About us
Oxford Semantic Technologies was founded in 2017 as a spin-out of the University of Oxford with a mission to bring cutting-edge research in semantic web technologies to industry.
The principal shareholders are the Founders, the University of Oxford and Oxford Sciences Innovation.
➤ LOCATION
The Innovation Centre,
99 Park Drive, Milton Park, Oxfordshire, OX14 4RY,
United Kingdom
Semantic technology
Semantic technologies address the challenges posed by data integration by providing (1) a flexible graph data model for representing semistructured data, (2) ontologies for representing a unified conceptual view of the data, and (3) powerful reasoning systems that combine information from the ontology and the data in order to answer user queries.
Two databases from the worlds of Formula One and Hollywood can be combined into a single graph.
EXample Applications
Financial services: Financial institutions have multiple, separate databases. OST technology enables these systems to be mapped to an ontology that can then be used for compliance and transactions.
Industry: Manufacturing companies can use these technologies to integrate data and model production processes..
Engineering and design: These technologies can be used to assist designers and engineers to select components that comply with standards imposed by clients, ISO or the operating environment.
Services: Service companies can use these technologies to model and simulate customer decisions and behaviour.
Integration
Oxford Semantic Technologies uses cross-platform software which can be used on Windows, MacOS and Linux/Unix systems.
The data is processed in the Resource Description Format (RDF) data format. This versatile and future-proof format is most popular on the world wide web and allows for the exchange of data between any systems, whether the latest vendor product or a legacy in-house solution. Any data stored in classical SQL or no-SQL databases tables can be readily translated back and forth into RDF.
Products
Oxford Semantic Technologies owns RDFox, the optimised RDF-triple store and parallel Datalog reasoning engine developed at the University of Oxford. OST’s development team has applied state of the art techniques and some of the finest programming skills to exploit the full power of modern multi-core architecture.
RDFox scales with every additional processor core extremely well and brings, for the time, first mid-sized and large applications of Semantic Technologies into the reach of commodity hardware.
Datalog is a rule language which allows for neat and elegant formulation of queries and views. With Datalog, one can encode specification and regulations and policies given in natural language whilst maintaining a high correspondence to the original text. Datalog's clarity shortens development cycles and enormously increases maintainability of implemented projects.
Developing solutions in Datalog require less IT-expert skills and allows domain experts to formulate queries by themselves. Development cycles for data analysis tasks are drastically reduced. Datalog-explanations for query answers show how exactly a certain answer was derived from the given data. This allows the domain expert to validate his developed solutions and gives certainty about the obtained results.
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The Web was designed as an information space, with the goal that it should be useful not only for human-human communication, but also that machines would be able to participate and help.
One of the major obstacles to this has been the fact that most information on the Web is designed for human consumption, and even if it was derived from a database with well defined meanings (in at least some terms) for its columns, that the structure of the data is not evident to a robot browsing the Web.
Leaving aside the artificial intelligence problem of training machines to behave like people, the Semantic Web approach instead develops languages for expressing information in a machine process-able form
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