ARIEL Data Challenge Series launched to build global community for exoplanet data solutions
ARIEL, has launched a global competition series to find innovative solutions for the interpretation and analysis of exoplanet data. The first ARIEL Data Challenge invites professional and amateur data scientists around the world to use Machine Learning (ML) to remove noise from exoplanet observations caused by star-spots and by instrumentation. The ARIEL ML contest has been selected as a Discovery Challenge by the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD). The closing date is Thursday 15th August.
The ARIEL Data Challenge series was announced in April at the UK Exoplanet Community Meeting (EXOM) 2019 in London. A second ARIEL Data Challenge that focuses on the retrieval of spectra from simulations of cloudy and cloud-free super-Earth and hot-Jupiter data was also launched in April. A further data analysis challenge to create pipelines for faster, more effective processing of the raw data gathered by the mission will be launched in June at the EWASS conference in Lyon.
Outcomes from all three ARIEL Data Challenges will be discussed at the ECMLPKDD in Würzburg from 16-20th September and at the EPSC-DPS Joint Meeting 2019, which takes place in Geneva during the same week.