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Presentations by group members at external events
We regularly present our work at seminars, specific meetings, and national and international conferences.
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
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
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
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.
OGSA-DAI provides an extensible framework that allows data resources to be incorporated into distributed systems. The WS-DAI (Web Service Data Access and Integration) family of specifications defines web service interfaces to data resources, such as relational or XML databases. Providing reference implementations for such specifications is important for the improvement of the specifications and the satisfaction of the interoperability goal.
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.
In this study, we apply a methodology for rapid development of portlets for scientific computing to the domain of computational chemistry. We report results in terms of the portals delivered, the changes made to our methodology and the experience gained in terms of interaction with domain-specialists.
In this paper, we report a metadata store that is designed around the concept of a data-metadata binding where both data and metadata elements are references to the respective sources, and bindings have user-assigned tags that describe the nature of the binding relationship. The design of the system, the services it provides, and the characteristic workflows of updates and queries that such a system must support are reported.
There is a rapidly growing wealth of data. The number of sources of data is increasing, while, at the same time, the diversity, complexity and scale of these data resources are also increasing dramatically. This cornucopia of data offers much potential; a combinatorial explosion of opportunities for knowledge discovery, improved decisions and better policies. Today, most of these opportunities are not realised because composing data from multiple sources and extracting information is too difficult.
