ISSN 2079-3537      

Scientific Visualization
Issue Year: 2016
Quarter: 4
Volume: 8
Number: 4
Pages: 1 - 14
Authors: K.V. Ryabinin (Russian Federation), S.I. Chuprina (Russian Federation), A.Yu. Bortnikov (Russian Federation)
The paper is recommended by program committee of 26th International Conference on Computer Graphics and Vision GraphiCon’2016.
Address: K.V. Ryabinin
Perm State National Research University, Perm, Russian Federation

S.I. Chuprina
Perm State National Research University, Perm, Russian Federation

A.Yu. Bortnikov
Perm State National Research University, Perm, Russian Federation
Abstract: This article describes the novel method to tackle challenges of scientific visualization systems’ adaptation to application domain phenomena. The authors suggest model-based approach to scientific visualization systems building based on ontology engineering methods. This approach enables to defeat such drawbacks of modern scientific visualization systems as a lack of high-level tools to adapt to varying third-party data sources (software and hardware solvers, data storages, etc.) and multiplatform portability. According to the suggested approach, the visualization system is driven by knowledge about graphical objects’ and scenes’ properties, specifics of the tasks being solved as well as hardware and software infrastructure. These different kinds of knowledge are stored as ontologies, which are formal models of application domains including a set of concepts with their definitions, a set of relations between the concepts and, if needed, a set of axioms describing semantic restrictions and laws imposed for concepts and relations. Using model-driven architecture enables to modify system behavior without changing of the source code. The suggested approach ensures a high-level tuning both of rendering and feedback to solver (allowing to start/stop the solver and to change its input data). Developed software and used technologies provide a multiplatform portability of the visualization system preserving a high efficiency of the rendering. The described approach has been used as a basis for implementation of multiplatform client-server scientific visualization system named SciVi, which has been successfully used to solve a number of practical and important scientific problems.
This article describes the new capabilities of the system SciVi, such as development of intuitive data filtering subsystem and thin Web-client.
SciVi data filtering subsystem enables to preprocess the data, which are to be visualized to suit the personal preferences of users, for example, sampling data for a certain period only. SciVi filtering mechanism has two parts: primary preprocessing on the server side and final preprocessing on the client side. The primary preprocessing goal is to satisfy most common user’s needs to change data generated by solver. The final preprocessing goal is to fine-tune data for special research cases. To tune the data filtering high-level graphical user interface based on data flow diagram is used.
Thin Web-client allows using SciVi on desktop computers and mobile device without any additional software installation.
Language: Russian

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