Monthly Archives: January 2012

Visual Analytics

 


Visual  analytics
 provides  technology  that  combines  the  strengths  of  human  and  electronic  data processing.  Visualization  becomes  the  medium  of  a  semi-automated  analytical  process,  where human  and  machine  cooperate using  their  respective  distinct  capabilities  for  the  most  effective results. The user has to be the ultimate authority in giving the direction of the analysis along his or her  specific  task.  At  the  same  time,  the  system  has  to  provide  effective  means  of  interaction  to concentrate  on  this  specific  task.  On  top  of  that,  in  many  applications  different  people  work  along the path from data to decision. A visual representation will sketch this path and provide a reference for their collaboration across different tasks and abstraction levels.

The diversity of these tasks cannot be tackled with a single theory. Visual analytics research is highly interdisciplinary  and  combines various  related  research  areas  such  as  visualization,  data  analysis, data  management,  data  fusion,  statistics  and  cognition  science (among  others).  One  goal  of  this project  is  to  demonstrate  that  joining  research  efforts  from  these  various  fields  can  lead  to  novel, highly  effective  analysis  tools,  contributing  solutions  to  the  information  overload  problem  in  many important domains. Because visual analytics is an integrating discipline, the existing solutions in the area  of  critical  infrastructures  and  crisis  response  will  be  integrated  to  support  decision  making  in situations where multiple critical infrastructures are relevant.

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Critical Infrastructures


Critical infrastructures
 are complex socio-technical systems. Their components and sub-systems are characterized by specific behaviors which result from the applied rules of physics, from technical specifications, and the established control regime. The resulting behaviors tend to be quite complex under normal and under exceptional conditions. Dependencies between critical infrastructures result in more complex behavior, including cascading failures and nonlinear effects. This holds for dependencies within the same sector and across different sectors. Power grids, telecommunication networks, transportation, food, public health, and logistic systems are tightly connected – but managed largely independently from each other. Failures in one network can propagate within this network; for example, blackouts in power grids, traffic contingencies in telecommunication or logistic networks. More significantly, they can propagate to other critical infrastructures (CI) within the same domain (power blackouts) and to depending CIs in other sectors (power blackouts or telecommunication failures affecting all other CIs). Risk in one network directly influences risk in a depending one. Whereas information management and control within one critical infrastructure is well adapted to the needs of risk management within its own network there is currently no appropriate approach towards a holistic risk management taking risks from different critical infrastructures into account.

Things are already complex today – and they will get even more complex in the years to come. New technologies and system structures are evolving:

  • in the power sector regenerative and distributed energy production, large distances of power transport, power trading, smart metering and smart grids
  • in telecommunication networks an integration of telecommunication, Internet, and mobile networks
  • in logistics a significantly increased role of information and communication technologies
  • In food safety and protection, logistics management, efficient distribution and interconnected production networks, lead to consumer items with ingredients from dozens of countries that can travel from field to table in only a few days with interrelated dependencies on computer networks, transportation networks, logistics, energy, and finance.
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Information and Communication Technologies


Even more than today, information and communication technologies (ICT) will form the information and  control  backbone  of  all  critical  infrastructures.  This  generates  new  opportunities  for  their effective and efficient management. But at the same time it generates new vulnerabilities. A loss of ICT functionality will severely influence the operation of critical infrastructures. Until recently, large critical infrastructures operated on their own, independent information and control infrastructures. In the future this will be possible only in rare exceptions (for instance, for the European transnational power grid). Most critical infrastructures will rely on external telecommunication networks not under their own control. This generates new dependencies which need adequate treatment.

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Information Management


A key issue for the management and control of such large complex critical infrastructures with their manifold dependencies is information management. For information management within one critical infrastructure the currently existing approaches have to be extended and adapted to the new needs in future networks. The usage of external ICT networks and the growing complexity of information to be managed are the main points. Much more information from different sources has to be processed in much shorter time intervals. Equally important,information from depending critical infrastructures has to be provided and processed in a form enabling holistic risk estimation and management.

Management  and  control  of  large  complex  critical infrastructures  are  done  today  by  highly  skilled and trained experts with significant and indispensable support from sophisticated highly adapted ICT systems. These systems provide three main functionalities:

  • collection and processing of all incoming information from the own network and from related networks
  • analysis of information according to highly adapted, special purpose built-in procedures
  • presentation of information and results in an appropriate form to the human experts.
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Information Modelling


A key issue for such an integrated approach is information modeling. Today’s simulation systems are based  on  special  purpose  data  models  based  on  the  needs  of  the  respective  critical  infrastructure. These  models  look  different  for  power  grids,  for  telecommunication  systems,  and  for  logistic simulators (and for other CIs). In order to manage and simulate dependent CIs an integrated model is needed  allowing  the  integration  of  the  different  special  purpose  models.  These  integrated  models have to be run on simulators which enable the simulation of complex system behaviors in dependent CIs. Different scenarios can be simulated as sequences of events and actions within one CI or crossing the borders between them.

