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\n  \n 2018\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Sense-making Strategies in Explorative Intelligence Analysis of Network Evolutions.\n \n \n \n\n\n \n Doppler Haider, J.; Gastecker, B.; Pohl, M.; Seidler, P.; Kodagoda, N.; and Wong, B. W.\n\n\n \n\n\n\n Behaviour & Information Technology. 2018.\n \n\n\n\n
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@article{doppler_haider_sense-making_2018,\n\ttitle = {Sense-making {Strategies} in {Explorative} {Intelligence} {Analysis} of {Network} {Evolutions}},\n\tdoi = {10.1080/0144929X.2018.1519036},\n\tjournal = {Behaviour \\& Information Technology},\n\tauthor = {Doppler Haider, Johanna and Gastecker, Bettina and Pohl, Margit and Seidler, Patrick and Kodagoda, Neesha and Wong, BL William},\n\tyear = {2018},\n}\n\n
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\n  \n 2017\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n Sense-making Strategies for the Interpretation of Visualizations–Bridging the Gap between Theory and Empirical Research.\n \n \n \n\n\n \n Pohl, M.; and Doppler Haider, J.\n\n\n \n\n\n\n Multimodal Technologies and Interaction, 1(3): 16. 2017.\n tex.publisher= Multidisciplinary Digital Publishing Institute\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{pohl_sense-making_2017,\n\ttitle = {Sense-making {Strategies} for the {Interpretation} of {Visualizations}--{Bridging} the {Gap} between {Theory} and {Empirical} {Research}},\n\tvolume = {1},\n\tnumber = {3},\n\tjournal = {Multimodal Technologies and Interaction},\n\tauthor = {Pohl, Margit and Doppler Haider, Johanna},\n\tyear = {2017},\n\tnote = {tex.publisher= Multidisciplinary Digital Publishing Institute},\n\tpages = {16},\n}\n\n
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\n \n\n \n \n \n \n \n How Analysts Think: Sense-making Strategies in the Analysis of Temporal Evolution and Criminal Network Structures and Activities.\n \n \n \n\n\n \n Doppler Haider, J.; Seidler, P.; Pohl, M.; Kodagoda, N.; Adderley, R.; and Wong, B. L. W.\n\n\n \n\n\n\n In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, volume 61, pages 193–197, Baltimore, USA, October 2017. \n \n\n\n\n
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@inproceedings{doppler_analysts_2017,\n\taddress = {Baltimore, USA},\n\ttitle = {How {Analysts} {Think}: {Sense}-making {Strategies} in the {Analysis} of {Temporal} {Evolution} and {Criminal} {Network} {Structures} and {Activities}},\n\tvolume = {61},\n\tdoi = {10.1177/1541931213601532},\n\tbooktitle = {Proceedings of the {Human} {Factors} and {Ergonomics} {Society} {Annual} {Meeting}},\n\tauthor = {Doppler Haider, Johanna and Seidler, Patrick and Pohl, Margit and Kodagoda, Neesha and Adderley, Rick and Wong, B. L. William},\n\tmonth = oct,\n\tyear = {2017},\n\tpages = {193--197},\n}\n\n
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\n  \n 2016\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n Design for Intelligence Analysis of Complex Systems: Evolution of Criminal Networks.\n \n \n \n\n\n \n Seidler, P.; Haider, J.; Kodagoda, N.; Wong, B. L. W.; Pohl, M.; and Adderley, R.\n\n\n \n\n\n\n In 2016 European Intelligence and Security Informatics Conference (EISIC), pages 140–143, Uppsala, Sweden, August 2016. \n \n\n\n\n
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@inproceedings{seidler_design_2016,\n\taddress = {Uppsala, Sweden},\n\ttitle = {Design for {Intelligence} {Analysis} of {Complex} {Systems}: {Evolution} of {Criminal} {Networks}},\n\tshorttitle = {Design for {Intelligence} {Analysis} of {Complex} {Systems}},\n\tdoi = {10.1109/EISIC.2016.036},\n\tabstract = {Intelligence analysts are at the forefront to provide decision makers with a greater picture of current situational context. Their main task is to identify relevant pieces of information from disparate systems and growing amounts of data while often lacking the appropriate tools. We propose a visual analytics approach to support analysts in monitoring and reasoning about the dynamics in a complex system. In our approach, we systematically map relations onto the user interface and support both overview and provenance over temporal dynamics. We further map explicitly otherwise tacit organisational knowledge. Our use case is based on a crime system taking the perspective of criminal network analysis tasks. Our analytics extract force-prioritised, weighted co-offender networks, which are represented through both a graph and a matrix visualisation, incorporating the evolution of relationships between offenders. The developed tools were evaluated in a study with domain experts, with the goal to assess tool utility and to investigate the appropriateness of the tool with the end user.