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Benchmark Details


Provenance: VAST Challenge 2016
Title: Mini-Challenge 2


Description:

As an expert in visual analytics, you have been hired to help GAStech understand its operations data. In this challenge, you are given two weeks of building and prox sensor data. Can you use visual analytics to identify typical patterns of and issues of concern?

Mini-Challenge 2 provides a two-week set of static data for you to analyze, covering May 31 to June 13, 2016.

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Dataset available at:
Click Here
Solution:
Click Here
Contacts:
Kris Cook, Pacific Northwest National Laboratory
Georges Grinstein, University of Massachusetts Amherst
Mark Whiting, Pacific Northwest National Laboratory
Kristen Liggett, Air Force Research Laboratory
Diane Staheli, MIT Lincoln Laboratory
Jordan Crouser, Smith College
John Fallon, University of Massachusetts Amherst

Total uses: 21
Used by:
Central Michigan University
Central South University
Chongqing University of Posts and Telecommunications
City University London
Award: Outstanding Presentation of Patterns in Context
Hong Kong University of Science and Technology
Instituto Tecnológico Buenos Aires
KU Leuven
Award: Strong Support for Visual Anomaly Detection
Knowledge Based Systems Inc
Middlebury College
Peking University
Award: Outstanding Comprehensive Solution
Purdue University
Award: Honorable Mention - Good Aesthetics
Tata Consultancy Services
Award: Honorable Mention - User-Friendly Anomaly Detection
University of Amsterdam
University of Buenos Aires
University of Buenos Aires - Andreoni
University of Konstanz
University of Maryland College Park
Award: Honorable Mention - Clear Analysis Strategy
University of Middlesex
University of St Andrews
VRVis Research Center
Award: Honorable Mention - Effective Support for Building Management
Zhejiang University

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