| Abstract | Semantic Technologies represent meanings, associations and know-how about the uses of things separately from data and program code. This knowledge representation is called an ontology, and is defined using constructs for: concepts (classes, things), relationships (properties), rules (axioms and constraints), instances of concepts (individuals). What really makes Semantic Technologies different from previous information technologies (IT) is that meanings are represented separately from data, content and application code, so that machines as well as people can understand, share and work with them. Semantic Technologies are "meaning-centered" rather than "data-centered". They include tools for auto-recognition of topics and concepts, information and meaning extraction, and categorization. Given a question, Semantic Technologies can directly search topics, concepts, associations that span a vast number of sources. The results are fast, relevant, and comprehensive. Semantic Technologies inscribe themselves into the long waves of innovations. Global investment to develop Semantic Technologies by Venture Capital, governments and Industry are predicted to approach $15 billion this decade. Semantic solutions, services and software markets should top $50 billion by 2010. More than 150 ITC companies have Semantic Technology R&D in progress, including most major players. 65 of them offer products. Semantic Technologies have been demonstrated to deliver the expected capabilities and performance, but in addition, their benefits outweigh the associated costs and risks. Semantic Technologies impact businesses at three levels: efficiency, effectiveness and edge. Indeed, early adopter researches depict 2 to 10 times improvements in key measures of performance (cost savings, return on assets, return on investment) across the solution life-cycle. Finally, the case of Thales Research & Technology France gives an insight into a multi-national company implementing Semantic solutions. |