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Mastering Data-Intensive Collaboration and Decision Making (Dicode)
Start date: Sep 1, 2010, End date: Aug 31, 2013 PROJECT  FINISHED 

Description Exploiting a cloud infrastructure to augment collaboration and decision making in data-intensive and cognitively-complex settingsThe goal of the Dicode project is to facilitate and augment collaboration and decision making in data-intensive and cognitively-complex settings. To do so, it will exploit and build on the most prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze and aggregate data existing in diverse, extremely large, and rapidly evolving sources. The foreseen solution can be viewed as an innovative workbench incorporating and orchestrating a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities. Services to be developed are: (i) scalable data mining services (including services for text mining and opinion mining), (ii) collaboration support services, and (iii) decision making support services. The achievement of the Dicode project’s goal will be validated through three use cases addressing clearly established problems. These concern: (i) scientific collaboration supported by integrated large-scale knowledge discovery in clinico-genomic research, (ii) delivering pertinent information from heterogeneous data to communities of doctors and patients in medical treatment decision making, and (iii) capturing tractable, commercially valuable high-level information from unstructured Web 2.0 data for opinion mining.

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