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| Paper: |
Concept for Collaborative and Guided Visual Analytics of Astrophysical and Planetary Data |
| Volume: |
538, ADASS XXXII |
| Page: |
101 |
| Authors: |
Manuela Rauch; Vedran Sabol; Santokh Singh; Lukas Schober; Albert Zijlstra; Iain McDonald; Nick Cox |
| DOI: |
10.26624/JOEV5441 |
| Abstract: |
The immense amount of data collected during space missions, by satellites or telescopes, requires means for analysis and investigation by interested users.
Advanced calculations, including machine learning (ML) methods, are applied to analyse the data and extract insights, while visualization methods provide means for data
exploration and interactive data analysis. Visual analytics tools have proven as a suitable method for investigating complex data and enabling users to spot patterns and draw
conclusions. Due to the complexity of space science and of the associated data analysis
techniques, it might prove difficult for users to successfully obtain the desired insights.
This is either because users do not (yet) possess profound enough knowledge on space
science, e.g., students or hobbyists, or because they are not well-acquainted with all the
details necessary to successfully apply algorithmic and visual techniques for data analysis. Also, in some cases, the desired data analysis results are best achieved when users
with complementary expertise team up and work together. To address these challenges,
we plan to offer visualizations adapted specifically to space data, seamlessly integrate
analytical algorithms within our visual analytics framework, and accompany various
analytical techniques with collaboration and user guidance methods. |
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