Voluntary consensus based geospatial data standards for the global illegal trade in wild fauna and flora.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
03 06 2022
03 06 2022
Historique:
received:
01
11
2021
accepted:
11
05
2022
entrez:
6
6
2022
pubmed:
7
6
2022
medline:
9
6
2022
Statut:
epublish
Résumé
We have more data about wildlife trafficking than ever before, but it remains underutilized for decision-making. Central to effective wildlife trafficking interventions is collection, aggregation, and analysis of data across a range of source, transit, and destination geographies. Many data are geospatial, but these data cannot be effectively accessed or aggregated without appropriate geospatial data standards. Our goal was to create geospatial data standards to help advance efforts to combat wildlife trafficking. We achieved our goal using voluntary, participatory, and engagement-based workshops with diverse and multisectoral stakeholders, online portals, and electronic communication with more than 100 participants on three continents. The standards support data-to-decision efforts in the field, for example indictments of key figures within wildlife trafficking, and disruption of their networks. Geospatial data standards help enable broader utilization of wildlife trafficking data across disciplines and sectors, accelerate aggregation and analysis of data across space and time, advance evidence-based decision making, and reduce wildlife trafficking.
Identifiants
pubmed: 35660766
doi: 10.1038/s41597-022-01371-w
pii: 10.1038/s41597-022-01371-w
pmc: PMC9166703
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
267Subventions
Organisme : National Science Foundation (NSF)
ID : 1935451
Informations de copyright
© 2022. The Author(s).
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