Materials Modelling has evolved dramatically in its capabilities over the last decades. What once were codes that could only be operated by authors and other experts has developed into professional software with user friendly interfaces that is used by tens of thousands of scientists. An even bigger circle of people are actual and potential beneficiaries of the technology.

However, substantial language barriers exist to enable all beneficiaries to reap the full benefit of materials modelling. A translation environment is required that speaks both the language of the end user (beneficiary) and that of modelling. It translates materials challenges and makes available information and potential modelling solutions readily available.
The OntoTrans project is aimed to rapidly bring these advancements in materials modelling standardization and translation into practice, making use also of advancements made by Information and Communication Technologies (ICT) in semantic knowledge management, using existing formats, tools and approaches to speed up implementation. OntoTrans will make use of:
knowledge formalization by means of a formal ontology expressed in OWL-DL language (the EMMO and dedicated sub-ontologies), to facilitate the use of existing tools for ontology extension, reasoning, compatibility with other existing ontologies
an Artificial Intelligence (AI) approach, exploiting the EMMO formalisation in the OWL-DL language to build a recommendation system (OntoRec) that forms the core upon which the translation environment will be based
RDF triplestore-based database management system (OntoKB) that will be used to store all knowledge (i.e. data with meaning) generated within the OntoTrans project and facilitate the achievement of the H2020 FAIR data management objectives, that will be populated by different means using OntoTrans key components, such as the ESS and the OSPs.
Graphical representation of the OntoTrans translation environment with reference to the EMMC translator's tasks
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