EMMO: a reference representation of materials and their modelling

This contribution describes the European Materials Modelling Ontology (EMMO) [1], its objectives and potential to overcome interoperability challenges. Materials modelling is understood to include science based predictive methods describing any type of chemical and material at any level of granularity, i.e. electronic, atomistic, mesoscopic and continuum modelling. Methods in use today have their origins in a wide range of communities, such as computational chemistry, solid state physics, materials science, mechanical engineering etc. Application to industrial challenges typically requires integration of a range of these methods, which poses a significant interoperability challenge, not only computationally but also between experts from different communities. The European Materials Modelling Council (EMMC) [2] recognized the need to collate the wide range of contributions and better integrate different communities and methodologies. Interoperability of models, software and data is needed to facilitate an integrated approach to materials design and product improvement. Thus, the EMMC facilitated the elaboration of a CEN Workshop Agreement: Materials modelling ? Terminology, classification and metadata [3] to establish a reference terminology for materials modelling. On this basis, EMMC has been supporting the development of a general and widely applicable semantic framework for the representation of materials and their modelling: the European Materials Modelling Ontology (EMMO). The aim of EMMO is to provide a common ground for describing materials and models and for the interchange of data. EMMO is designed to pave the road for semantic (rather than purely syntactic) interoperability. It can be used as the foundation for implementation of standards and open interfaces connecting different codes and models based on their fundamental characteristics. [1] Gerhard Goldbeck, Emanuele Ghedini, Adham Hashibon, Georg J. Schmitz, Jesper Friis; (2018), to be published. [2] https://emmc.info/ [3] CWA 17284: https://www.cen.eu/news/workshops/Pages/WS-2017-012.aspx The work has been carried out as part of the EMMC-CSA project, funded from the European Union?s Horizon 2020 research and innovation programme under Grant Agreement No 723867.