The Infectious Disease Ontology in the age of COVID-19

Abstract

Background Effective response to public health emergencies, such as we are now experiencing with COVID-19, requires data sharing across multiple disciplines and data systems. Ontologies offer a powerful data sharing tool, and this holds especially for those ontologies built on the design principles of the Open Biomedical Ontologies Foundry. These principles are exemplified by the Infectious Disease Ontology (IDO), a suite of interoperable ontology modules aiming to provide coverage of all aspects of the infectious disease domain. At its center is IDO Core, a disease- and pathogen-neutral ontology covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is extended by disease and pathogen-specific ontology modules. Results To assist the integration and analysis of COVID-19 data, and viral infectious disease data more generally, we have recently developed three new IDO extensions: IDO Virus (VIDO); the Coronavirus Infectious Disease Ontology (CIDO); and an extension of CIDO focusing on COVID-19 (IDO-COVID-19). Reflecting the fact that viruses lack cellular parts, we have introduced into IDO Core the term acellular structure to cover viruses and other acellular entities studied by virologists. We now distinguish between infectious agents – organisms with an infectious disposition – and infectious structures – acellular structures with an infectious disposition. This in turn has led to various updates and refinements of IDO Core’s content. We believe that our work on VIDO, CIDO, and IDO-COVID-19 can serve as a model for yielding greater conformance with ontology building best practices. Conclusions IDO provides a simple recipe for building new pathogen-specific ontologies in a way that allows data about novel diseases to be easily compared, along multiple dimensions, with data represented by existing disease ontologies. The IDO strategy, moreover, supports ontology coordination, providing a powerful method of data integration and sharing that allows physicians, researchers, and public health organizations to respond rapidly and efficiently to current and future public health crises.

CoV2K model, a comprehensive representation of SARS-CoV-2 knowledge and data interplay

“…Many efforts aim at systematizing knowledge areas related to COVID-19. CoV2K is not competing with the COVID-19 Ontology 33 , CIDO 23 , COVID-19 Infectious Disease Ontology 34 , the COVID-19 Disease Map 35 , or the COVID-19 knowledge graph 36 , as they are essential for understanding the ontological properties of COVID-19 (mostly on the aspects of the disease), but are not aimed at linking large datasets about SARS-CoV-2 as CoV2K does. We instead propose an abstract model focused on SARS-CoV-2 sequences and their mutations/variants.…”

Covid19/IT the digital side of Covid19: A picture from Italy with clustering and taxonomy

“…The resulting ontology is publicly available online and suited for drug re-purposing towards Covid19 therapeutic development. Babock et al [ 40 ] extend the Infectious Disease Ontology (IDO), a suite of inter-operable modules of ontology covering all aspects of the infectious disease domain, with new ontologies that are pathogen-specific to Covid19. Their goal is to allow data on novel diseases to be easily compared, along multiple dimensions, with data represented by existing diseases of such ontologies.…”

Covid19-IBO: A Covid-19 Impact on Indian Banking Ontology Along with an Efficient Schema Matching Approach

“…Ontology as a Semantic Model: To respond effectively to emergencies such as public health, we need to share information across various disciplines and IT systems [9]. The digital technologies for analyzing the data will be possible to work effectively, if the underlying data model is itself robust.…”

“…Along with the databases, various ontologies also have been developed to extract hidden and semantic information. Many bioinformaticians and biologists have argued that if ontologies are designed in a coordinated manner, then they will become an effective tool for data sharing [9]. The Open Biomedical Ontologies (OBO) Foundry is the most successful approach for the development of the coordinated ontology.…”

“…IDO follows the ontology design principle of OBO Foundry and provides a 'hub and spokes model' for the development of the other ontologies. The backbone of the IDO ontology is entity 'disease' which is extracted from the OGMS ontology [9]. IDO has well-tested and offers a reliable starting point for the other ontologies.…”