The development of manufacturing technologies for new materials involves the generation of a large and continually evolving volume of information. The analysis, integration and management of such large volumes of data, typically stored in multiple independently developed databases, creates significant challenges for practitioners. There is a critical need especially for open-sharing of data pertaining to engineering design which together with effective decision support tools can enable innovation.We believe that ontology applied to engineering (OE) represents a viable strategy for the alignment, reconciliation and integration of diverse and disparate data. The scope of OE includes: consistent capture of knowledge pertaining to the types of entities involved; facilitation of cooperation among diverse group of experts; more effective ongoing curation, and update of manufacturing data; collaborative design and knowledge reuse.As an illustrative case study we propose an ontology focused * Address all correspondence to this author.on the representation of composite materials focusing in particular on the class of 'Functionally Graded Materials' (FGM) in particular. The scope of the ontology is to provide information about the components of such materials, the manufacturing processes involved in creation, and diversity of application hanging from additive manufacturing restorative dentistry. The ontology is developed using Basic Formal Ontology (BFO) and parts of the Ontology for Biomedical Investigation (OBI).
NOMENCLATURE
INTRODUCTIONInformation management encompassing the lifecycle of acquisition, curation and dissemination of material data have posed significant challenges in both academic and industrial domains. Over the years, relevant communities have accumulated ever larger amount of scientific data, and this accumulation has created a shortfall in effective information management. Improving this effectiveness is the key to obtaining better results in both research and development.Typically, data about materials science and engineering relates to four elements: composition of the material produced, properties of these materials, processing, performance in finished products [1,2].Oftentimes materials science data, of the sorts analysed by the scientists, are stored in multiple, autonomous, distributed, and heterogeneous sources, codified in different, and in many cases incompatible, formats often in the form of raw data obtained from lab instruments acquisition and or from measures of performance of basic properties, like corrosion data or fatigue data.A less discussed (but perhaps more critical) challenge is the semantic inconsistency of explicit and shared information as between different users and different applications [3,4]. Different aspects of this problem have to be considered, including: different ways of classification of materials due to different scopes, semantic discrepancy of synonyms and homonyms, different representation of similar data. Further comprending this matter is the fact that ...