EVEREST: a virtual research environment for the Earth Sciences

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Helen M Glaves, British Geological Survey Keyworth, Nottinghamshire, NG12, United Kingdom, Fulvio Marelli, European Space Research Institute, Frascati, Italy and Mirko Albani, European Space Agency/ESRIN, Frascati, Italy
There is an increasing requirement for researchers to work collaboratively using common resources whilst being geographically dispersed. By creating a virtual research environment (VRE) using a service oriented architecture (SOA) tailored to the needs of Earth Science (ES) communities, the EVEREST project will provide a range of both generic and domain specific data management services to support a dynamic approach to collaborative research. EVER-EST will provide the means to overcome existing barriers to sharing of Earth Science data and information allowing research teams to discover, access, share and process heterogeneous data, algorithms, results and experiences within and across their communities, including those domains beyond Earth Science. Data providers will be also able to monitor user experiences and collect feedback through the VRE, improving their capacity to adapt to the changing requirements of their end-users. The EVER-EST e-infrastructure will be validated by four virtual research communities (VRC) covering different multidisciplinary ES domains: including ocean monitoring, selected natural hazards (flooding, ground instability and extreme weather events), land monitoring and risk management (volcanoes and seismicity). Each of the VRC represents a different collaborative use case for the VRE according to its own specific requirements for data, software, best practice and community engagement. The diverse use cases will demonstrate how the VRE can be used for a range of activities from straight forward data/software sharing to investigating ways to improve cooperative working. Development of the EVEREST VRE will leverage on the results of several previous projects which have produced state-of-the-art technologies for scientific data management and curation as well those initiatives which have developed models, techniques and tools for the preservation of scientific methods and their implementation in computational forms such as scientific workflows.