Giving a major boost to open science in Europe, the Commission has presented its blueprint for cloud-based services and world-class data infrastructure to ensure science, business and public services reap benefits of big data revolution.
By bolstering and interconnecting existing research infrastructure, the Commission plans to create a new European Open Science Cloud that will offer Europe's 1.7 million researchers and 70 million science and technology professionals a virtual environment to store, share and re-use their data across disciplines and borders. This will be underpinned by the European Data Infrastructure, deploying the high-bandwidth networks, large scale storage facilities and super-computer capacity necessary to effectively access and process large datasets stored in the cloud.
With the adoption of the Digital Single Markets strategy on May 6, the Commission announced the launch of a cloud for research data—the research open science cloud. The European Open Science Cloud aims to create a trusted environment for hosting and processing research data to support E.U. science in its global leading role.
Commissioner Moedas first flagged the initiative at the ERA of Innovation Conference, in June 2015. In a joint blog post, Commissioners Oettinger and Moedas further explained that the initiative “will combine existing and future data infrastructures, offering secure and seamless access to European researchers for storing, managing and processing data from different sources.”
The Commission appointed a High Level Expert Group on the European Open Science Cloud to advise on the scientific services to be provided on the cloud and on its governance structure.
The initiative reinforces open science, open innovation and open to the world policies. It will foster best practices of global data findability and accessibility (FAIR data), help researchers get their data skills recognized and rewarded (careers, altmetrics); help address issues of access and copyright (IPR) and data subject privacy; allow easier replicability of results and limit data wastage e.g. of clinical trial data (research integrity); contribute to clarification of the funding model for data generation and preservation, reducing rent-seeking and priming the market for innovative research services e.g. advanced TDM (new business models).