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Data-intensive computing
Systems and problems that include huge data volumes and complex patterns of integration and interaction.
From the ENVRI Description of Work: "Frontier environmental research increasingly depends on a wide range of data and advanced capabilities to process and analyse them. The ENVRI project, 'Common Operations of Environmental Research Infrastructures' is a collaboration in the ESFRI Environment Cluster, with support from ICT experts, to develop common e-science components and services for their facilities. The results will speed up the construction of these infrastructures and will allow scientists to use the data and software from each facility to enable multi-disciplinary science."
The Data-Intensive Process Engineering Language (DISPEL) has been developed in the ADMIRE project to encourage partitioning of data-intensive process design and development. It manipulates processing elements and data streams to generate graphs that represent the requested processes. Some of the features of the language designed to make this possible will be introduced
The 10-years of the e-Science programme and many earlier years of e-Science have shown the critical importance of digital communication in data-intensive research and in collaboration to bring sufficient expertise to bear on challenges. A review of the 10 years of the e-Science programme shows that the significant positive outcomes are often years after the initial work, even though that led to major breakthroughs and achievements.
We are delighted to welcome Donald MacDonald who is joining the Rapid-OMERO project developing its story from where Jos Koestier is leaving it.
He brings with him the experience of working in the OMERO team with Professor Jason Swedlow in Dundee, and earlier experience of data mining in Paisley.
At the start of the e-Science programme we thought scale was the predominant challenge.
Within a year we realised that there were many more aspects to the challenge of empowering researchers by applying distributed computation.
We now understand that e-Science is a continuous process, progress being achieved by walking paths together discovering critical issues and inventing solutions collaboratively.
The Open Science Data Cloud (OSDC) is an open-source, cloud-based infrastructure that allows scientists to manage, analyze, integrate and share medium to large size scientific datasets.
The OSDC PIRE project aims to narrow the growing gap between the capability of modern scientific instruments to produce data and the ability of researchers to control and examine the data in a reliable and timely manner.
The Royal Society of Edinburgh (RSE), Scotland’s National Academy, is delighted to announce that it has today chosen the first members of the new “RSE Young Academy of Scotland”. This exciting development is the first of its kind in the UK. It will be part of a growing movement of Young Academies across the world.
The VERCE project aims at studying and developing a working framework for running data- and computationally intensive applications in the seismology domain.
project aims at studying and developing a working framework for running data- and computationally intensive applications in the seismology domain.
