Numbers of the Future: Dealing with Uncertain Data for Quantitative Risk Analysis
Submission deadline: 28 February 2027

Risk is an important consideration across multiple disciplines such as: engineering, industry, healthcare, finance, and forensics. Quantitative risk analysis based on empirical, experimental or expert-elicited data will give a numerical measure of risk. However, the trustworthiness and reliability of the result is vulnerable to the level of quality and availability of the data that is used. Coupled with the (often) complex computations involved, the data and calculations need to be reliable, trackable, reusable, comprehensively described and linked, whilst safeguarding private information. The combination of all these factors introduces significant challenges and elements of uncertainty into the overall quantitative risk analysis.

This begets the following fundamental research questions:

• What details are needed when collecting and sharing observational data and calculations?
• How can we be sure that empirical effort produces meaningful, correct, and logically complete measurements?
• What changes or augmentations are needed in empirical work to ensure that estimates and calculations are trackable and checkable?
• What structures and processes can make scientific statements trustworthy, beyond relying on the integrity of scientists as individuals?
• How can these be automated to be natural and least burdensome?
• How can we radically reduce the need to ’clean’ data sets?
• What provisions can guarantee that the information is secure and uncorrupted but also accessible and reusable?
• How can we avoid wasting or losing observations?
• What are the ethical considerations around anonymisation of data?

Guest editors:

Adolphus Lye (Executive Guest Editor), Singapore Nuclear Research and Safety Institute, National University of Singapore, Singapore; Email: snrltsa@nus.edu.sg

Nicholas Gray, Institute of Population Health, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK; Email: nick.g.gray@gmail.com

Alexander Wimbush, Cancer Research Clinical Trials Unit, School of Medical Sciences, University of Birmingham, Birmingham, UK; Email: a.wimbush.1@bham.ac.uk

Yu Chen, Department of Mechanical and Aerospace Engineering, University of Liverpool, Liverpool, UK; Email: yu.chen2@liverpool.ac.uk

Kari Sentz, Los Alamos National Laboratory, Los Alamos, USA; Email: ksentz@lanl.gov

Special issue information:

The objective of this special issue is to create a collection of the state-of-the-art methodologies and cutting-edge research results in the context of risk analysis across multiple disciplines, aimed at addressing the above research questions. Topics of interest to the special issue include (but not limited to):

• Dealing with uncertainty from expert elicitations

• Dimension and units checking and propagation

• Decision-making under justification tracking

• Provenance and calculation stream histories

• Evidence and justification tracing

• Ethical dimensions of numbers and data

• Truthfulness of numbers reported in crisis situations

Note that all contributions should explicitly highlight and address the challenges in risk analysis due to uncertain data.

The Special Issue is inspired by the works presented at the inaugural “Numbers of the Future” conference held at the University of Liverpool, United Kingdom, between the 3rd and 5th December 2025. Extended versions of the research works presented at that conference are welcomed. Contributions from researchers and practitioners beyond the conference are also welcomed.

Manuscript submission information:

Important Dates:
Submission Open Date: April 13, 2026
Submission Deadline: February 28, 2027
Notification of Acceptance: May 31, 2027

Manuscripts must be submitted via the International Journal of Approximate Reasoning online submission system (Editorial Manager®). Please select the article type “VSI: Numbers of the Future” when submitting your manuscript online.

Please refer to the Guide for authors to prepare your manuscript.

All submitted papers under this call will undergo the standard review process of the journal.

For any further information, the authors may contact the Guest Editors.

Keywords:

Uncertainty quantification; Risk analysis; Trustworthiness; Data analytics; Security