The 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 - such as cloud computing, MapReduce, Apache Hadoop, Apache Mahout, and column databases – to meaningfully search, analyze and aggregate data existing in diverse, extremely large, and rapidly evolving sources.
Building on current advancements, the solution foreseen in the Dicode project will bring together the reasoning capabilities of both the machine and the humans. It 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:
- scalable data mining services (including services for text mining and opinion mining),
- collaboration support services, and
- decision making support services.
People have to cope with a diverse and exploding digital universe when working together; they need to efficiently and effectively collaborate and make decisions by appropriately assembling and analyzing enormous volumes of complex multi-faceted data residing in different sources. For instance, imagine:
- A community of clinical researchers and bio-scientists, supported in their scientific collaboration by a system that allows them to easily examine and reuse heterogeneous clinico-genomic data and information sources for the production of new insightful conclusions (or the formation of reliable biomedical knowledge), without having to worry about the method of locating and assembling these huge quantities of data (clinical and genomic data, molecular pathways, DNA sequence data, etc.).
- Or a community of clinicians, radiologists, radiographers, patients and pharma-researchers being able to contribute more effectively to clinical decisions and drug testing by combining heterogeneous, collaboratively annotated datasets from patient results (blood tests, physical examinations, free text journals from patients on their experience from treatment) and different scan modalities (X-Ray, Static and Dynamic MRI), without having to be anxious about tracking the data and their provenance through the complex decision making process, and the handling of the associated multimedia material.
- Or even, a marketing and consultancy company being able to effortlessly forage the Web (blogs, forums, wikis, etc.) for high-level knowledge, such as public opinions about its products and services; it is thus able to capture tractable, commercially vital information that can be used to quickly monitor public response to a new marketing launch; having the means to meaningfully filter, collate and analyse the associated findings; and use the information to inform new strategy.
The goal of the Dicode project is to turn this vision into reality. The project aims at facilitating and augmenting 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 - such as cloud computing, MapReduce, Apache Hadoop, Apache Mahout, and column databases – to meaningfully search, analyze and aggregate data existing in diverse,1extremely large, and rapidly evolving sources. Services to be developed and integrated in the context of the Dicode project will be released under an open source license. Building on current advancements, the solution foreseen in the Dicode project will bring together the reasoning capabilities of both the machine and the humans. It 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 and innovative activities. Aiming at facilitating and augmenting collaboration and decision making, the Dicode solution will enhance the quality of these processes and render time and cost savings.