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Effective algorithms
Algorithms for integration, analysis, visualisation that get the job done.
Diversity, in every dimension, is a key attribute of today’s data bonanza. Our research takes a holistic view, embracing this diversity and the consequent intricate interactions between users and systems. We created the Dispel data-streaming language to describe complex computation patterns at high levels of abstraction, while providing meta-information for optimisation. Provenance and contextual information must be harnessed to achieve autonomous execution, data placement, energy efficiency and reliability.
The Centre National de la Recherche Scientifique – Institut National des Sciences de l’Univers (CNRS-INSU) is looking for a new R&D Scientific Software Research Engineer to assist in the VERCE project (http://www.verce.eu/). Details attached, as well as available from the VERCE website.
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.
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 inherent limits to the predictability of brittle failure events such as earthquakes and volcanic eruptions are important, unknown, and much debated. We will establish techniques to determine what this limit is in the ideal case of controlled laboratory tests, for the first time in real-time, prospective mode, meaning before failure has occurred.
Edinburgh Data-Intensive Research Data-intensive refers to huge volumes of data, complex patterns of data integration and analysis, and intricate interactions between data and users. Current methods and tools are failing to address data-intensive challenges effectively. They fail for several reasons, all of which are aspects of scalability.
Date and time:
Tuesday, 1 June, 2010 - 14:00
Location:
iDEA lab bio-medical data day, Informatics Forum, Edinburgh, UK
Global and regional seismology monitoring systems are continuously operated and are transmitting a growing wealth of seismological data in Europe and from around the world. This opens exciting opportunities for a large range of geophysical research. The multi-use nature of these data puts a great premium on open-access data archive infrastructures that are well integrated in the European Plate Observing System (EPOS)—an ESFRI initiative of the solid earth community.
The agenda of this meeting will be flexible, the aim is to provide the informaticians with an understanding of the specific challenges in monitoring, analysis and modelling of experimental and seismological data.
I will introduce my PhD work on simulating a human/automatic curation cycle, and understanding how knowledge quality improves or degrades when automatically derived facts are accepted into a wiki-style knowledge base.
Data-intensive refers to huge volumes of data, complex patterns of data integration and analysis, and intricate interactions between data and users. Current methods and tools are failing to address data-intensive challenges effectively. They fail for several reasons, all of which are aspects of scalability.
Date and time:
Wednesday, 28 April, 2010 - 10:30
Location:
edikt2010 Symposium - Using computing in your research, e-Science Institute, 15 South College Street, Edinburgh
We present Edinburgh Data-Intensive Research, a research group in Edinburgh Informatics and part of the UK National e-Science Centre. The demonstration comprises several rounds of 15 minutes, where we briefly introduce the group (2-minutes), then attendees can pick people to talk to for the remaining time. All team members are there and have laptops to provide in-depth demonstrations of our methods and applications of them.
Date and time:
Monday, 15 March, 2010 - 14:00
Location:
Data-Intensive Research Workshop, e-Science Institute, UK