},\n\tbooktitle = {2016 {European} {Intelligence} and {Security} {Informatics} {Conference} ({EISIC})},\n\tauthor = {Seidler, P. and Haider, J. and Kodagoda, N. and Wong, B. L. W. and Pohl, M. and Adderley, R.},\n\tmonth = aug,\n\tyear = {2016},\n\tkeywords = {Adjacency Matrix, Bars, Color, Complex systems, Context, Force, Law enforcement, Time-varying Data, User Interface, Visual analytics, Visualization, Visualization of Networks, complex system, criminal network analysis, data analysis, data visualisation, evaluation, force-prioritised weighted co-offender networks, graph, graph theory, law administration, matrix algebra, matrix visualisation, organisational aspects, tacit organisational knowledge, temporal dynamics, tool utility},\n\tpages = {140--143},\n}\n\n
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\n Intelligence analysts are at the forefront to provide decision makers with a greater picture of current situational context. Their main task is to identify relevant pieces of information from disparate systems and growing amounts of data while often lacking the appropriate tools. We propose a visual analytics approach to support analysts in monitoring and reasoning about the dynamics in a complex system. In our approach, we systematically map relations onto the user interface and support both overview and provenance over temporal dynamics. We further map explicitly otherwise tacit organisational knowledge. Our use case is based on a crime system taking the perspective of criminal network analysis tasks. Our analytics extract force-prioritised, weighted co-offender networks, which are represented through both a graph and a matrix visualisation, incorporating the evolution of relationships between offenders. The developed tools were evaluated in a study with domain experts, with the goal to assess tool utility and to investigate the appropriateness of the tool with the end user.\n
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\n \n\n \n \n \n \n \n \n Who, Where, When and with Whom? Evaluation of Group Meeting Visualizations.\n \n \n \n \n\n\n \n Kriglstein, S.; Haider, J.; Wallner, G.; and Pohl, M.\n\n\n \n\n\n\n In Jamnik, M.; Uesaka, Y.; and Elzer Schwartz, S., editor(s), Diagrammatic Representation and Inference: 9th International Conference, Diagrams 2016, Philadelphia, PA, USA, August 7-10, 2016, Proceedings, pages 235–249. Springer International Publishing, Cham, 2016.\n \n\n\n\n
\n\n\n\n \n \n \"Who,Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@incollection{kriglstein_who_2016,\n\taddress = {Cham},\n\ttitle = {Who, {Where}, {When} and with {Whom}? {Evaluation} of {Group} {Meeting} {Visualizations}},\n\tisbn = {978-3-319-42333-3},\n\turl = {http://dx.doi.org/10.1007/978-3-319-42333-3_19},\n\tbooktitle = {Diagrammatic {Representation} and {Inference}: 9th {International} {Conference}, {Diagrams} 2016, {Philadelphia}, {PA}, {USA}, {August} 7-10, 2016, {Proceedings}},\n\tpublisher = {Springer International Publishing},\n\tauthor = {Kriglstein, Simone and Haider, Johanna and Wallner, Günter and Pohl, Margit},\n\teditor = {Jamnik, Mateja and Uesaka, Yuri and Elzer Schwartz, Stephanie},\n\tyear = {2016},\n\tdoi = {10.1007/978-3-319-42333-3_19},\n\tpages = {235--249},\n}\n\n
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\n  \n 2015\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n Supporting Sense-Making and Insight Processes in Visual Analytics by Deriving Guidelines from Empirical Results.\n \n \n \n\n\n \n Haider, J.; Pohl, M.; Pallaris, C.; and Wong, W. B.\n\n\n \n\n\n\n In Proceedings of the Internation Summer School on Visual Computing 2015, pages 59–68. Fraunhofer IGD, Rostock, Germany, 2015.