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Data-intensive computing
Systems and problems that include huge data volumes and complex patterns of integration and interaction.
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.
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
The aim is to develop an open-access, automated, web-based platform for real-time data collation, analysis and information exchange for geophysical experiments. This scientific gateway should enable competing physical hypotheses and statistical methods for forecasting rock failure to be tested and developed in fully prospective mode in an open, testable environment comparable to say daily weather forecasts.
Today’s challenges demand the best quality decisions that can be achieved. The growing wealth of available data should be used to improve those decisions. Data are the catalysts in research, engineering and diagnosis. Data fuel analysis to produce key evidence and supply the information for compelling communication. Data connect computational systems and capture the work of large collaborative endeavours.
Date and time:
Tuesday, 2 February, 2010 - 10:10
Location:
EPSRC Infrastructure Strategic Advisory Team, London, UK
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.
Science is witnessing a data revolution. Data are now created by faster and cheaper physical technologies, software tools and digital collaborations. Examples of these include satellite networks, simulation models and social network data. To transform these data successfully into information then into knowledge and finally into wisdom, we need new forms of computational thinking. These may be enabled by building "instruments" that make data comprehensible for the "naked mind" in a similar fashion to the way in which telescopes reveal the universe to the naked eye.
Date and time:
Tuesday, 9 February, 2010 - 09:30
Location:
Seminar Room, Biomedical Systems Analysis, Human Genetics Unit, Medical Research Council, Edinburgh, UK
Presenting the research of the Data-Intensive Research Group as part of a visit of Professor Robin Stanton (Pro Vice-Chancellor) and Professor Lindsay Botten (Director, National Computational Infrastructure), Australian National University, to the UK National e-Science Centre.
Today there is a growing abundance of data often in large-scale collections or with great complexity. It is pertinent to every pressing strategic challenge, to the deep questions that research addresses and the urgent application science. A great deal of thought is needed to improve our capabilities to use data well in a wide variety of research endeavours. The workshop will bring together practitioners, theoreticians and technologists with a wide range of viewpoints to shape a strategy for the thinking and research that is needed.
Location:
e-Science Institute, 15 South College Street, Edinburgh
This presentation's focus is on the computer science research performed at the National e-Science Centre as part of the University of Edinburg and the University of Glasgow. Another submission reports on the community support offered by the National e-Science Centre.
To explore, analyse and extract useful information and knowledge from massive amounts of data collected from geographically distributed sites, one has to overcome both data and computational intensive problems in distributed environments.
Science is witnessing a data revolution. Data are now created by faster and cheaper physical technologies, software tools and digital collaborations. Examples of these include satellite networks, simulation models and social network data. To transform these data successfully into information then into knowledge and finally into wisdom, we need new forms of computational thinking. These may be enabled by building "instruments" that make data comprehensible for the "naked mind" in a similar fashion to the way in which telescopes reveal the universe to the naked eye.
Date and time:
Wednesday, 27 January, 2010 - 14:00
Location:
Rm 6301, James Clerk Maxwell Building (JCMB), Kings Buildings
Final project report for JISC, with links to all individually created deliverables and progress posts. RapidSeis has produced a scientific gateway via a web portal that allows seismologist to pick up data from Orfeus—the central repository for earthquake data in Europe—and then run several analyses on these data. Advanced users can also create new analyses and share these with all the other users.
At the meeting we will present the result of the RapidSeis project, a collaboration between ORFEUS, the UK National e-Science Centre and the University of Liverpool. Over the past six months, this project has created a system that facilitates running waveform analysis on data from ORFEUS where the computation is performed on remote compute resources provided by the University of Liverpool.
Location:
Department of Earth & Ocean Sciences, University of Liverpool, UK
The aim is to develop an open-access, automated, web-based platform for real-time data collation, analysis and information exchange for geophysical experiments. This scientific gateway should enable competing physical hypotheses and statistical methods for forecasting rock failure to be tested and developed in fully prospective mode in an open, testable environment comparable to say daily weather forecasts.
At the meeting we will present the result of the RapidSeis project, a collaboration between ORFEUS, the UK National e-Science Centre and the University of Liverpool. Over the past six months, this project has created a system that facilitates running waveform analysis on data from ORFEUS where the computation is performed on remote compute resources provided by the University of Liverpool.
