Data Science and Decisions - How can MOD harness the benefits of data science? How do we build trust in automated systems? How do we integrate multiple sources of information with differing levels of uncertainty and represent this effectively and efficiently to busy decision makers?
Background
In an increasingly connected and complex world, we need to optimise our use of rich and diverse data sets to inform decision makers in a timely manner. As the types and volumes of information available to the commander increase, this will place a greater importance on tools and techniques to collate, synthesise and visualise information in a timely and understandable way so that it can be readily acted upon. Different sources will have different degrees of assurance but combining multiple information sources greatly increases the robustness of the analysis – although we need to be able to show levels of certainty/uncertainty within the analysis.
Next steps
Get in touch with accelerator@dstl.gov.uk
Topics
Related UKRI funded projects
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DIVA: Data Intensive Visual Analytics - Provenance and Uncertainty in Human Terrain Analysis
Data Intensive Visual Analytics can help address the data deluge by helping decision makers to rapidly reach informed and effective decisions in a range of situations. This exploratory project will apply DIVA to defence...
Funded by: EPSRC
Why might this be relevant?
The project addresses the question fully and the authors have the necessary expertise.
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ExtremeXP
Extreme data characteristics (volume, speed, heterogeneity, distribution, diverse quality, etc.) challenge the state-of-the-art data-driven analytics and decision-making approaches in many critical domains such as crisis...
Funded by: Horizon Europe Guarantee
Why might this be relevant?
The project addresses the challenges of handling extreme data characteristics and decision-making processes, integrating various data sources with differing levels of uncertainty, and building trust in automated systems.
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From Models To Decisions (M2D)
Today many decisions are made using evidence from numerical models. Such models are often large and complex and often appear to be without uncertainty. However, even if the model is itself deterministic in that it gives ...
Funded by: EPSRC
Why might this be relevant?
The project addresses the question partially and the authors have the necessary expertise.