by Keith G. Jeffery and Pierre Guisset (ERCIM)

How researchers collaborate is per se a research topic! Many scientific problems are related across different domains: for example, the global climate changes involve knowledge from eco-system, ocean, atmosphere and earth as well as from energy science and human-related activity modelling.  Scientists face great challenges in handling collaboration among different disciplines and in modelling and discovering knowledge in massively available data from a wide diversity of domains. Today, data-driven approaches are considered as good alternatives to drive scientific research activities.

by Keith G Jeffery

Research Infrastructures and their research communities are heterogeneous. This is a barrier to one community (re-)using the assets of another. VRE4EIC aims to overcome this heterogeneity.

by Yi Yin and Anneke Zuiderwijk (Delft University of Technology)

Collaboration among researchers from different disciplines is becoming an essential ingredient of scientific research. In order to solve increasingly complex scientific and social conundrums, research data needs to be shared among researchers from different disciplines. New technologies pave the way for unlimited potential for preserving, analysing and sharing research information. The methods used to leverage information technologies to deal with research data vary significantly among scientists, and likewise the requirements of individual scientists vary.

by Cesare Concordia and Carlo Meghini (ISTI-CNR)

Virtual Research Environments (VREs) are rapidly becoming a popular technology for supporting scientists during their research work. In order to overcome the current heterogeneity, a reference architecture for VREs is being developed by the VRE4EIC Project.

by Phil Archer (W3C)

Sharing data between researchers, whether openly or not, requires effort, particularly concerning its metadata. What is the minimum metadata needed to aid discovery? Once data has been discovered, what metadata is needed in order to be able to evaluate its usefulness? And, since it’s not realistic to expect everyone to use the same metadata standard to describe data, how can different systems interoperate with the metadata that is commonly provided? These topics and more were discussed in Amsterdam in late 2016.

by Leonardo Candela, Donatella Castelli and Pasquale Pagano (ISTI-CNR)

Virtual research environments are emerging as an invaluable tool for scientists, enabling professionals in different fields to collaboratively and seamlessly access and use resources (computing, datasets, services) spread across several providers. This solution is particularly relevant in long-tail science contexts, i.e., when researchers and practitioner communities lack dedicated resources to perform their research. Implementing such a solution requires an approach that is open, flexible, and can easily evolve.  

by Daniele Bailo and Manuela Sbarra

The European Plate Observing System (EPOS) aims at creating a pan-European infrastructure for solid Earth science to support a safe and sustainable society. In accordance with this scientific vision, the mission of EPOS is to integrate the diverse and advanced European Research Infrastructures for solid Earth science relying on new e-science opportunities to monitor and unravel the dynamic and complex Earth system.  

by Zhiming Zhao, Paul Martin (University of Amsterdam) and Keith G. Jeffery (ERCIM)

Environmental Research Infrastructures (RIs) face common challenges regarding data management and how best to support the activities of scientists at all stages of the research data and experimentation lifecycle. The ENVRIPLUS ‘Data for Science’ theme aims to design and develop a suite of standard solutions to those common problems based on the reference model of research infrastructures (ENVRI-RM) and the e-VRE architecture proposed by VRE4EIC.

by Jorge dos Santos Oliveira, José Borbinha and Ana Teresa Freitas (INESC-ID/IST, Universidade de Lisboa)

Microbial enhanced oil recovery gained a new meaning with the development of metagenomics. This genomic method involves identifying the collective genome of a microbial community, including those that cannot be cultivated in controlled conditions. However, this method generates petabytes of genomic data, presenting specific computational challenges, demanding the development of new collaborative research platforms. The main goal of this project is to develop a virtual research environment (VRE) that can support studies using metagenomic data with application to the oil and gas field.