In information science, an ontology is an explicit, formal structuring of shared concepts that make up a domain. An ontology contains either descriptive or formal content links. The advantage of the method is clear: If one defines in a formalized way how all concepts of a discipline are to be designated and in which relation they are to each other, this logic is objectively comprehensible in a machine understandable way. Based on this, data that follow the corresponding logic can, for example, be uniformly filed, curated, or even evaluated.
The MaterialDigital platform therefore strives for an ontological structure as the basis of its information ecosystem. For materials science and engineering, an ontology should take into account the cross-scale nature of the discipline and must in itself provide added logical content value beyond a relational description.
An ontology for materials science according to the principles of the Semantic Web should help in the project with the uniform and standardized adaptable data organization as well as storage, retrieval and aggregation. A resulting knowledge graph will enable the uniform structuring of generated data sets, the analysis of their content, and the derivation of new knowledge from the logics obtained. The linkage of data, which can be achieved by means of the knowledge graph, can make then their complex connections developable, which are expressed in simpler form today in special models (in the form of textbook knowledge). Because of its complexity, ontology development can hardly take place in isolation, but must be tackled as a joint effort of the materials science community.
The following basic principles for ontology development are followed:
The ontology for materials science and engineering must be defined by the domain experts and thus the respective community, contributors and ultimate users. In other words, the actual process must be "bottom-up". Information science can only contribute the basic structure as the foundation of the required data space.
The ontology for materials science and engineering must be developed according to applicable research principles in a way that never implies completeness, but always allows for adaptivity and further growth.
The ontology for materials science and engineering must grow organically within initial domains in an application-oriented manner, and only in the long term will it evolve into a more holistic representation of the complete scientific discipline.
The performance of an ontology approach must be measured primarily by its practical application benefit for the goals of data structuring, accessibility / data reusability and evaluation. An ontology without application utility is irrelevant. Standardization is only one of the expected benefit dimensions of the ontology.
The platform managers see for themselves the task of creating an infrastructure to which the domain ontologies can "dock". This concerns in particular the guarantee of uniform interfaces as well as the definition of initial terminologies and claims, to which the partial ontologies can refer. The platform also intends to provide an initial, basic ontology as a starting schema.