Semiotic Approach in the Development of Interactive Visual Analytics Systems

Author:

Zakharova Alena1ORCID,Vekhter Evgenia2ORCID

Affiliation:

1. Bryansk State Technical University

2. Tomsk Polytechnic University

Abstract

Increasing information saturation in all spheres of life entails accumulation of large amounts of data that must be perceived, processed and decisions must be made on their basis. Therefore, the issues of interaction with data and of visual analytics require solutions at a new level. The authors investigate communication between the user and the data, highlight a number of negative trends that prevent effective use of visualization in solving practical problems, formulate aspects of subjective influence on the decision-making procedure, namely those leading to significant decrease in the efficiency of visual analytics systems. The paper proposes an approach to the problem of reasonable use of existing and potential visualization capabilities for solving data analysis problems and making control decisions. A significant factor hindering the development of visual analytics is a lack of a model for coordinated use of computational and subjective resources corresponding to the technical level of computer visualization capable of ensuring close communication between the researcher and the available data. The paper describes an approach based on the concept of visual communication, the properties of which are determined on the basis of a number of key concepts of semiotics and linguistics.

Funder

Russian Foundation for Basic Research

Publisher

MONOMAX Limited Liability Company

Reference11 articles.

1. Blascheck, T., John, M., Kurzhals, K., Koch, S., Ertl, T.: VA2 : A Visual Analytics Approach for Evaluating Visual Analytics Applications. IEEE Transactions on Visualization and Computer Graphics. 22(1), 61–70 (2016). doi: 10.1109/TVCG.2015.2467871

2. Sacha, D., Sedlmair, M., Zhang, L., Lee, J.A., Weiskopf, D., North, S., Keim, D.: HumanCentered Machine Learning Through Interactive Visualization: Review and Open Challenges. In: ESANN 2016 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pp. 641–646. i6doc.com publ, Bruges, Belgium (2016).

3. Massel L.V., Massel A.G., Ivanov R.A.: Integration of Visual Analytics, Cognitive Graphics and Semantic Modeling in Semiotic Intelligent Systems for Decision Support. In: Proceeding of International Workshop on Contingency Management, Intelligent, AgentBased Computing and Cyber Security in Critical Infrastractures CM/IA/CS/CI-2016. pp. 19–22. Melentiev Energy Systems Institute; Russian Academy of Science Siberian Branch, Irkutsk, Russia (2016).

4. Crouser, R.J., Franklin, L., Endert, A., Cook, K.: Toward Theoretical Techniques for Measuring the Use of Human Effort in Visual Analytic Systems. IEEE Transactions on Visualization and Computer Graphics. 23(1), 121–130 (2017). doi: 10.1109/TVCG.2016.2598460

5. Batch A., Elmqvist, N.: The Interactive Visualization Gap in Initial Exploratory Data Analysis. IEEE Transactions on Visualization and Computer Graphics. 24(1), 278–287 (2018). doi: 10.1109/TVCG.2017.2743990

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