1/20 (Big Data Analytics for Everyone) Remco Chang Assistant Professor Department of Computer Science Tufts University Big Data Visual Analytics: A User-Centric.

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Presentation transcript:

1/20 (Big Data Analytics for Everyone) Remco Chang Assistant Professor Department of Computer Science Tufts University Big Data Visual Analytics: A User-Centric Approach

2/20 “The computer is incredibly fast, accurate, and stupid. Man is unbelievably slow, inaccurate, and brilliant. The marriage of the two is a force beyond calculation.” -Leo Cherne, 1977 (often attributed to Albert Einstein)

3/20 Work Distribution Crouser et al., Balancing Human and Machine Contributions in Human Computation Systems. Human Computation Handbook, 2013 Crouser et al., An affordance-based framework for human computation and human-computer collaboration. IEEE VAST, 2012 Creativity Perception Domain Knowledge Data Manipulation Storage and Retrieval Bias-Free Analysis Logic Prediction

4/20 Visual Analytics = Human + Computer Visual analytics is “the science of analytical reasoning facilitated by visual interactive interfaces.” 1.Thomas and Cook, “Illuminating the Path”, Keim et al. Visual Analytics: Definition, Process, and Challenges. Information Visualization, 2008 Interactive Data Exploration Automated Data Analysis Feedback Loop

5/20 Visual Analytics Systems Political Simulation – Agent-based analysis – With DARPA Wire Fraud Detection – With Bank of America Bridge Maintenance – With US DOT – Exploring inspection reports Biomechanical Motion – Interactive motion comparison Crouser et al., Two Visualization Tools for Analysis of Agent-Based Simulations in Political Science. IEEE CG&A, 2012

6/20 Visual Analytics Systems R. Chang et al., WireVis: Visualization of Categorical, Time-Varying Data From Financial Transactions, VAST Political Simulation – Agent-based analysis – With DARPA Wire Fraud Detection – With Bank of America Bridge Maintenance – With US DOT – Exploring inspection reports Biomechanical Motion – Interactive motion comparison

7/20 Visual Analytics Systems R. Chang et al., An Interactive Visual Analytics System for Bridge Management, Journal of Computer Graphics Forum, Political Simulation – Agent-based analysis – With DARPA Wire Fraud Detection – With Bank of America Bridge Maintenance – With US DOT – Exploring inspection reports Biomechanical Motion – Interactive motion comparison

8/20 Visual Analytics Systems R. Chang et al., Interactive Coordinated Multiple-View Visualization of Biomechanical Motion Data, IEEE Vis (TVCG) Political Simulation – Agent-based analysis – With DARPA Wire Fraud Detection – With Bank of America Bridge Maintenance – With US DOT – Exploring inspection reports Biomechanical Motion – Interactive motion comparison

9/20 Current Big Data Practice

10/20 Human+Computer in Big Data Analytics Goal: Allow an analyst (user) to fluidly explore and analyze a large remote data warehouse from commodity hardware

11/20 Problem: Big Data is BIG and Far Away Visualization on a Commodity Hardware Large Data in a Data Warehouse

12/20 Approach: Predictive Prefetching

13/20 Predict User Behavior from User Interactions?

14/20 Experiment: Finding Waldo

15/20 Predicting a User’s Completion Time Fast completion time Slow completion time

16/20 Analyses Results: Performance Biometric (low-level mouse data) Accuracy: ~70% Interaction pattern (high-level button clicks) Accuracy: ~80%

17/20 Predicting a User’s Personality External Locus of Control Internal Locus of Control Ottley et al., How locus of control influences compatibility with visualization style. IEEE VAST, Ottley et al., Understanding visualization by understanding individual users. IEEE CG&A, 2012.

18/20 Analysis Results: Personality Traits Noisy data, but can detect the users’ individual traits “Extraversion”, “Neuroticism”, and “Locus of Control” at ~60% accuracy by analyzing the user’s interactions alone. Predicting user’s “Extraversion” Accuracy: ~60%

19/20 Developed a prototype system (ForeCache) in collaboration with the Big Data Center at MIT and researchers at Brown Evaluated system with domain scientists using the NASA MODIS dataset (multi-sensory satellite imagery) Remote analysis on commodity hardware shows (near) real-time interactive analysis Wrap Up: Theory Into Practice

20/20 Questions? Remco Chang