I am an astrophysics researcher working at the Open University in the UK. Modern astrophysical instruments provide exquisite, high-quality data in unprecedented volumes and with increasing complexity and diversity. Analysing these data is a significant challenge facing modern astrophysics research. My research explores the ways that citizen science can help to unlock the scientific insights that these and future data contain. Notwithstanding the increasing power and prevalence of Deep Learning algorithms, human volunteers continue to outperform automatic analyses in terms of intuitive perceptiveness and the potential for serendipitous discovery.
Discovering data with the ESCAPE Science Analysis Platform
We present a suite of online data discovery tools that have been developed for the ESCAPE Science Analysis Platform (ESAP). ESCAPE (European Science Cluster of Astronomy & Particle physics ESFRI research infrastructures) brings together the astronomy, astroparticle and particle physics communities to establish a single collaborative cluster of next generation facilities to build the astronomy and particle physics cell of the European Open Science Cloud.
One of the core components of the ESAP is a generic interface that enables discovery of Virtual Observatory (VO) resources by querying the VO registry. Once suitable VO resources have been discovered, ESAP provides a flexible interface to select and retrieve specific subsets of data and stage them for interactive or batch data analysis.
The ESAP data discovery framework also enables support for non-VO data archives with minimal developer effort. As an example, we show how citizen science classification data from the Zooniverse platform can be accessed via ESAP.