases, verifying outcomes.
  • Analysis of risk interactions across business units and projects provides a strategic risk capability linking strategic threats to operational readiness.

This will make it possible to develop evidence-based best practice that supports performance-based regulation and will ultimately provide an operational basis for future system design. The ARK solution transforms risk management from quantifying loss to proactive governance, assuring reliable transactional value from operations, ensuring this is sustainable across the enterprise, potentially massively enhancing value through effective future system innovation.

ARK-Virus

The ARK-Virus Project extends the ARK Platform for use in the healthcare domain - specifically for the risk governance of personal protective equipment (PPE) use for infection prevention and control (IPC) during the COVID-19 pandemic. The project is a collaboration between the ARK academic team and a community of practice (CoP) which includes safety staff in St. James's Hospital, Beacon Renal, and Dublin Fire Brigade.

Acknowledgements

This research was conducted with the financial support of Taighde Éireann – Research Ireland under Grant Agreement No. 20/COV/8463 at the ADAPT Centre in Dublin City University and Trinity College Dublin, and through the Enterprise Ireland Commercialisation Fund (CF 2018-1012) and co-funded by the European Regional Development Fund (ERDF) under Ireland's European Structural and Investment Funds Programme 2014-2020. The ADAPT Taighde Éireann – Research Ireland Centre for Digital Content Technology is funded by Science Foundation Ireland through the Taighde Éireann – Research Ireland Research Centres Programme and is co-funded under the European Regional Development Fund (ERDF) through Grant #13/RC/2106_P2.

Team

People

University College Dublin (UCD)

  • Asst. Prof. Rob Brennan
  • Junli Liang
  • Malick Ebiele
  • Huan Chen
  • Sajjad Karimian
  • Haula Galadima

Trinity College Dublin (TCD)

  • Prof. Nick McDonald
  • Paula Hicks

ARK Partners

  • St. James's Hospital
  • Dublin Fire Brigade
  • Beacon Renal
  • Dr. Julio Hernandez
  • Dr. Lucy McKenna
  • Dr. Ademar Crotti Junior
  • Dr. Yalemisew Abgaz
  • Dr. Daniele Baranzini
  • Mischa Heeb
  • Maryam Basereh
  • Rebecca Vining
  • Brian Doyle
  • Pallavi Prakash
  • Lucie Andrieu
  • Luke Derwin
  • Max Aedo-Espicto
  • Natalia Duda
  • Carlotta Acconito
  • Maÿlis Laporte

Semantic Web

ARK Ontologies

The ARK ontologies include several modules that are currently under development. The major modules include:

Application

ARK Platform

The Access Risk Knowledge (ARK) Platform is a mindful risk-governance system that uses Semantic Web technologies to model, integrate and classify risk data, from both qualitative and quantitative sources, into a unified risk graph.

Open the ARK Platform app

Please contact the team to get access to the application (rob.brennan@ucd.ie).

Application

ARK Evidence

ARK Evidence, built using CKAN, is a catalogue of evidence data that can be interlinked with risk management projects on the ARK Platform. ARK Evidence can be used to publish and share data, such as Personal Protective Equipment (PPE) compliance data, Infection Prevention and Control (IPC) data or other healthcare risk data, which can be used as supportive evidence on the ARK Platform.

Open ARK Evidence app

Please contact the team to get access to the application (rob.brennan@ucd.ie).

Learn

ARK Training

View the videos below to learn more about how to use the ARK Platform and ARK Evidence applications.

Research

Publications

  • 2022

    ARK Virus: Access Risk Knowledge Platform for Mindful Governance of Infection Prevention and Control Risk. Final Stakeholder Report. May, 2022.

  • 2022

    McDonald, N., and Ward, M.E. (2022). Building accountability and trust into healthcare risk management. European Conference on Safety and Reliability (ESREL) 2022.

  • 2022

    Vining, R., McDonald, N., McKenna, L., Ward, M.E., Doyle, B., Liang, J., Hernandez, J., Guilfoyle, J., Shuhaiber, A., Geary, U., Fogarty, M., and Brennan, R. (2022). Developing a Framework for Trustworthy AI-Supported Knowledge Management in the Governance of Risk and Change. Human Computer Interaction International (HCII) 2022.

  • 2024

    Galadima, H. S., Doherty, C., McDonald, N., Liang, J., & Brennan, R. (2024). Evaluating incident response in CSIRTs using Cube socio-technical systems analysis. Computer Standards & Interfaces, 88, 103970.

  • 2022

    Hernandez, J., McKenna, L., Brennan, R. (2022). TIKD: A Trusted Integrated Knowledge Dataspace for Sensitive Data Sharing and Collaboration. In: Curry, E., Scerri, S., Tuikka, T. (eds) Data Spaces. Springer, Cham.

  • 2021

    ARK Virus: Access Risk Knowledge Platform for Mindful Governance of PPE for Virus Infection Prevention and Control. Stakeholder Report. December, 2021.

