Abstract
Situation analysis for activities such as crisis management, military situation awareness, homeland security, or environmental monitoring is both enabled and challenged by access to enormous data sets. The advent of new sensing capabilities, advanced computing and tools available via cloud services, intelligent interconnections to mobile devices, and global interconnectivity with ever-increasing bandwidths provide unprecedented access to data and to computing. In addition, emerging digital natives freely share data and collaboration. Thus, on one hand situation analysts have great opportunities to access unprecedented amounts of information from sensors, human observers and online sources to assist in understanding an evolving situation. On the other hand, this access to huge data sources and computing can create a type of intelligence attention-deficit disorder, in which analysts are overwhelmed by the urgent, but lack the ability to focus on important data. This chapter provides a summary of this dilemma, describes a new analysis paradigm that links data-driven and hypothesis driven approaches, introduces a new prototype analyst workbench, and discusses an educational approach to empower the next generation of analyst.
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References
Bedworth M, O’Brien J (2000) The Omnibus model: a new model of data fusion? IEEE Aero Elect Syst Mag 15(4):1903–1910
Blasch E, Plano S (2002) DFIG Level 5 user refinement issues supporting situational assessment reasoning. In: Proceedings of SPIE, vol 4729. SPIE, Wyndham, PA, pp 270–279
Bostock M, Ogievetsky V, Heer J (2011) Data-driven documents. IEEE Trans Vis Comput Graph 17(12):2301–2309
Boyd J (1987) A discourse on winning and losing. USAF, Maxwell AFB, Montgomery, AL
Cai G (2007) Formalizing analytical discourse in visual analytics. In: VAST-IEEE Symposium on Visual analytics and technology, Sacramento, CA, pp 217–218.
Cai G, Graham J (2014) Semantic data fusion through visually-enabled analytical reasoning. In: Proceedings of Fusion 2014: The Seventeenth International Conference on Information Fusion, International Society of Information Fusion, Salamanca, Spain
Cai G, Sharma R, Maceachren A, Brewer I (2006) Human-GIS interaction issues in crisis response. Int J Risk Assess Manag 6(4/5/6):388–407
Cai G, Hall DL, Llinas J, Gross G (2014) A visual framework for data fusion in investigative intelligence. In: SPIE DSS Conference on Next-Generation Analyst II. SPIE, Baltimore, MD
Carrico L, Guimarares N (1998) Integrated multi-views. J Vis Lang Comput 9(3):287–297
Dasarathy B (1994) Decision fusion. IEEE Computer Society Press, Washington, DC
Endsley M (1995) Towards a theory of situation awareness in dynamic systems. Hum Factors 37:32–64
Foo P, Ng G (2013) High-level information fusion: an overview. J Adv Inf Fusion 8(1):33–72
Graham JL (2010) Analytic decision game # 2: diabolical deeds in the district: instructor course guide for SRA 231: decision theory and analysis. The Pennsylvania State University, College of Information Sciences and Technology, University Park, PA
Graham JL (2011) Analytic decision game # 3: piracy on the high seas, instructor course guide for SRA 440W: security and risk analysis capstone course. The Pennsylvania State University College of Information Sciences and Technology, University Park, PA
Graham JL, Hall DL (2012) The use of Analytic Decision Game (ADG) methods for test and evaluation of hard and soft data fusion systems and education of a new generation of data fusion analysts. In: MSS National Symposium on Sensor and Data Fusion. GTRI, Washington, DC
Hall DL (2002) Semantic information fusion: breaking the bits-barrier. The Pennsylvania State University, College of Information Sciences and Technology, University Park, PA
Hall DL (2011) Challenges in hard and soft fusion: worth the effort? In: Proceedings of the SPIE Defense, Security and Sensing Symposium, Orlando, FL
Hall DL, Jordan JM (2010) Human-centered information fusion. Artech House, Inc., Boca Raton, FL
