The COVID-19 epidemic has demonstrated the important role that data plays in the response to and management of public health emergencies. It has also heightened awareness of the role that ontologies play in the design of semantically precise data models that improve data interoperability among stakeholders. This paper surveys vocabularies and ontologies relevant to the task of achieving epidemic-related data interoperability. The paper first reviews 16 vocabularies and ontologies with respect to the use cases. Next it identifies patterns of knowledge that are common across multiple vocabularies and ontologies, followed by an analysis of patterns that are missing, based on the use cases. Conclusions show that existing vocabularies and ontologies provide significant coverage of the concepts underlying epidemic use cases, but there remain gaps in the coverage. More work is required to cover missing but significant concepts.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1177/14604582231180226 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
PlasGO: enhancing GO-based function prediction for plasmid-encoded proteins based on genetic structure.
Gigascience
January 2024
Department of Electrical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR (HKG), China.
Background: Plasmid, as a mobile genetic element, plays a pivotal role in facilitating the transfer of traits, such as antimicrobial resistance, among the bacterial community. Annotating plasmid-encoded proteins with the widely used Gene Ontology (GO) vocabulary is a fundamental step in various tasks, including plasmid mobility classification. However, GO prediction for plasmid-encoded proteins faces 2 major challenges: the high diversity of functions and the limited availability of high-quality GO annotations.
View Article and Find Full Text PDFIdentifying Medical Concepts and Semantic Types in Lay Vocabularies of Health Consumers Who are Concerned with Diabetes on Social Media Using the UMLS and NLP.
Proc COMPSAC
July 2024
College of Nursing, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA.
This study suggests a way to utilize the existing medical ontology and natural language processing techniques to extract major medical concepts from lay vocabularies of health consumers on social media and group them based on the defined semantic types in the ontology. Diabetes-related discussions on Tumblr was used to test the efficiency of SpaCy and the Markov-Viterbi algorithm to map lay medical terms to the defined medical concepts in the UMLS. The system discussed in this paper can better analyze free texts, take care of word ambiguity and extract the lifestyle indicators from the daily life discussions of diabetic people on Tumblr.
View Article and Find Full Text PDFOntology-based integration and querying of heterogeneous rare disease data sources - POLVAS perspective.
Comput Biol Med
December 2024
2nd Department of Internal Medicine, Jagiellonian University Medical College, ul. Jakubowskiego 2, 30-688 Kraków, Poland. Electronic address:
The integration of rare disease medical databases belonging to different countries is an important problem, as a large number of observations are required for reliable statistical inference of patient data in order to facilitate clinical research. Such integration of national registry data, which requires harmonization of the heterogeneous data sets into a unified view, is facilitated in the European FAIRVASC project by developing a domain-specific ontology. The FAIRVASC project is dedicated to the rare disease of anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV).
View Article and Find Full Text PDFBackground: While unstructured data, such as free text, constitutes a large amount of publicly available biomedical data, it is underutilized in automated analyses due to the difficulty of extracting meaning from it. Normalizing free-text data, , removing inessential variance, enables the use of structured vocabularies like ontologies to represent the data and allow for harmonized queries over it. This paper presents an adaptable tool for free-text normalization and an evaluation of the application of this tool to two different sets of unstructured biomedical data curated from the literature in the Immune Epitope Database (IEDB): age and data-location.
View Article and Find Full Text PDFDefinition of reproductive structures in Eucalyptus for phenological data collection.
Int J Biometeorol
November 2024
School of Agriculture, Food and Ecosystem Sciences, Faculty of Science, The University of Melbourne, Burnley, Victoria, 3121, Australia.
In an era where global climate change is shifting plant phenology, global meta-analyses of multiple species are required more than ever. Common language or references for enhanced data compatibility are key for such analyses. Although the Plant Phenology Ontology (PPO) addresses this challenge, it does not capture several relevant reproductive structures that are critical in species with long reproductive cycles, like many Eucalyptus species.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!