Research Data Infrastructures and Engineering Metadata

This chapter introduces metadata models as a semantic technology for knowledge representation to describe selected aspects of a research asset. The process of building a hierarchical metadata model is reenacted in this chapter and highlighted by the example of EngMeta. Moreover, an overview on data infrastructures is given, the general architecture and functions are disscussed, and multiple examples of data infrastructures in materials modelling are given.

Semantic Technology for Simulations and Molecular Particle-Based Methods

In this Chapter we discuss the role of ontologies for simulations, in the context of materials modelling in general and of molecular particle-based methods in particular. After a brief overview of the literature and possible applications, we present the VIMMP ontologies that allow to describe software capabilities and to further specify the various algorithms via the involved variables: the VImmp Ontology of Software (VISO) and the Vimmp Ontology of Variables (VOV).

Applications of the Metadata Standards

This chapter addresses issues related to the practical use of the metadata standards, including syntactic interoperability and concrete scenarios from molecular modelling and simulation. It discusses challenges that arise from semantic heterogeneity, wherever multiple interoperability standards are concurrently employed for identical or overlapping domains of knowledge, or where domain ontologies need to be matched to top-level ontologies such as the European Materials and Modelling Ontology (EMMO).

Marketplace-Level Domain Ontologies

To enable semantic interoperability with external services and platforms, the Virtual Materials Marketplace (VIMMP) project has developed a system of marketplace-level domain ontologies, supporting the ingest and retrieval of data and metadata at the VIMMP marketplace front end; these ontologies are expressed in OWL2 using TTL notation [1]. Internally, VIMMP uses the marketplace-level domain ontologies as a part of its approach to data management, underlying the interactions with users. This chapter and the subsequent two chapters present ontologies from the VIMMP project and their relation to other work, including other ontologies.

Introduction

Digitalization is one of the driving forces of technological and social progress today. In the engineering sciences, in combination with a great variety of quantitatively reliable modelling and simulation approaches, it supports the development known as industry 4.0 by contributing to virtual manufacturing through cyber-physical systems. This is the main topic of this book, where the focus will be on the interoperability aspects of findable, accessible, interoperable, and reusable (FAIR) data management, and the practical implementation on digital platforms and data infrastructures for materials modelling.