Spatiotemporal Exploration and Visual Analytics

Our spatiotemporal visual analytics research involves analyses  of events, people, places, and resources that vary over time.  We have developed novel, patented spatiotemporal predictive analytics techniques and useful deployed systems for use in resource allocation, workload prediction, scheduling, and logistics management.  Our predictive/correlative and other analytics research within its spatiotemporal suite of tools enables users to better:

• Explore and understand complex datasets.

• Understand potential patterns at different scales and in different spaces/environments.

• Employ the outcomes from the datasets for effective decision-making.

Social Media Analytics and Reporting Toolkit (SMART)

This technology provides analysts with scalable and interactive social media analysis and visualization through topic extraction, combination of filters, cluster examination, and stream categorization for increasing situational awareness in disaster events and accidents using social media data.

Purdue: Ebert | University of Stuttgart: Ertl

Visual Analytics Law Enforcement Toolkit (VALET)

This project allows enhanced exploration and analysis of multivariate spatiotemporal law enforcement data to enable advanced data exploration and analysis of high volume criminal, traffic and civil incidence report data.

Purdue: Ebert, Collins

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iValet - Mobile Visual Anaylytics Law Enforcement Toolkit

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CGSaRVA - Coast Guard Search and Rescue Visual Analytics

This system provides Coast Guard managers and analysts with a suite of tools for analyzing the distribution of previous search and rescue cases and a methodology for understanding the risk, efficiencies, and benefits involved with reallocation or reduction of resources.

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Situation Surveillance & In-field Criminal Investigative Analytics

Develop an exploratory visual analytic mapping method to support criminal investigative analytics by processing large geographically referenced data, then searching for events of interest.

Purdue: Ebert, Boutin, Delp, Cleveland / Penn State: MacEachren, Hardisty / Virginia Tech: Barrett, Eubank, Marathe / Rutgers: Roberts

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Study of Terrorism and Responses to Terrorism (START) Center Visual Analytics

Having collect large amounts of data on terrorism and terrorism response at the START Center, the Visual Analytics component proposes to refine and explore the data by analyzing it visually.

Purdue: Ebert, Elmqvist / UNCC: Kosara / START: Smarick / Rutgers: Roberts, Pottenger

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Visual Analytics for the DHS Center of Excellence Projects

Leverage visual analytics to create an interactive visual database of all research and educational material produced by the Centers for exposure to the scientific community, government agencies and the general public.

Purdue: Elmqvist, Ebert / GeorgiaTech: Stasko / SFU: Dill / Rutgers: Roberts / USC: Hovy / UIUC: Roth

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Flight Delay Visualization (FlightVis)

This project provides a visual analytics environment enabling users to explore multivariate spatial node-link data (e.g., flight delay data) with novel visual representations (Petals and Threads) and an anomaly detection algorithm.

Purdue: Ebert / University of Oxford: Chen / Sejong University: Yun Jang

SensePlace 2 - Harnessing Twitter to Support Situational Awareness and Crisis Management Through Geovisual Analytics

SensePlace2 is a geovisual analytics application that forages place-time-attribute information from the Twitterverse and supports crisis management through visually-enabled sensemaking with the information derived.

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TRIP -Travel Response Investigate Profiler

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CrimeViz - Spatiotemporal Social Media Aalytics for Abnormal Event Detection

An extensible web-based map application that supports geovisual exploration of, and sense making about, criminal activity in space and time.

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iOPAR - Operational Perfomrance Assesment Reports

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GeoJunction: Collaborative Visual-Computational Information Foraging and Contextualization to Support Situation Awareness

This project focuses on developing a tool which helps its users to search and contextualize place-time aware data to support situation awareness and interpret evidence and make decisions in a continually changing environment.

Penn State: MacEachren, Mitra / USC: Hovy

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MADIS - Multimedia-Aided Disaster information Integration System

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