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Making Sense of (Big) Data with Visual Analytics
The document discusses the concept of sensemaking in relation to visual analytics, highlighting its importance in decision-making processes across various domains. It emphasizes the limitations of AI, such as IBM Watson and AlphaGo, in handling ill-defined tasks like choosing a camera, and argues for the integration of human and computing intelligence. Additionally, it presents demonstrations of visual analytics systems like SAVI and Sensemap as tools to aid in the sensemaking process.
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 isSensemaking • 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 isthe 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 usuallywhat 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 inbrowser
- 7. Making Sense of(Big) Data
- 8. Why IBM Watsonor 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 thebest 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 inthe 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
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- 14. SAVI: Social AnalyticsVisualisation
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- 16. Map Visualisation andSensemaking 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’ ofSensemaking • 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
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- 22. Takeaway Messages • Sensemakingis 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
- #8 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.
- #12 Various funding sources: EPSRC, dstl, UK Government, EU No, we were not involved in the NSA One example