Such federated simulations provide a new integrated component of visual analytics. Not just data but comprehensive simulations of complex system behaviors can be used as basis for complex but highly adapted analytical investigations and special purpose presentations to human decision makers. Novel visual  analytics  systems  to  be  developed  within  the  proposed  collaboration  will  tightly  integrate  CI simulation and analysis with advanced visual interfaces to support effective decision making by the human.

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Decision Making

Even  with  sophisticated  information  and  control  systems,  decision  making in  critical infrastructure  management  is  a challenge. This holds for normal and near-normal operations, and even more for crisis management. The  system  behavior  is  too  complex  to  be  fully  accessible  by  human intuition.  Though  human expertise is an indispensable pre-requisite to manage such complex systems, the analysis of system behavior  and  the  prediction  of  changes  need  special  purpose  simulations  which  take  the  specific modes  of  system  behavior  into  account.  That’s  why  CI  information  and  control  systems  include special purpose simulations (such as, for instance, N-1 contingency analysis in power grids). They are an essential pre-requisite to understand and manage the complexity.

Today, these simulation systems are highly adapted to the specific domains. They are based on the assumption to completely know the state of their critical infrastructures. Both assumptions are not adequate  for  dependent  critical  infrastructures  with  external  ICT  systems.  They  are  not  suited  for holistic risk management in such dependent networks of networks. What is needed is an integrative information  management with  federated  simulations  bringing  the  different  system  behaviors together.

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Project Description

The  goal of  VASA  (Visual  Analytics  for  Security  Applications)  is  to  apply  visual analytics  to  disaster prevention  and  crisis  response,  with  a  focus  on  critical  infrastructures  in  logistics,  transportation, food  safety,  digital  networks  and  power  grids  at  the  national  levels.  The  connectedness  and dependency  of  these  critical  infrastructures  make  the  problem  of  monitoring  and  understanding their functioning and dependencies one of the most complex analytical tasks faced by our societies. Their proper functioning is crucial for the well-being of the population, economic viability, and most of all to prevent loss of life.

Visual  analytics is  the  science  of  analytical  reasoning  facilitated  by  interactive  visual  interfaces.  It provides technology that combines the strengths of human and electronic data processing enabling a semi-automated  analytical  process,  where  humans  and  machines  cooperate using  their  respective distinct capabilities. The VASA project proposes the application of visual analytics to the problems of monitoring  and  understanding  critical  infrastructures,  cascading  infrastructure  effects,  and  to  the management of crisis response. While, for example, there exist detailed models for individual types of infrastructures such as electric power grids, these do not encompass the various interconnections and  interdependencies  one  needs  to  be  aware  of  to  make  risk  estimation  decisions  and  for performing operational risk management. What is therefore required is a mechanism for conjoining the  information  available  for  individual  infrastructure  sectors  and  providing  unified  views  and analytical tools for planning and decision support.

VASA is conceived as a three-year German-US collaboration project from science through prototypes and  demonstrations  to  evaluations  for  transitions  into  practice  which  leverage  other  investments from both countries.

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Universität Konstanz

The Data Analysis and Visualization Research Group (DBVIS) at the University of Konstanz focuses on delivering innovative and high quality research in the fields of Information Visualization, Knowledge Discovery, and Visual Analytics. The research at the University of Konstanz includes all aspects of the data analysis process including the development of novel visualization, interaction, and data analysis techniques. A major issue is to develop scalable visual analytics techniques that tightly couple automated and visual techniques in order to support decision making in large and complex information spaces. In this context, the DBVIS group proposed a number of sophisticated techniques for various application scenarios. For instance, the group successfully developed techniques to monitor high volume data for network security, techniques for the analysis of news streams, and, in collaboration with the University of Charlotte, visual analytics techniques for multimedia data streams. The group has unique competencies, demonstrated in numerous top-class conferences and journal publications.

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Fraunhofer IGD

Fraunhofer IGD (Institute for Computer Graphics Research) is one of 60 research institutes of the Fraunhofer-Gesellschaft. The institute focuses on applied research with the aim of innovation in computer graphics by making the results of basic research available for applications. Through this transfer of knowledge from research to practical applications the IGD contributes to the furthering of technology in European trade and industry.

Fraunhofer IGD focuses on the development of product prototypes (hard- and software) and the realisation of concepts, models, and solutions for computer graphics and its adaptation to specific application requirements. The R&D projects are directly related to current problems in industry, trade, traffic, and services. For the implementation of these projects the departments of IGD have developed excellent competencies in Computer Graphics and its applications. An important research area is information visualisation and Visual Analytics, with a focus on the interactive and semantics-based visualisation of decision-critical information, as well as solutions for the financial industry.

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Fraunhofer IAIS

Fraunhofer IAIS (Institute for Intelligent Analysis and Information Systems) is one of 58 research institutes of the Fraunhofer Society. With its workforce of nearly 280 employees, Fraunhofer IAIS combines the competences and scientific qualities of all engineering disciplines – especially informatics, and mathematics, natural sciences, business economics, geo and social sciences – with profound industry expertise. With a budget of approx. 20 million Euros the institute implements application solutions in the fields of machine learning, multimedia pattern recognition, visual analytics, process intelligence, preventive security, adaptive robotics and cooperating objects.

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