The 11th International Conference on Fuzzy Systems and Data Mining (FSDM 2025)

Abstract: Space astrometry aims to determine stellar parameters like angular positions and proper motions on the celestial sphere based on satellite telescope observations, which allows for building star catalogues and helps to understand the structure of the Universe. Even small astrometric missions pose Big Data problems and require high-performance computers, as billions of observations must be taken into account to achieve high accuracy in the values of stellar parameters. Astrometric solvers implement complex calibration models to compensate for distortions of observations caused by imperfections in telescope optics and detectors, deviations in satellite attitude, relativistic effects of light bending, etc. We propose leveraging visual data mining to validate the astrometric solution and its underlying calibration model, as well as to profile the performance and numerical stability of astrometric solvers. If the visual means involved are designed well, they possess both cognitive clarity and visual aesthetics. Herewith, visual aesthetics is not only a nice-to-have feature but also an essential part of visual data mining with twofold meaning. First, it makes the research process and results more attractive for scientists, and second, it allows exporting the research to a wider audience, having not only scientific but also artistic and promotional value. In this work, we integrate the ontology-driven semantic visual data mining platform SciVi with the high-performance astrometric solver we made for the Japan Astrometry Satellite Mission for INfrared Exploration (JASMINE). Using the adaptive data processing and rendering capabilities of SciVi, we create an artistic visualisation of the solving process to profile the solver and promote JASMINE.

Biography: Dr. Konstantin Ryabinin is a research worker at the Astronomisches Rechen-Institut (ARI) (https://zah.uni-heidelberg.de/de/institute-des-zah/ari), Center for Astronomy of Heidelberg University, Germany. Currently, he is conducting his Computational Science, Software Engineering, and Data Mining research in a collaborative project on data reduction within the Japan Astrometry Satellite Mission for INfrared Exploration (JASMINE) (https://www.isas.jaxa.jp/en/missions/spacecraft/future/jasmine.html).
He graduated from the mechanics and mathematics faculty of Perm State University in 2011 and defended his PhD in Computer Science in 2015. Since 2011, he has been deeply involved in research of Scientific Visualisation, Visual Analytics, Human-Computer Interaction, Computational Geometry, Computer Graphics, Multimedia, Ontology Engineering, Semantic Data Mining, Multiplatform Portability, Ubiquitous Computing, and the Internet of Things. He is a leading developer of the ARI JASMINE Astrometric Solver, the SciVi visual analytics platform, and the NChart3D data visualization library. He published more than 70 papers in scientific journals and proceedings of international conferences in the area of his research expertise.