  • 2021

    McDonald, N., McKenna, L., Vining, R., Doyle, B., Liang, J., Ward, M.E., Ulfvengren, P., Geary, U., Guilfoyle, J., Shuhaiber, A., Hernandez, J., Fogarty, M., Healy, U., Tallon, C., and Brennan, R. (2021). Evaluation of an Access-Risk-Knowledge (ARK) Platform for Governance of Risk and Change in Complex Socio-Technical Systems. International Journal of Environmental Research and Public Health. 2021; 18(23):12572.

  • 2021

    McKenna, L., Liang, J., Duda, N., McDonald, N., and Brennan, R. (2021). ARK-Virus: An ARK Platform Extension for Mindful Risk Governance of Personal Protective Equipment Use in Healthcare. In Companion Proceedings of the Web Conference 2021 (WWW '21). Association for Computing Machinery, New York, NY, USA, 698–700.

  • 2021

    Hernandez, J., McKenna, L. and Brennan, R. (2021). TIKD: A Trusted Integrated Knowledge Dataspace For Sensitive Healthcare Data Sharing. In IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 1855-1860.

  • 2020

    Junior, A. C., Basereh, M., Abgaz, Y., Liang, J., Duda, N., McDonald, N., and Brennan, R. (2020). The ARK Platform: Enabling Risk Management through Semantic Web Technologies. In 11th International Conference on Biomedical Ontologies (ICBO 2020) joint with the 10th Workshop on Ontologies and Data in Life Sciences (ODLS) and part of the Bolzano Summer of Knowledge (BoSK 2020), Bolzano, Italy, 2807.

  • 2024

    Ward, M. E., Geary, U., Brennan, R., Vining, R., McKenna, L., O'Connell, B., Bergin, C., Byrne, D., Creagh, D., Fogarty, M., Healy, U., McDonald, G., Ebiele, M., Crane, M., Pham, M. K., Bendechache, M., Bezbradica, M., Liang, J., Doyle, B., Guilfoyle, J., … McDonald, N. (2025). A systems approach to managing the risk of healthcare acquired infection in an acute hospital setting supported by human factors ergonomics, data science, data governance and AI. Ergonomics, 68(8), 1239–1259.

  • 2024

    Pham, M.-K.; Mai, T.T.; Crane, M.; Ebiele, M.; Brennan, R.; Ward, M.E.; Geary, U.; McDonald, N.; Bezbradica, M. Forecasting Patient Early Readmission from Irish Hospital Discharge Records Using Conventional Machine Learning Models. Diagnostics 2024, 14, 2405.

  • 2026

    Pham, M.-K., Ho, T. L. N., Dao, T. T. P., Mai, T. T., Tran, M. T., Ward, M. E., Geary, U., et al. (2026). Retrieval-aligned tabular foundation models enable robust clinical risk prediction in electronic health records under real-world constraints. arXiv preprint arXiv:2604.01841.

  • 2025

    Pham, M.-K., Mai, T. T., Crane, M., Brennan, R., Ward, M. E., Geary, U., Byrne, D., et al. (2025). Explainable AI for infection prevention and control: modeling CPE acquisition and patient outcomes in an Irish hospital with transformers. BMC Medical Informatics and Decision Making, 25(1), 391.

  • 2025

    Vining, R., Karimian, S., McDonald, N., Ebiele, M., Doyle, B., McKenna, L., et al. (2025). Trustworthy artificial intelligence and organisational trust: a scoping review using socio-technical systems analysis. Ergonomics, 1–23.

  • 2025

    Karimian, S., Ward, M. E., Corrigan, S., & Brennan, R. (2025). Enhancing healthcare data transparency through a FAIR ontology for the Systems Engineering Initiative for Patient Safety (SEIPS). Irish Conference on Artificial Intelligence and Cognitive Science, 108–119.

  • 2025

    Karimian, S., Corrigan, S., Ward, M. E., Geary, U., & Brennan, R. (2025). Integrating human factors socio-technical systems analysis in a data investigation in an acute hospital: methodological insights. International Conference on Healthcare Systems Ergonomics and Patient Safety (HEPS 2025).

  • 2025

    McDonald, N., Ward, M. E., Geary, U., O'Connell, B., Bergin, C., Byrne, D., et al. (2025). Developing an evidence-driven concept of operations for the prevention and control of healthcare acquired infections in the acute hospital setting. International Conference on Healthcare Systems Ergonomics and Patient Safety (HEPS 2025).

  • 2025

    McDonald, N., Ward, M. E., Geary, U., & Brennan, R. (2025). Building an ontology for proactive risk control. International Conference on Healthcare Systems Ergonomics and Patient Safety (HEPS 2025).

  • 2025

    Hernandez, J., Galadima, H. S., Liang, J., McKenna, L., & Brennan, R. (2025). Security models based on semantic web technologies: the ARK Platform security modules. Advances in Knowledge-Based Systems, Data Science, and Cybersecurity.