\n Vortrag: International Summer School on Visual Computing 2015, Rostock, Germany; 2015-08-17 – 2015-08-21\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@incollection{haider_supporting_2015,\n\ttitle = {Supporting {Sense}-{Making} and {Insight} {Processes} in {Visual} {Analytics} by {Deriving} {Guidelines} from {Empirical} {Results}},\n\tisbn = {978-3-8396-0960-6},\n\tabstract = {We need analytics systems that are optimised to human\nsense-making and reasoning due to the amount of data that is available\nfor intelligence analysis. The purpose of Visual Analytics is to enable\nand discover insights in complex data through automatic computation\nand interactive visualisation. Sense-making describes the process of giving\nmeaning to one’s experience in order to understand events. To do so\ninteractivity is the essential key to make sense out of data because the\nlimits of human capacities are reached quickly. It is, however, not suffi-\nciently clear how analysts derive knowledge from information systems. In\nthis work, we investigate interaction processes with visual analytics tools\nto improve the understanding on how this meaning is generated. Additionally,\nguidelines based on empirical research and user requirements\nare presented.},\n\tbooktitle = {Proceedings of the {Internation} {Summer} {School} on {Visual} {Computing} 2015},\n\tpublisher = {Fraunhofer IGD, Rostock, Germany},\n\tauthor = {Haider, Johanna and Pohl, Margit and Pallaris, Chris and Wong, William B.L.},\n\tyear = {2015},\n\tnote = {Vortrag: International Summer School on Visual Computing 2015, Rostock, Germany; 2015-08-17 – 2015-08-21},\n\tkeywords = {decision making, design recommendations, insight model},\n\tpages = {59--68},\n}\n\n
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\n We need analytics systems that are optimised to human sense-making and reasoning due to the amount of data that is available for intelligence analysis. The purpose of Visual Analytics is to enable and discover insights in complex data through automatic computation and interactive visualisation. Sense-making describes the process of giving meaning to one’s experience in order to understand events. To do so interactivity is the essential key to make sense out of data because the limits of human capacities are reached quickly. It is, however, not suffi- ciently clear how analysts derive knowledge from information systems. In this work, we investigate interaction processes with visual analytics tools to improve the understanding on how this meaning is generated. Additionally, guidelines based on empirical research and user requirements are presented.\n
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\n \n\n \n \n \n \n \n Exploring the Challenges of Implementing Guidelines for the Design of Visual Analytics Systems.\n \n \n \n\n\n \n Haider, J.; Pohl, M.; Hillemann, E.; Nussbaumer, A.; Attfield, S.; Passmore, P.; and Wong, B. L. W.\n\n\n \n\n\n\n In Proceedings of the Human Factors and Ergonomics Society 59th Annual Meeting - 2015, Los Angeles, 2015. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{haider_exploring_2015,\n\taddress = {Los Angeles},\n\ttitle = {Exploring the {Challenges} of {Implementing} {Guidelines} for the {Design} of {Visual} {Analytics} {Systems}},\n\tdoi = {10.1177/1541931215591053},\n\tabstract = {Intelligence analysis activities are increasingly seen as a sense-making activity. Information systems supporting\nthese activities have, therefore, to be designed in a way to enable analysts to engage in sensemaking\nin an efficient manner. In the context of the VALCRI project, we developed guidelines for an appropriate\ndesign of intelligence analysis systems. Such guidelines can be very valuable in the design process,\nbut their application is sometimes not straightforward. We describe such problems and also suggest\npossible solutions for these application problems within the context of intelligence analysis.},\n\tbooktitle = {Proceedings of the {Human} {Factors} and {Ergonomics} {Society} 59th {Annual} {Meeting} - 2015},\n\tauthor = {Haider, Johanna and Pohl, Margit and Hillemann, Eva-Catherine and Nussbaumer, Alexander and Attfield, Simon and Passmore, Peter and Wong, B. L. William},\n\tyear = {2015},\n}\n\n
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\n Intelligence analysis activities are increasingly seen as a sense-making activity. Information systems supporting these activities have, therefore, to be designed in a way to enable analysts to engage in sensemaking in an efficient manner. In the context of the VALCRI project, we developed guidelines for an appropriate design of intelligence analysis systems. Such guidelines can be very valuable in the design process, but their application is sometimes not straightforward. We describe such problems and also suggest possible solutions for these application problems within the context of intelligence analysis.\n
