Aligning Enterprise Data Quality with Defence Needs
Conference
Australian Defence Science, Technology and Research Summit 2026 (ADSTAR)
Title
Aligning Enterprise Data Quality with Defence Needs
Abstract
Military intelligence gathering faces well-known challenges in our modern information age. From a press release announcing the Thai Air Force’s acquisition of two H225 multi-role helicopters, to a Boeing brochure touting the latest efficiency gains of its blended winglet – data, fragments forming open source information come in all forms. The fragment may come from a dubious source, it may have had unit conversion error going from pounds to kilograms, or it may be slightly outdated. How does one reconcile these disparate data fragments of varying quality and trustworthiness in a unified system, and propagate them for subsequent synthesis into credible Open Source Intelligence (OSINT)?
In this presentation, we present an approach to adapt enterprise data quality management for use in a military intelligence context. The traditional dimensions of enterprise data quality, such as timeliness, authoritativeness, and validity are adapted to score each open-source data fragment. The result is a reproducible and unified scoring function from which the authors can collapse these varying enterprise data quality attributes into the traditional, singular confidence measure of information quality. As a starting point, the scoring function is a simple weighted arithmetic sum of the constituent data quality dimension scores. The weights have been derived through preliminary workshops using the structured decision-making analytic hierarchy process, Analytic Hierarchy Process (AHP), for various stakeholder groups.
The approach leverages proven practices for resolving data quality concerns in enterprise applications and can be expanded to include more complex scoring functions. These include geometric sums, sensitivity analysis on the chosen data quality dimensions and the impact of uncertainty propagation on the final confidence. Like any decision-making process, a degree of subjectivity is present and further workshops with stakeholders from different intelligence military domains are needed to further generalise the technique.
Key takeaways:
- Traditional enterprise data quality dimensions, such as timeliness, authoritativeness, and validity, can be adapted to assess open-source data for military intelligence.
- Converting multiple data quality attributes into a single confidence measure allows intelligence assessments to become more transparent and repeatable.
- Despite the above, a degree of subjectivity remains, with stakeholder input essential to strengthen and further generalise the technique.
Authors
John Wharington PhD, Principal System Engineer, Shoal Group
Luan Dinh, Modelling and Simulation Engineer, Shoal Group
Date
Thursday 6 August 2026
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About Shoal
Shoal is complex systems design company. We use Systems Engineering combined with Modelling, Simulation and Analysis to help our clients define, analyse, decide, optimise, and deliver technology-intensive projects in complex environments across Defence, Space, Transport, Energy and Infrastructure.
In 2026, Shoal celebrates 25 years of applying systems thinking to complex challenges.
More: shoalgroup.com
Contact
Matthew Wylie
Head of Engineering, Shoal Group
[email protected]
