ArticlePloS one2014
Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
43 citing papers in PubMed.
- RD-OMICS: An Integrative Multi-Omics Data Inventory in Rare Diseases.bioRxiv : the preprint server for biology · 2026Article
- Assessing coverage of the monitoring framework of the Kunming-Montreal Global Biodiversity Framework and opportunities to fill gaps.Nature ecology & evolution · 2025Article
- Fragmented Networks: Challenges in communication and cohesion of European Biodiversity Research Infrastructures.Biodiversity data journal · 2025Article
- Russian Biodiversity Collections: A Professional Opinion Survey.Animals : an open access journal from MDPI · 2023Article
- The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.Mammalian genome : official journal of the International Mammalian Genome Society · 2023Article
- The Ontology of Biological Attributes (OBA) - Computational Traits for the Life Sciences.bioRxiv : the preprint server for biology · 2023Article
- Ontologies for increasing the FAIRness of plant research data.Frontiers in plant science · 2023Review
- CRENO: An ontology to model concepts relating to culture, race, ethnicity, and nationality for health data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Ontology-driven analysis of marine metagenomics: what more can we learn from our data?GigaScience · 2022Article
- Toward FAIR Representations of Microbial Interactions.mSystems · 2022Article
- A solution to the challenges of interdisciplinary aggregation and use of specimen-level trait data.iScience · 2022Article
- How Metagenomics Has Transformed Our Understanding of Bacteriophages in Microbiome Research.Microorganisms · 2022Review
- Past and future uses of text mining in ecology and evolution.Proceedings. Biological sciences · 2022Review
- Providing Adverse Outcome Pathways from the AOP-Wiki in a Semantic Web Format to Increase Usability and Accessibility of the Content.Applied in vitro toxicology · 2022Article
- PREGO: A Literature and Data-Mining Resource to Associate Microorganisms, Biological Processes, and Environment Types.Microorganisms · 2022Article
- Ontology-Enriched Specifications Enabling Findable, Accessible, Interoperable, and Reusable Marine Metagenomic Datasets in Cyberinfrastructure Systems.Frontiers in microbiology · 2021Article
- Transforming the study of organisms: Phenomic data models and knowledge bases.PLoS computational biology · 2020Review
- FAIR digital objects in environmental and life sciences should comprise workflow operation design data and method information for repeatability of study setups and reproducibility of results.Database : the journal of biological databases and curation · 2020Article
- Article
- Towards a catalogue of biodiversity databases: An ontological case study.Biodiversity data journal · 2020Article
Corrections and comments
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Authors and funding
25 authors.
Funding
Abstract
The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.