"Knowledge Enabled Ser vices (KES ) for Decision Suppor t in Contr ol Rooms. CESADS(KES) Case Study at ESA/ESOC."

This paper describes an innovative yet operational knowledge-based Monitoring, Diagnostic and Decision Support system aimed to increase operational efficiency and knowledge preservation in complex control rooms under conditions of stressed operation. The system fixes current difficulties in terms of (1) homogenization of ope rator’s knowledge and (2) management of complexity derived from large systems resulting from a progressive and accumulative deployment. The paper discusses the combination of Knowledge Technologies addressing main issues in the control room: structural (domain) knowledge and behavioural (reasoning) knowledge. Conceptually, the paper describes the organization and construction of knowledge models on top of Ontologies and Production Rules (using Fuzzy Logic). The paper does also address the design of specific, operatoradapted human machine interfaces for the definition, maintenance and evolution of modular and hierarchical set of formalized knowledge. The paper depicts implementation of the Knowledge Enabled Service (KES) based on the integration of Protege and Jess tools, which are integrated into multi-client distributed architecture with modular client applications for system interaction, including a key Knowledge Acquisition Module (C-KAE). Additionally, the paper introduces the demanding methodological approach which has result from the combination of the CommonKADS framework for the Knowledge Engineering tasks - with the Rational Unified Process. The paper includes detailed description of an operative Case Study: the CESADS project, a KES Decision Support System (DSS) implemented at ESOC for monitoring, prediction and diagnostic of very critical end-to-end space link (S/L) losses in spacecraft control missions, with high stress and responsiveness requirements on operators. The paper discusses the development and implantation of the pre-operational tool and focus on lessons learnt. Accordingly, the paper elaborates further the evolution of the knowledge and software engineering frameworks via Ontologies (on top of the W3C’s RDF and OWL specs), WebServices, Grid and SemanticWeb, into the emerging and unifying Semantic-Grid paradigm. Keywor ds: KES, Decision Support, ESA, ESOC, CommonKADS, Ontology.