Astronomical research in the next decade: trends, barriers and needs in data access, management, visualization and analysis
2020-11-12, 12:00–12:15, Times in UTC

Astronomy is entering uncharted territory. The advent of next-generation observing facilities, such as the Large Synoptic Survey Telescope (LSST) and the Square Kilometre Array (SKA), able to map large regions of the sky with unprecedented detail, will result in a data deluge overwhelming the current management and analysis capabilities of the astrophysics community.

In the era of the PB-scale datasets, NEANIAS (Novel EOSC Services for Emerging Atmosphere, Underwater & Space Challenges) emerges as a unique opportunity to tackle the needs of the next-decade astronomy in advance. This ambitious H2020 project foresees the creation of a set of services aimed at boosting astronomers' capabilities in three major fronts: data management and visualization, enabling access to large datasets in a straightforward way under FAIR principles and exploiting novel visualization techniques such as Augmented Reality; map-making and mosaicking, providing workflows to generate large-scale multidimensional maps and fostering multimessenger astronomy; and data analysis supported with Machine Learning techniques, automating the extraction and characterization of compact sources and extended structures from all-sky surveys.

However, the development and deployment of such services represent a substantial scientific and technological challenge, that requires an accurate portrait of the current research landscape in the astrophysics community. With the aim of better understanding the current barriers and needs in space research, we have conducted a survey among astrophysicists and data scientists from several research institutions across Europe, including also the private sector, spanning a wide range of disciplines and expertise levels. In this talk, we will present the preliminary results of the survey, with a particular emphasis on the adoption of Machine Learning techniques and Open Science practices. This research opens a direct communication channel between NEANIAS and the scientific community, providing valuable inputs that will allow us to better tailor the foreseen services to actual research requirements. In this way, we will create a solid foundation to face the astronomical challenges of the next decade.


Theme – Machine Learning, Statistics, and Algorithms, Open Source Software and Community Development in Astronomy, Other