Maintenance is an important technical aspect that must be considered in engineering practices. In this paper we present a preliminary ontological investigation of questions such as “What is a component of an engineering system?” and “What happens when a component is replaced after a malfunctioning?”, which are both fundamental from a maintenance modeling stance. We focus in particular on two inter-related problems, which we call the missing component and the replacement problems. We describe different approaches dealing with them. First, we start representing kinds of components and systems as temporally qualified first-order logic predicates, eventually reified. We then consider a four-dimensionalist (4D) perspective, mainly based on the ISO 15926. Lastly, we briefly mention a novel point of view based on possible worlds. By the end of the paper, we shortly compare the approaches by discussing their advantages and shortcomings.

An overview of some ontological challenges inengineering maintenance

This paper introduces an ontology-based approach for facilitating theaccess to the available information in different sources to help tribologistsshortening  the  time,  number  and  size  of  experiments  required  to  iden-tify the tribological characteristic of a material or combination of them(e.g., metal, coating, lubricant) with respect to specific operation condi-tions.  More specifically, how the use of ontologies for mapping relevanttribological  information  sources,  containing  from  experiment  results  topatents/scientific publications, enables the development of a holistic Se-mantic Federated Search service for tribology domain.

Materials’ Tribological Characterisation: an OntoCommons Use Case

Recent advances in computational and experimental technologies applied to the design and development of novel materials have brought out the need for systematic, rational and efficient methods for the organization of knowledge in the field. 
In this work, we present the initial steps carried out in the development of MAMBO - an ontology focused on the organization of concepts and knowledge in the field of materials based on molecules and targeted to applications. 
Our approach is guided by the needs of the communities involved in the development of novel molecular materials with functional properties at the nanoscale. 
As such, MAMBO aims at bridging the gaps of ongoing efforts in the development of ontologies in the materials science domain. 
By extending current work in the field, the modular nature of MAMBO also allows straightforward extension of concepts and relations to neighboring domains. 
Our work is expected to enable the systematic integration of computational and experimental data in specific domains of interest 
(nanomaterials, molecular materials, organic an polymeric materials,
supramolecular and bio-organic systems, etc.). 
Moreover, MAMBO can be applied to the development of data-driven integrated predictive frameworks for the design of novel materials with tailored functional properties.

Introducing MAMBO: Materials And Molecules Basic Ontology

Supply Chain Management (SCM) involves coordinating and integrating material, information and money flows, both within and across several companies. The integration of these flows is perceived differently by distinct communities, raising some semantics-related problems. In traditional industries as well as in the context of the recent Industry 4.0, smart manufacturing or cyber-physical systems initiatives, more efficient and effective integration of supply chain flows is required. This integration implies physical as well as application interoperability and a common understanding at the semantic level. For several years, ontologies have been considered the key technology to achieve semantic integration. So, this contribution introduces SCONTO, an ontology that formally describes a SC at various abstraction levels, by specifying its associated business processes based on the SCOR de facto standard as well as sharing a precise meaning of the information exchanged during communication among the many stakeholders involved in the SC. Moreover, SCONTO provides a foundation for the specification of information logistics processes and sets the grounds for measuring and evaluating a SC by stating different metrics and performance-related concepts.

SCONTO: A Modular Ontology for Supply Chain Representation 

Ontologies have been proposed as a means towards making data FAIR (Findable, Accessible, Interoperable, Reusable) and has recently attracted much interest in the materials science community. Ontologies for this domain are being developed and one such effort is the Materials Design Ontology.
However, to obtain good results when using ontologies in semantically-enabled applications, the ontologies need to be of high quality. One of the quality aspects is that the ontologies should be as complete as possible. In this paper we show preliminary results regarding extending the Materials Design Ontology using a phrase-based topic model. 

A First Step towards Extending the Materials Design Ontology

Domain-specific metadata standards, including ontologies, markup languages, and technical interface specifications, are a necessary component of solutions for FAIR research data management with industrial applications. The Workshop on Domain Ontologies for Research Data Management in Industry Commons of Materials and Manufacturing (DORIC-MM 2021) discusses the state of the art, challenges, and perspectives for continuing innovation in this field. The present work comments on the landscape of semantic assets in the field of materials modelling, covering electronic, atomistic, mesoscopic, and continuum methods. Summaries are given of particularly promising lines of work, including the CAPE-OPEN interface standard, the XML schemas EngMeta, CML, and ThermoML, and the ontologies OntoCAPE, Metadata4Ing/Metadata4HPC, OSMO (the ontology version of MODA) and the VIMMP system of ontologies, and the domain-level modules of the European Materials and Modelling Ontology (EMMO). For future work, it is recommended to emphasize advancing in accordance with five principles: 1. Diversification of technologies; 2. Observation of practices; 3. Realistic objectives; 4. Incentives for providing citable data and software; 5. Co-design of simulation and data technology.

ESWC 2021 Workshop DORIC-MM Submissions

An overview of some ontological challenges inengineering maintenance

Materials’ Tribological Characterisation: an OntoCommons Use Case

Introducing MAMBO: Materials And Molecules Basic Ontology

SCONTO: A Modular Ontology for Supply Chain Representation

A First Step towards Extending the Materials Design Ontology

Domain-specific metadata standardization in materials modelling