Making Sense of (Big) Data with Visual Analytics
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Did you have 20 opened Chrome tabs and feel frustrated about research? This is a problem more than organising tabs. In this talk, I will introduce how to combine human and machine intelligence (yes, not machine alone) to address this challenge.
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Making Sense of (Big) Data with Visual Analytics
- 1. Making Sense of (Big) Data with Visual Analytics Dr Kai Xu Associate Professor in Data Analytics Middlesex University, London, UK k.xu@mdx.ac.uk https://kaixu.me
- 2. Outline • What is Sensemaking • Why do we need Visual Analytics • Demo – SAVI: Social Analytics Visualisation • Demo – SenseMap: A ‘Map’ for Sensemaking
- 3. What is Sensemaking? • Making sense of data • Collecting, understanding, analysing, reasoning, and making decisions • It is something we do everyday: • Plan a holiday, buy a house, understand an illness, … • Defence, policing, investment, medical diagnosis, … • How is it different from data analysis? • The task is usually not well defined
- 4. Example: what is the best camera for about £500? What is the best camera for £500? Pixel number Sensor size Image quality chromatic aberration?! Noise reduction What does experts say? Online reviews What does my friend say? Smart phone Compact Full frame? Micro 4/3?Sony RX100 Nikon D750Samsung Galaxy S7 What are the price? How do I compare? Panasonic LX100 Form factor Models Camera Lens Aperture
- 5. This is usually what it looks like after one hour • What is relevant and what is not? • Where is the information about image quality? • How to compare the models? • Where did I left off two days ago? • How do I explain to my wife?
- 6. Not just in browser
- 7. Making Sense of (Big) Data
- 8. Why IBM Watson or AlphaGo can’t do it • Watson is good at: • Natural language processing, e.g., understand the Jeopardy! Questions • Find the (relevant) fact quickly • However, the £500 camera task is • Every personal, Watson need all the information about me and understand it • No ‘best’ answer, so can’t just search it • For AlphaGo, the Go game is very complex and difficult, but • The goal and rules are very well defined, and the results are easily measurable • However, the £500 camera task is ill defined and not easily measurable • How many people have the knowledge and resource to build a deep neural network, collect all the training data, and then train and tune it, just to find a camera?
- 9. Who is the best chess player in the world? • Deep Blue, was in 1997 • Currently, probably a human-machine team • And the two people on the team are not even professional chess players • The power of integrating the complementary strength of human and machine
- 10. Visual Analytics = Human + Computing Intelligence Visualisation Data Analysis Interaction Information Retrieval Machine Learning Data Mining Information Visualisation Scientific Visualisation Computer Graphics Human-Computer Interaction Cognitive Psychology Perception
- 11. Some work in the last five years
- 12. Example - SAVI: Social Analytics Visualisation • IEEE Visual Analytics Science & Technology (VAST) Challenge • Provide dataset and analysis tasks • Entry: visual analytics systems • Leading research groups and companies • VAST Challenge 2014 – Mini Challenge 3 • Data: tweets • Task: detect and describe a crime
- 13. The Data
- 14. SAVI: Social Analytics Visualisation
- 15. Video
- 16. Map Visualisation and Sensemaking Support
- 17. The Final Findings • Still a long time before AI can do such sensemaking • Difficult for human, too: almost impossible without the tool • Human leads, the tool supports • The tool does not provide answer, • Reveal pattern, help with organisation and reasoning, and many more
- 18. A ‘Map’ of Sensemaking • Sensemaking is kind of like exploring a maze … • What may be helpful is something like this …
- 19. SenseMap – A ‘Map’ for Online Sensemaking Browser enhancement History Map Knowledge Map
- 20. Video
- 21. Comparison
- 22. Takeaway Messages • Sensemaking is how people understand, reason, and make decisions with data • It is important to Big Data, but there is limited support available • Visual Analytics combines data visualisation with analytics • A promising approach for sensemaking support More details about SAVI and SenseMap: http://vis4sense.github.io/
Editor's Notes
- A Sense Making model: Using literature review as an example from search & filter and then jump to hypothesis & presentation. For big data, most focus on the early stages of sense making: we have storage, search, and analysis; Relatively 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, EU No, we were not involved in the NSA One example