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Edit on GitHubHow is GBIF-mediated data used?
The GBIF literature tracking system has identified over 5,000 uses of GBIF mediated data, most of which are in peer-reviewed articles. The majority of these uses are in the field of ecology, but others relate to climate change, conservation, human health and agriculture. A systematic review of the use of GBIF-mediated data by Heberling et al. (2020) showed:
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Both data availability and data use have increased over time.
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Data integration facilitates global research and access.
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Uses of GBIF-mediated data span disciplinary boundaries.
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The scientific areas using GBIF-mediated data are conceptually diverse and change in prevalence over time.
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Globally integrated datasets enable researchers to ask both basic and applied questions at taxonomic, temporal and spatial scales that would be otherwise impossible.
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The synergistic roles of observation- and specimen-based biodiversity data highlight the value and need for deeper integration with phylogenetic, environmental, phenotypic, ecological and genetic sources of data.
GBIF-mediated data is also used for monitoring the state of biodiversity and progress towards achieving the targets of the Convention on Biological Diversity. The increase in availability of GBIF occurrence data is one of the indicators for tracking progress towards the achievement of Aichi Biodiversity target 19 and GBIF is a key data source in the creation of a number of other indicators, including the Species Status Information Index, Species Habitat Index and the Biodiversity Habitat Index.
While the utility of GBIF-mediated data is clear, the wide variety of sources of data accessible through GBIF, spanning museum collections, citizen science, metagenomics, among others, means that not all GBIF-mediated data will be fit for every use. Key components of using GBIF-mediated data are understanding how to access the specific data that you need from what is available in GBIF and understanding some of the common data quality issues that affect the data so as to facilitate processing of the data before analysis.