A Method for Extending Ontologies with Application to the Materials Science Domain

Abstract

In the materials science domain the data-driven science paradigm has become the focus since the beginning of the 2000s. A large number of research groups and communities are building and developing data-driven workflows. However, much of the data and knowledge is stored in different heterogeneous data sources maintained by different groups. This leads to a reduced availability of the data and poor interoperability between systems in this domain. Ontologybased techniques are an important way to reduce these problems and a number of efforts have started. In this paper we investigate efforts in the materials science, and in particular in the nanotechnology domain, and show how such ontologies developed by domain experts, can be improved. We use a phrase-based topic model approach and formal topical concept analysis on unstructured text in this domain to suggest additional concepts and axioms for the ontology that should be validated by a domain expert. We describe the techniques and show the usefulness of the approach through an experiment where we extend two nanotechnology ontologies using approximately 600 titles and abstracts.

Materials Informatics for Mechanical Deformation: A Review of Applications and Challenges

“…A convenient way of organizing metadata is by incorporating an ontology, which serves as a framework for metadata design [ 259 ]. For mechanical deformation MI applications, such ontologies are currently being pursued.…”

“…Ontologies are defined as sophisticated classification schemes aimed at making complex data searchable. They have a hierarchical structure and define the basic terms and relations over a domain, as well as the rules for combining them [ 259 ]. Ontologies consist of four components: (i) concepts that represent sets or classes of entities in a domain, (ii) instances that represent the actual entities, (iii) relations (is-a or has-a), and (iv) axioms representing restrictions imposed on the domain.…”

An Ontology-Based Approach to Enable Data-Driven Research in the Field of NDT in Civil Engineering

“…The use of ontologies to address interoperability in MS is a common practice [29][30][31] and can be traced back until the work of [32]. However, the interest in applying ontologies in the technical domains can be found as far as 1996 in [33].…”

“…To date, some scientific papers have been published that relate MS to semantic interoperability using ontologies. The need for further research in this field has been expressed multiple times, e.g., in terms of "interoperability" as an issue to be addressed explicitly [31,[34][35][36][37] or implicitly using the terms "data integration" [38,39], "lack of uniformity, data selectivity" [40], or "conflicting terminologies between subfields, inconsistent recording practices" [41].…”

DomainSenticNet: An Ontology and a Methodology Enabling Domain-Aware Sentic Computing

“…Researchers in this field are also exploring the creation of new resources to be leveraged in ODSA-based applications. As an example, in [23], the authors presented a methodology to extend ontologies in the "Materials Science" domain. The presented approach leveraged the titles and abstracts of 600 domain publications and complemented a given ontology with additional concepts and axioms by means of a phrase-based 16 A recent model revision is described in [35] 15 SenticNet 6 has recently been released.…”