One of the most important strategies in 21st Century Earth Management related science and engineering disciplines concerns the integration and implementation of intelligent solutions for sensing the Earth environment, numerically simulating the natural and anthropogenic processes involved and the automated service delivery of extracted knowledge for decision-support. In situ, airborne and space-borne Earth observations which are performed by multiple research and industrial organizations around the world are now generating a large volumes of data and information about Earth processes and eco-systems. Nevertheless, such generated Big data and information cannot be efficiently managed using traditional methods of data storage, access and processing by a large community of multi-disciplinary and collaborative decision makers; particularly those specializing in Critical Earth Management.
Therefore, there is, an urgent need for the deployment of generic knowledge bases and decision-support services in the context of an event driven service architecture. Enhancements for the on-demand availability to large user communities in accordance to their professional requirements for conducting crises as they evolve in time as need to be undertaken. Required actions to mitigate the foreseeable impacts which may occur during crises have to be further refined.
TRIDEC as an Integrated Project â partly funded by the European Commission under the Seventh Framework Programme â focuses on new approaches and technologies for intelligent geo-information management in complex and critical decision-making processes. The key objective in TRIDEC is to design and implement a collaboration infrastructure of interoperable services through which the intelligent management of information and data, dynamically increasing both in terms of size and dimensionality, is critically supported. This will enable multiple decision-makers to respond efficiently using a collaborative decision-support environment.
TRIDEC will establish rapid and on-demand interoperability of inherited legacy applications and tools owned by the project consortium partners. By using collaborative computing techniques TRIDEC enhances the interoperability of the components to establish a decision-support enterprise system of services which can critically deliver timely information to decision-makers.
TRIDEC will be demonstrated in two scenarios. Both involve intelligent management of large volumes of data for critical decision-support. The first scenario concerns a large group of experts working collaboratively in crisis centres and government agencies using sensor networks. Their goal is to make critical decisions and save lives as well as infrastructural and industrial facilities in evolving tsunami crises.
The other scenario concerns a large group of consulting engineers and financial analysts from energy companies working collaboratively in sub-surface drilling operations. Their common objective is to monitor drilling operations in real-time using sensor networks, optimising drilling processes and critically detecting unusual trends of drilling systems functions. This prevents operational delays, financial losses, and environmental accidents and assures staff safety in drilling rigs.
A knowledge-based service framework is deployed for context information and intelligent information management with flexible orchestration of system resources. An adaptive framework for collaborative decision making is enabled with new functions for the support of complex business processes.
Based on a âWork Packageâ organization TRIDEC will conduct fundamental research as well as component and system development. Basic research will aim at new approaches for the architecture and service integration of crisis management systems with special emphasis on robustness and fault tolerance. Complementary research will focus on new approaches for the design and intelligent retrieval of knowledge-bases comprising among others historic data, prognostic models, and rules. Together with information about the actual status of the underlying sensor systems will this enable the development of new, effective, and efficient tools for decision-support processes in critical crisis situation with evolving conditions.