2008-2009 Highlights

VAST Challenge: The VAST 2008 Challenge consisted of four heterogeneous synthetic data sets each organized into separate mini-challenges. The Grand Challenge required integrating the raw data from these four data sets as well as integrating results and findings from team members working on specific mini-challenges

Each mini-challenge was addressed using a custom Improvise visual analysis environment tailored to working with the particular data provided and making use of connections to other NEVAC analytical methods. The NEVAC team won the wiki-edit mini-challenge.

For the Grand Challenge report, modeling the problem with a semantic network provided a means for integrating both the raw data and the subjective findings. The NEVAC team won the Data Integration (Grand Challenge) based on the overall results.

ReliefWeb: Today's increasingly interconnected world coupled with a modern hazard-scape, derived in part from climate change, increased population, societal over-dependence on computing technology, violent conflicts, and terrorism, is creating an environment where disasters increasingly cross international borders and where the global community responds to those disasters and makes long-term commitments to recovery. International disaster response and recovery is increasingly being coordinated through ReliefWeb, a sub-organization with the United Nation's Office for the Coordination of Humanitarian Affairs (OCHA). The primary mission of ReliefWeb is to serve as an information management coordination role through the collection, maintenance, and dissemination of humanitarian information to the humanitarian community. As the world's central repository for vast amounts of heterogeneous humanitarian information, ReliefWeb represents an important and unique group that can benefit from the applied use of geovisual analytic technologies.

In 2008, NEVAC-alumni Dr. Brian Tomaszewski worked with ReliefWeb to incorporate select open-source geovisual analytic technologies he developed for use on the ReliefWeb site. In particular, Dr. Tomaszewski developed a humanitarian vacancies mapping application, which automatically creates map symbols by geocoding an RSS feed of humanitarian vacancies published by ReliefWeb. The geocoder used in this application is a open-source geographic information retrieval algorithm developed by Tomaszewski as part of other NEVAC geovisual analytic research on supporting situation assessment and reasoning with text documents. The application represents a small, but an important, first step toward the use of geovisual analytics in homeland security threats that can be addressed through the general improvement of the lives of destitute people around the world.

NeoCITIES Geo-tools: NeoCITIES Geo-tools is both an update and an extension of the original NeoCITIES scaled world simulation developed based on knowledge elicitation from crisis management experts. At its core, the NeoCITIES simulation is a resource allocation problem involving police, fire and hazmat teams designed to mimic the emergent situations that comprise real-life emergencies and to measure decision-related outputs.

NeoCITIES Geo-tools incorporates a host of geo-spatial tools, including: an interactive multi-layer map, an annotated geo-chat capability (linking chat to map objects to avoid misunderstandings), and elementary GIS analysis features. Developed using Adobe Flex technology, NeoCITIES Geo-tools can potentially run on any device capable of supporting Adobe Flash player. Thus, it is not only web deployable, but can also be scaled to work with portable devices like tablet PCs or PDAs. The simulation is in the advanced stages of implementation and testing, having undergone multiple cycles of design, usability evaluation, and redesign.

Information Theoretic Framework: In our ongoing development of an information theoretic framework for visual analytic reasoning, software development in 2009 has focused on setting up tools and data for execution of the experiments on Drexel's 64-CPU compute cluster. This included setup and debugging of the Large Graph Layout algorithm with a few small submissions to the SourceForge project (http://lgl.sourceforge.net/). In June, we extended previous work on large graph analytics and visualization to assessment of the Influenza A H1N1 2090 Mexican Swine Flu.

We integrated data on all Influenza protein sequences available at the National Center for Biotechnology Information (NCBI). All available sequences were compared for similar-ity using BLAST on a 64-core supercomputer at Drexel University. The results of this analysis were used to create a base-line map of similarity using the Large Graph Layout algorithm. This map has been annotated with the current pandemic strain, strains from historical deadly pandemics and the proteins known to cause virulence in humans. This map provides a novel tool for the interactive assessment of risk based on existing molecu-lar biology theory and published research using near real-time sequence data being up-loaded to NCBI daily. We are currently working with the Drexel College of Medicine Department of Epidemiology and Biostatistics to analyze this data.