10. DIVA: Data Intensive Visual Analytics
• EPSRC (UK Research Council) and DSTL
(Defence Science and Technology Lab)
• Uncertainty in Human Terrain Analysis
– Help ground troops understand local social
structure (i.e., the sense making task)
• Approach
– Visual Analytic
– Analytic Provenance
11. Data Provenance
• “The sources of information,
such as entities and processes,
involved in producing an
artefact” (W3C).
• Provenance decides the value of
the ‘artefact’
• Analytic provenance: how users
make sense of data
16. Looking for domain application
and commercial collaboration
Kai Xu
k.xu@mdx.ac.uk
http://kaixu.me
Editor's Notes
What is visual analytics, and how visual analytics can be used to make sense of big data. Different from data visualisationStart with some background
Middlesex University, north-west LondonIt is a young university and growing very fastLast two years hire 150 new academic staffs, from deans, professors, to lecturers.
A recent photo of staff members (not all of them), and all the students are missing.Lead the UK Visual Analytics Consortium (UKVAC): four other universities.
What is visual analytics?Humans are particularly good at certain things, such as finding patterns in the data. Machines can computer very fast and process large amount of data. Visual Analysis tries to combine the best of both worlds.
Everyone of us does sense making all the time: Start with data collection and analysisInterpret the results: what does the number tell me?Make a decision: plan of actions
A slightly more complex model of Sense Making6 stagesIterative process
For big data, most focus on the early stages of sense makingwe have storage, search, and analysisRelatively very little on the further stages
This is the focus of our research. Not all the stages at the same time yet.Mostly in the defence and intelligence domain.
Various funding sources: EPSRC, dstl, UK Government, EUNo, we were not involved in the NSAOne example
A fake Mona Lisa does not worth muchData from unreliable sources probably should be avoided altogether
PrototypeFacets: location, time, authorView can be configuredSelect which is the main viewDynamic filtering
Provenance of the visualisationProvenance of the data explorationConstruct narrative
Visualise epidemic spread through twitter dataFacets and filteringProvenance and note taking
Application in domain other than defence and intelligenceCommercialisation feasiblity