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Big Data across disciplines: In search of symbiosis

Building on a successful Target conference in 2013, Target aims to continue and expand the conversation about the obvious benefits and potential challenges in developing interdisciplinary Big Data solutions. The second Target conference will bring together Big Data specialists, ICT researchers, e-scientists and traditional scientists from a variety of disciplines who will explore differences and commonalities in their approach to the three main stages in the Big data lifecycle Big Data acquisition and storage (Big Data technologies) Big Data analysis (metadata and databases) Big Data visualization - See more at:
When 03 November 2014 12:25 PM to
05 November 2014 12:25 PM
Where Groningen NL
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Theme 1: Big Data Technology

In these sessions, we will examine the current trends in technologies supporting the processing of Big Data. In particular, we will look at high speed data acquisition systems, data storage, data networks and processing facilities. Contributions from technology suppliers, hardware and software, together with projects which are driving this technology will be featured. The conflicting requirements of performance and high availability, are of particular interest to a number of large-scale projects on the horizon. Similarly, the requirement to ensure data privacy in medical research represents an increasing challenge to existing technological solutions.


Theme 2: Big Data Metadata

Metadata or "data about data" becomes increasingly important in managing Big Data. When data has been acquired the use of metadata allows the imposition of structure, so that subsequent analysis can take place. In these sessions, we will focus on examining the role that detailed data models can play in a number of disciplines from astronomy to social sciences that deal with Big Data. Topics which will be covered include data mining, querying large and ultra-large catalogues, application of relation and object-orientated databases, data providence and data lineage.

Theme 3: Big Data Visualization

The final phase in Big Data management, following data processing, is gaining insight and understanding from Big Data. In these sessions, the role of visualization techniques in extracting knowledge from data will be examined. We expect visual analytics (VA) to play an increasing valuable role in the future interpretation of Big Data. VA methodologies can allow the user to discover interesting and unexpected relationships in complex multi-dimensional datasets. In addition there will be contributions on the role that visualization can play in presenting complex science principles to the general public.

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