aflak: Pluggable visual programming environment with quick feedback loop tuned for multi-spectral astrophysical observations

Published by Issei FUJISHIRO on

Malik Olivier Boussejra, Kazuya Matsubayashi, Yuriko Takeshima, Shunya Takekawa, Rikuo Uchiki, Makoto Uemura, Issei Fujishiro

Astronomical Data Analysis Software and System XXVIII ASP Conference Series, Vol. 523, pp. 245―248, 2019


In the age of big data and data science, some may think that artificial intelligence would bring analytical solution to every problem. However, we argue that there is still ample room left for human insight and exploration thanks to visualization technologies. New discoveries are not made by AI (yet!). This is true in all scientific domains, including astrophysics. With the improvements of telescopes and proliferation of sky surveys there is always more data to analyze, but not so many astronomers. We present aflak, a visualization environment to open astronomical datasets and analyze them. This paper’s contribution lies in that we leverage visual programming techniques to conduct fine-grained, astronomical transformations, filtering and visual analyses on multi-spectral datasets with the possibility for the astronomers to interactively fine-tune all the interacting parameters. By visualizing the computed results in real time as the visual program is designed, aflak puts the astronomer in the loop, while managing data provenance at the same time.

Publication page in 2019 is here


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