The Devices, Experimental Scaffolds, and Biomaterials Ontology (DEB): A Tool for Mapping, Annotation, and Analysis of Biomaterials Data

Abstract

The size and complexity of the biomaterials literature makes systematic data analysis an excruciating manual task. A practical solution is creating databases and information resources. Implant design and biomaterials research can greatly benefit from an open database for systematic data retrieval. Ontologies are pivotal to knowledge base creation, serving to represent and organize domain knowledge. To name but two examples, GO, the gene ontology, and CheBI, Chemical Entities of Biological Interest ontology and their associated databases are central resources to their respective research communities. The creation of the devices, experimental scaffolds, and biomaterials ontology (DEB), an open resource for organizing information about biomaterials, their design, manufacture, and biological testing, is described. It is developed using text analysis for identifying ontology terms from a biomaterials gold standard corpus, systematically curated to represent the domain's lexicon. Topics covered are validated by members of the biomaterials research community. The ontology may be used for searching terms, performing annotations for machine learning applications, standardized meta-data indexing, and other cross-disciplinary data exploitation. The input of the biomaterials community to this effort to create data-driven open-access research tools is encouraged and welcomed.

The Biomaterials Annotator: a system for ontology-based concept annotation of biomaterials text

“…Various corpora of abstracts were used during the development, covering the general biomaterials literature. These corpora included a collection of manually curated abstracts of the biomedical polymer polydioxanone (Fuenteslópez et al 2021, manuscript in preparation, GitHub repository: https://github.com/ProjectDebbie/ polydioxanone_project) and a previously published biomaterials gold standard collection (Hakimi et al, 2020), comprising a total of 1222 abstracts. Corpora were passed through four steps, each described in detail below.…”

“…Whilst there are a handful of ontologies in the biomaterials domain (such the nanoparticle ontology NPO (Thomas et al, 2011) and the Bone and Cartilage Tissue Engineering Ontology BCTEO (Viti et al, 2014)), to the best of the our knowledge, the DEB ontology (Hakimi et al, 2020) is the only one that is tailored to link and curate concepts for Biomaterials NER. Therefore, it specifically covers different categories related to the biomaterials domain.…”

Data-driven materials research enabled by natural language processing and information extraction

“…Recent work used a hierarchical LDA, which learned an overall structure from the data and generated a tree of classes that could be used for searching terms, annotation, and standardization of metadata. 77 There are a few interesting ways to generate these concept lists. The work by Krenn and Zelinger analyzed trends in quantum physics by generating a concept list through human-expert input that is expanded by Rapid Automatic Keyword Extraction to a term list; this is, then, fed into a comprehensive corpus to establish links between each of the terms.…”

Proceedings of the Second Workshop on Scholarly Document Processing

“…Whilst there are a handful of ontologies in the biomaterials domain (such the nanoparticle ontology NPO (Thomas et al, 2011) and the Bone and Cartilage Tissue Engineering Ontology BCTEO (Viti et al, 2014)), to the best of the our knowledge, the DEB ontology (Hakimi et al, 2020) is the only one that is tailored to link and curate concepts for Biomaterials NER. Therefore, it specifically covers different categories related to the biomaterials domain.…”

“…To cover entities from different domains, multiple nomenclatures, vocabularies, and especially ontologies were identified and combined. To combine these resources into a single instrument, the Devices, Experimental scaffolds and Biomaterials Ontology (DEB) was used providing the logical schema and the definition of key categories (Hakimi et al, 2020).…”