1. 1 APPROVED FOR PUBLIC RELEASE U.S. Army Research, Development and Engineering Command ARL-CISD Social Network Analysis Team Leader Visual Analytics Consortium, July 31, 2012 Elizabeth.k.bowman.civ@mail.mil Dr. Elizabeth K. Bowman Challenges and Successes in Visual Analytics for Big Data: An Army Perspective

2. 2 APPROVED FOR PUBLIC RELEASE DOD’s D2D Strategic Inititiative Army perspective on Visual Analytics: –How has big data changed our approach? –Barriers to transitioning research? –Key factors to applying interactive visual techniques to big data? –Key future opportunities for visual analytics? Outline

3. 3 APPROVED FOR PUBLIC RELEASE Mr. David Jakubek, ASD(R&E), sponsor of Data to Decisions D2D is a defense S&T priority area (1 of 7) Goal: reduce cycle time and manpower required to conduct analysis in support of military missions Research shows large data management aids acquisition of more data, not HSI and analysts’ ability to analyze data in timely fashion Unmet needs: –How to increase quality of collected data in context of a decision –How to better represent complex data –How to decrease errors, conflicts, and holes in datasets –How to increase discoverability DOD Data to Decisions (D2D)

4. 4 APPROVED FOR PUBLIC RELEASE Extensive search for algorithms to fuse hard/soft data Interdisciplinary research to develop context-aware sensing Efforts to develop decision-driven collection methods How has Big Data Changed the Way We Approach VA? CHALLENGEOPPORTUNITY Social media applications provide open source reports Topic and sentiment analysis techniques can augment physical sensor reports Re-think the role of decisions in D2D

5. 5 APPROVED FOR PUBLIC RELEASE Become aware of social identity & group structure Focus on tactical levels Social-Cultural Challenges: o Data Collection o Information Processing o Visualizing Associations Cultural Imperatives for COIN

6. 6 APPROVED FOR PUBLIC RELEASE Social-Cultural Data Collection Why is collection so difficult? Local context matters and varies by small group Collector perspectives influence perception of observations Cultural norms are buried in tradition and are often difficult to explain and describe Theoretical models that explain social behavior have limited predictive power in a military context (longer term vs. shorter term) Traditional ethnography is a tedious and long-term process

7. 7 APPROVED FOR PUBLIC RELEASE Social networking is not only for ‘keg’ parties anymore Dynamic and localized intel around the globe: o Willingness and capability of millions to post information and images o ‘Viral’ spread of information and influence across a variety of social groups Text & Imagery have meta-data tags for processing triage Transformative Socio-Technical Events

8. 8 APPROVED FOR PUBLIC RELEASE Social Network Analysis It’s not about who is connected to whom, but: o Why o How o Where o When o For what purposes Trend analysis Semantic analysis and trends Topic detection and analysis Detecting hidden properties o Clusters o Links o Actions and behaviors Cultural influences and understanding Needed: automatic extraction of social network features

9. 9 APPROVED FOR PUBLIC RELEASE Monolithic, stove-piped analysis systems Mis-understanding of social-cultural research traditions (Qualitative Research is empirical science) Search for a quick answer vs. a longer perspective Reluctance to move beyond our areas of expertise in the physical world of high- performance sensing Barriers to Transition?

10. 10 APPROVED FOR PUBLIC RELEASE Goal: Identify leaders, topics, supporting motivation, semantic trends, identify roles and relationships in social networks, track and forecast activity Issues o Data overload o Data variety (unstructured/semi-structured) o Foundational models and ontology for associations & correlations o User-defined options for selecting views o Representing uncertainty o Collaborative interactions with co-located/remote team members o Decision-adaptive views o Unpredictability and frequency of change in data Key Factors in Applying Interactive Visualization Techniques to Big Data?

11. 11 APPROVED FOR PUBLIC RELEASE Key Future Opportunities for VA of Big Data? “We cannot simply maneuver through the terrain. We must also “maneuver” through the population, e.g., physically maneuvering along cultural avenues of approach vice physical, or maneuvering through the systems that support the population.” USJFCOM Concept for Joint Urban Operations, 1/14/2004 Counter-Insurgency Operations Diplomatic Monitoring Humanitarian Aid & Disaster Relief Operations Networked medical care/tracking in tactical operations Forecasting impending conflicts