The volume of scientific literature being published has increased dramatically in the digital age. Ontologies and taxonomies are important tools to help researchers retrieve and understand this overwhelming amount of scientific literature, but using and managing ontologies can be challenging in itself.
In this whitepaper written by SciBite and our partner Copyright Clearance Center, we’re looking at the history of biomedical classification and how these systems have evolved to address new technology and use cases. We’ll explain the difference between taxonomies and ontologies, and discuss the challenges and successes that come with adopting and managing ontologies.
Ontologies can now be used for many applications, including search, data analysis, indexing and information sharing. The use of ontologies, potentially across structured and unstructured content, across a range of domains, opens possibilities far beyond Boolean searching of pooled citations. For example:
However, adopting and managing ontologies to achieve these benefits can be a challenge. To make use of public ontologies and taxonomies – such as MeSH, MedDRA, SNOMED, and NCI Thesaurus – in named entity recognition scenarios, for example, these must be tailored for use through expert manual curation or automated processes. These and private ontologies and taxonomies require high-throughput software to convert unstructured text into machine-readable information annotated with ontology terms.
Managing ontologies across an organization can also be a challenge. For example, if you use public ontologies modified locally, how do you then reconcile changes made in the original ontology with your modifications? How do you allow subject matter experts and users to contribute changes to your ontology safely and quickly?
Different types of ontology users need different permissions to suggest changes or make changes directly and immediately. Versioning, local changes, and audit trails must also be accounted for in productionized operations.
The volume of scientific literature has exploded. The value of searching across genetic, clinical, anatomy, and biochemical resources at once has shaped the new paradigm for research and development. Biomedical ontologies are a necessary tool to harness big data so that both humans and machines can advance our scientific understanding.
To learn more, download the full whitepaper.
In the first of this two-part blog, I describe what ontologies are and how you can use them to make the best use of scientific data within your organisation.Read
Just released by the Copyright Clearance Center, a semantic search solution applied to full-text articlesRead
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