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\n \n\n \n \n \n \n \n Guidelines for Sense-making in Intelligence Analysis.\n \n \n \n\n\n \n Pohl, M.; Haider, J.; Pallaris, C.; and Wong, W. B.\n\n\n \n\n\n\n In European Intelligence and Security Informatics Conference, pages 177, 2015. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{pohl_guidelines_2015,\n\ttitle = {Guidelines for {Sense}-making in {Intelligence} {Analysis}},\n\tdoi = {10.1109/EISIC.2015.45},\n\tabstract = {Due to the vast amount of data that needs to be processed in the field of intelligence analysis, visual analytic systems should be optimised with regard to sense-making and reasoning. The main problem is that it is not clear how knowledge is derived from information systems. We outline the benefits of empirically derived design guidelines and present newly created sense-making recommendations for the work of analysts. Their practical relevance is given by an extensive requirement analysis and their relations to theoretical models of the intelligence analysis process described in the literature.},\n\tbooktitle = {European {Intelligence} and {Security} {Informatics} {Conference}},\n\tauthor = {Pohl, Margit and Haider, Johanna and Pallaris, Chris and Wong, William B.L.},\n\tyear = {2015},\n\tpages = {177},\n}\n
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\n Due to the vast amount of data that needs to be processed in the field of intelligence analysis, visual analytic systems should be optimised with regard to sense-making and reasoning. The main problem is that it is not clear how knowledge is derived from information systems. We outline the benefits of empirically derived design guidelines and present newly created sense-making recommendations for the work of analysts. Their practical relevance is given by an extensive requirement analysis and their relations to theoretical models of the intelligence analysis process described in the literature.\n
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\n  \n 2013\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Defining Visual User Interface Design Recommendations for Highway Traffic Management Centres.\n \n \n \n\n\n \n Haider, J.; Pohl, M.; and Fröhlich, P.\n\n\n \n\n\n\n In 17th International Conference, pages 204–209, 2013. \n \n\n\n\n
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@inproceedings{haider_defining_2013,\n\ttitle = {Defining {Visual} {User} {Interface} {Design} {Recommendations} for {Highway} {Traffic} {Management} {Centres}.},\n\tdoi = {10.1109/IV.2013.27},\n\tabstract = {The design of traffic management systems is challenging because of the large amount of dynamic data which has to be analysed by operators. Systems have to be designed appropriately to enable operators to react efficiently and quickly. The following paper gives an overview of guidelines derived from empirical research in cognitive psychology and HCI. These guidelines specifically address the design of traffic management systems. The following topics seem to be especially relevant: visual perception, geographic data, perception of motion, monitoring of tasks and interaction. These guidelines can help to design usable and useful systems.},\n\tbooktitle = {17th {International} {Conference}},\n\tauthor = {Haider, Johanna and Pohl, Margit and Fröhlich, Peter},\n\tyear = {2013},\n\tpages = {204--209},\n}\n\n
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\n The design of traffic management systems is challenging because of the large amount of dynamic data which has to be analysed by operators. Systems have to be designed appropriately to enable operators to react efficiently and quickly. The following paper gives an overview of guidelines derived from empirical research in cognitive psychology and HCI. These guidelines specifically address the design of traffic management systems. The following topics seem to be especially relevant: visual perception, geographic data, perception of motion, monitoring of tasks and interaction. These guidelines can help to design usable and useful systems.\n
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