Ontologies and databases on thermophysical properties of nuclear reactor materials

The study is dedicated to the information technologies for storage, systematization and distribution of thermophysical data for nuclear power engineering. The general trend existing in the areas involving wide use of scientific data is the shifting from conventional databases to the development of a consolidated infrastructure capable of overcoming sharply growing volumes of scientific data with continuously increasing complexity of the data structure due to the expansion of the range of materials. The above infrastructure ensures interoperability, including data exchange and dissemination. The general principle of data management for thermophysical properties of the nuclear reactor materials based on the subject-oriented ReactorThermoOntology (RTO) is suggested in the present paper. The ontology includes a unified glossary of all concepts, expanded through logical connections and axioms. The suggested RTO ontology combines the terms typical for reactor materials, their characteristics, as well as all types of information entities determining textual, mathematical and computer structures. In the coded form, the ontology becomes the control add-in capable to integrate heterogeneous data. Its most important feature is the possibility of its permanent expansion, which is necessary with introduction of new materials and terms related to them, e.g. nanostructures characteristics. Beside the ontology, description of the reactor materials, the possible scenarios for the use of the ontology during the phases of design, operation and integration of autonomous resources, primarily databases, are examined in the paper. The use of Big Data technology with diverse variations of logical structures of the data is suggested as the most efficient tool for data integration. Joint use of the technologies which before were applied separately, such as exchange standard in the form of the structured text documents, data control based on the ontology and platform for the work with big data, allows the conversion of multiple existing primary resources (databases, files, archives, etc.) to the standard JSON text format for the subsequent semantic integration.