Hall DL, Llinas J (2014) The emergence of the millennium analyst: How advances in information technology and use enable asymmetric ISR. In: Proceedings of the MSS National Symposium on Sensor Data Fusion. Springfield, VA
Hall DL, McMullen SA (2004) Mathematical techniques in multisensor data fusion. Artech House, Inc., Boca Raton, FL
Hall DL, Hellar BD, Llinas J, McNeese M (2006) Assessing the JDL model: a survey and analysis of decision and cognitive process models and comparison with the JDL model. In: Proceedings of the National Symposium on Sensor and Data Fusion, McLean, VA
Hall DL, Hellar BH, McNeese MD (2006b) Rethinking the data overload problem: closing the gap between situation assessment and decision making. In: MSS National Symposium on Sensor and Data Fusion. MITRE Corporation, Washington, DC
Hall DL, McNeese M, Llinas J, Mullen T (2008) A framework for hard/soft fusion. In: Proceedings of the 11th International Conference on Information Fusion, Cologne, Germany
Hall DL, Chong C-Y, Llinas J, Liggins M II (2013) Distributed data fusion for network-centric operations. CRC Press Taylor & Francis Group, Boca Raton, FL
Hall DL, Rimland J, Shafer S (2014) A hitchhiker’s guide to distributed hard and soft information fusion infrastructure development. In: Proceedings of the International Conference on Information Fusion, Salamanca, Spain
Hall MJ, Hall SA, Tate T (2000) Removing the HCI bottleneck: How the human computer interface (HCI) affects the performance of data fusion systems. In: Proceedings of the 2000 MSS National Symposium on Sensor and Data Fusion, San Diego, CA
McNeese M, Vidulich MA (2002) Cognitive systems engineering in military aviation environments: Avoiding Cogminutia Fragmentosa. CSERIAC Press, Wright Patterson AFB, OH
North C, Shneiderman B (2000) Snap-together visualization: can users construct and operate coordinated visualizations? Int J Hum Comput Stud 53(5):715
Pike W, Bruce J, Baddeley B, Best D, Franklin L, May R et al (2009) The scalable reasoning system: lightweight visualization for distributed analytics. Inf Vis 8(1):71–84
Pirolli P, Card S (2005) The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. In: Proceedings of the 2005 International Conference on Intelligence Analysis, McLean, VA
Rimland J, McNeese MM, Hall DL (2013) Conserving analyst attention units: use of multi-agent software and CEP methods to assist information analysis. In: SPIE DSS Conference on Next-Generation Analyst. SPIE, Baltimore, MD
Roberts Jr JC (2007) State of the art: coordinated and multiple views in exploratory visualizations. In: CMV’07 Fifth International Conference on Coordinated and Multiple Views in Exploratory Visualization, Zurich, Switzerland, pp 61–71
Steinberg AN, White F, Bowman CL (1998) Revisions to the JDL model. In: Proceedings of the Joint NATO/IRIS Conference, Quebec City, QC, Canada
Tang J, Cebrian M, Giacobe N, Kim H-W, Kim T, Wickert D (2011) Reflecting on the DARPA red balloon challenge. Trans ACM 54(4):78–85
Thomas JJ, Cook KA (2005a) Illuminating the path: the research and development agenda for visual analytics. IEEE Computer Society, Washington, DC
Thomas JJ, Cook KA (2005) The science of analytical reasoning. In: Illuminating the path: the research and development agenda for visual analytics. National Visualization and Analytics Center
Wang BM, Woodruff A, Kuchinsky A (2000) Guidelines for using multiple views in information visualization. In: Proceedings of the Working Conference on Advanced Visual Interfaces. ACM, New York, NY, pp 110–119
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Hall, D., Cai, G., Graham, J. (2016). Empowering the Next-Generation Analyst. In: Rogova, G., Scott, P. (eds) Fusion Methodologies in Crisis Management. Springer, Cham. https://doi.org/10.1007/978-3-319-22527-2_11
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DOI: https://doi.org/10.1007/978-3-319-22527-2_11
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