What is the Big Data Horizon Prize about?
Many issues impacting society such as public health, climate change, transportation, energy efficiency will benefit from our ability to examine historical records and predict how developments in these areas will evolve. To further improve forecasting systems in these areas of study in terms of scalability, accuracy, speed and use of computational resources, the European Commission is awarding a total budget of EUR 2 million in a new Horizon Prize which will be launched in December 2017.
What do you need to deliver to win the prize?
Winning contestants are expected to develop new solutions to spatiotemporal forecasting. Access to big data will be provided to participants who will attempt to develop new forecasting methods which are able to beat ones currently available. Datasets will include Open Data resources (including satellite imagery of Europe and the Atlantic Ocean, weather forecast data etc.) and private datasets such as electrical grid flows linking power generation to load or usage.
Contestants will be asked to develop solutions in the form of fully functioning software implementations against the available datasets according to a publicly specified algorithm.
This Prize will complement the activities of the Big Data contractual Public Private Partnership (cPPP) which aims to develop Europe's data driven economy.
What are Horizon Prizes?
The Horizon Prizes were introduced as a new instrument to bring solutions to issues which are of critical importance to Europe's citizens and to complement grants and other funding tools for innovation. This type of inducement prize is used to spur investment in a given direction, by specifying a target prior to the performance of the work. Their rationale includes simplification and outcome orientation, increase of private R&I investment in Europe and promotion of ‘out of box’ thinking and entrepreneurship. Building on the first success, more inducement prizes are planned in 2018-2020.
To stay tuned, follow #HorizonPrize on Twitter.