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Details of Grant 

EPSRC Reference: EP/J020443/1
Title: DIVA: Data Intensive Visual Analytics - Provenance and Uncertainty in Human Terrain Analysis
Principal Investigator: Wood, Dr JD
Other Investigators:
Stephens, Dr D Xu, Dr K Dykes, Professor JA
Researcher Co-Investigators:
Project Partners:
Department: Information Science
Organisation: City, University of London
Scheme: Standard Research
Starts: 31 May 2012 Ends: 30 May 2013 Value (£): 172,333
EPSRC Research Topic Classifications:
Computer Graphics & Visual. Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine
Related Grants:
Panel History:
Panel DatePanel NameOutcome
09 Feb 2012 Data Intensive Systems (DaISy) Announced
Summary on Grant Application Form
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 and security applications in close collaboration with DSTL. It will investigate visual methods for effectively utilising the kinds of dynamic and uncertain data that are emerging from multiple and frequently conflicting sources. Methods will be developed to store, communicate and use metadata about (potentially conflicting, uncertain and messy) data origins, quality and analytical process. They will be transferable and apply at operational and strategic levels.

We draw together a team of UK academics with complimentary expertise. Contributors from Middlesex University and City University London have growing international reputations for developing innovative and applied visual analytics solutions and the theoretical work that supports this activity. Contributors from Loughborough University offer experience of information management and analysis in real time, harsh environments and the military context. The team will work closely to establish and evaluate the potential for DIVA in the area of Human Terrain Analysis.

The programme of work is designed to ensure close engagement between academics and DSTL colleagues. Short bursts of concerted activity focusing around a series of participatory design workshops will result in rapid development and evaluation. These intense periods of coordinated co-located activity will stimulate subsequent reflection and respond to feedback involving DSTL in an iterative process. A continuous bridging presence over a 12 month elapsed period (one researcher working at two sites) will support and consolidate this work. These efforts will address critical research issues faced by the emerging academic VA community:

* How can we best support analysts with information about data uncertainty and provenance?

These factors underlie analytic approaches in data intensive systems yet many issues remain unresolved.

* How can we capture, annotate and explain the analytic process?

Doing so will enable us to reproduce the analytic process and support communication and collaborative analysis.



* How do VA approaches apply in critical applications areas?

Close collaboration with DSTL will ensure that academic developments are grounded in and informed by an applications domain that is vital to national security.

The planned activity will produce schemas, methods and prototypes that address these questions, support analytical work and demonstrate DIVA potential in the military context.

The results are likely to have application impact across MOD and in wider disciplines to which VA is being increasingly applied, including significant data intensive areas in science, industry and government.

Findings will be communicated widely through national and international academic conferences, social media, press releases and at DSTL networking events. Software and functionality developed will be made available through a Creative Commons licence. Along with the knowledge derived through the planned research, this will be used by the UK Visual Analytics Community.

The project offers significant value, using existing skills, equipment and technology, and has low start-up costs. No recruitment is necessary with all participants employed in dynamic and successful research groups at the three participating institutions: City University London (lead), Middlesex University and Loughborough University. The programme of activity involves 24 months of research time over 12 months elapsed time and fits in well with the schedules and workloads of world class researchers operating in the international arena. All are committed to the work plan, which will contribute to institutional objectives in all cases and is supported by the US National Visual Analytics Centre.

Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Further Information:  
Organisation Website: http://www.city.ac.uk