Making Sense of (Big) Bata with Visual Analytics
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This document discusses visual analytics and sensemaking. Visual analytics combines data visualization with analytics techniques to help make sense of big data. An example is given of a visual analytics system called SAVI that was used to analyze tweets and solve a crime for the VAST Challenge 2014. Sensemaking is described as the process of collecting, understanding, analyzing, reasoning about, and making decisions with data. It is an exploratory and iterative process. An example concept called SenseMap is presented as a potential "map" to support online sensemaking by capturing the analytic process. The document concludes by emphasizing the importance of sensemaking for big data and the need for better support tools.
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Making Sense of (Big) Bata 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 http://vis4sense.github.io/
- 2. Outline • What is Visual Analytics • Example - TimeSet & VAST Challenge 2014 • What is Sensemaking • Example - SenseMap
- 3. Data Visualisation – Human Cognition for Pattern Discovery
- 4. Visual Analytics = Visualisation + (Data) Analytics Visualisation Data Analysis Interaction Information Retrieval Machine Learning Data Mining Information Visualisation Scientific Visualisation Computer Graphics Human-Computer Interaction Cognitive Psychology Perception
- 5. My Previous Work – Visual Analytics
- 6. Example - VAST Challenge 2014 • 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 solve a crime
- 7. The Data
- 8. Our Entry - SAVI: Social Analytics Visualisation
- 9. 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, … • The task is usually not well defined • Can’t run a google search or SQL query to find the answer • Involve many different data • Explorative and iterative
- 10. Sensemaking Data Analysis & Visualisation Reasoning Decision
- 11. Making Sense of (Big) Data
- 12. 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
- 13. This is usually what it looks like after one hour • What is relevant and what is not? • Where are information about image quality? • How to compare the models? • Where did I left off two days ago? • How do I explain to my wife?
- 14. A ‘Map’ of Sensemaking • Sensemaking is kind of like exploring a maze … • What you need is something like this …
- 15. SenseMap – A ‘Map’ for Online Sensemaking Browser enhancement History Map Knowledge Map
- 16. SenseMap • SenseMap to support browser- based online sensemaking • Capture and visualise the analytic provenance • Support information collection and curation • Early stage of the sensemaking process
- 17. 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
- 18. Questions? I am looking for collaboration Dr Kai Xu (Associate Professor in Data Analytics) Middlesex University, London, UK k.xu@mdx.ac.uk https://kaixu.me http://vis4sense.github.io/
Editor's Notes
- Facebook network, Where the users are and how they are connected. Also interesting is where there is no users: Africa, South America, and Russia/China. Visual Analytics: combines the complementary strength of visualisation and algorithm, to better address analysis needs.
- Various funding sources: EPSRC, dstl, UK Government, EU No, we were not involved in the NSA One example
- Everyone of us does sense making all the time: Start with data collection and analysis Interpret the results: what does the number tell me? Make a decision: plan of actions
- 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.