Development of Scientific Data Applications for Science Cloud Platforms
In the era of big data and cloud storage and computing, new ways for scientists to approach their research are emerging, which impact directly how science progresses and discoveries are made. For astrophysics and particle physics, initiatives such as ESA Datalabs and ESCAPE aim to offer science data processing and analysis platforms to researchers to help them explore increasingly big data sets generated by space missions and large facilities. In this context there is also a need to provide sophisticated and targeted science data applications to be deployed in different cloud environments.
We will present ongoing inter-linked projects that address this need for cloud-deployed applications for the scientific exploitation of space- and ground-based astrophysics and planetary science data. These projects bring together scientists and engineers from public institutions and private actors and leverage artificial intelligence and human intelligence to provide collaborative, cloud-enabled thematic science applications focussed for the global space science community. Topics include Gaia science, Lunar exploration, data fusion tools for the JWST MIRI instrument, and machine learning tools for selected use cases in planetary science.
Our goal is to deploy containerised Scientific Applications and similar initiatives for uptake by the space science and astrophysics community to discover and exploit new science products in an open and FAIR approach.