IN-SPIRE VISUALATION Making Sense out of Large Amounts of Data

1. IN-SPIRE VISUALATION Making Sense out of Large Amounts of Data Introduced by Global Trade Solutions, Inc

2. Overwhelmed with information but can't make heads or tails out of it? Industry and government face this challenge every day as they try to stay ahead of the competition or understand national security risks. The ability to uncover relationships, trends, and themes hidden within data can lead to discoveries of knowledge and insights that could be used to assess terrorist threats, determine how to treat a medical condition, or gather market research on the competition. IN-SPIRE™, powerful information visualization software developed by the Pacific Northwest National Laboratory, can give people the ability to discover important insights that would otherwise be obscured in large datasets. Are you getting the most out of your data…..and other’s?

3. IN-SPIRE™ can quickly and automatically convey the gist of large datasets of unstructured text documents such as technical reports, web data, newswire feeds, e-mail, and message traffic. IN-SPIRE™ can handle real-time data by adding new documents as they arrive. It also processes foreign language data and provides robust support for translation. By clustering similar documents together, this Windows-based software unveils common themes and reveals hidden relationships within the collection. IN-SPIRE™ allows analysts to spend more time exploring the information they find most relevant and less time sifting through the masses of irrelevant documents.IN-SPIRE™ uses a variety of statistical and linguistic techniques to analyze large datasets of text files in order to determine the themes of each document in the collection. The user can then analyze the documents using a variety of powerful interactive visualization based tools to explore thematic trends, discover hidden relationships, validate (or invalidate) hypotheses, and find the “needle in the haystack”. IN-SPIRE™ Visual Document Analysis

4. Social Network Analysis Challenge • Social networks can provide early indicators of security and health threats, public sentiment, and actor motivation—but the massive volume of streaming data complicates analysis. Mission Impact • PNNL algorithms are used by emergency management organizations to detect real-time themes in social media. • New techniques for discovering structure in communications traffic have been delivered to federal and regional law enforcement.

5. Exploration of Open Source Intelligence Information • for indications and warning in live, streaming social media. Mission Impact • Emergency management organizations use this capability • Challenge • The world communicates in natural language, but the volume and complexity of text—in sources like social media and open news—requires new science in theme extraction in order to detect subtle, emerging trends. • Approach PNNL invented a technique for extracting “stories” from massive text collections and representing their ebb and flow visually.

7. Making Sense out of Large Unstructured Text Data: ThemescapeTM – the big picture This is the Classic Themescape view of the entire dataset. Peak height represents the thematic density in a given region of the map. If you display this next to the Galaxy view, it's immediately apparent that it's built on top of it.  That is, the documents are located in the same spot in both views.

8. Example Case 1 – Cost Savings in Manufacturing • A large chemical manufacturer wanted to increase the yield and reduce the waste stream of the manufacture of polypropylene plastic. • Used IN-SPIRE to analyze the research literature and the patent data related to the process. • Discovered a small start-up which had developed an improved process (based on electron-donor catalysis) which was more efficient. • Instead of licensing a method from a competitor, they were able to purchase the start-up for a fraction of the cost of licennsing in order to obtain access to the new technology.

9. Example Case 2 – Medical Research • A surgical oncologist (DARPA program manager) was using IN-SPIRE to explore cancer literature abstracts from NIH (500,000+ docs) for 1990 - 1996 • Discovered a correlation between Kaposi's sarcoma and use of street drugs that had not appeared in the literature until the following year. • The causal relationship was implicit in the data, even though researchers hadn’t yet published any explicit mention of the fact until 1997.

10. Example Case 3 – Legal Discovery • A large law firm representing a major corporation in a lawsuit used IN-SPIRE to accelerate the discovery process • The case involved several million e-mail messages which had to be reviewed by attorneys to determine whether or not they were relevant to the case or needed redaction • The law firm claimed that using IN-SPIRE accelerated the process 30-fold, thus saving the client considerable money while increasing the law firm’s profit margin.

11. GTS roleIntroduce In-spire capabilitiesunderstand client objectives License in-spireProvide training and support

12. Next Steps - Start discussions toIdentify Requirement(s)Define Funding mechanism(s)Create the data platform(s)

13. For further information, please contact: Fred Johnson fred@gtsworldwide.com Introduced by Global Trade Solutions, Inc