Data standardization of plant-pollinator interactions
Abstract
Background: Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing. Results: Here we present a vocabulary of terms and a data model for sharing plantâpollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plantâpollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plantâpollinator interactions. Conclusions: The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plantâpollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plantâpollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of terms.
Más información
| Título según WOS: | Data standardization of plant-pollinator interactions |
| Título según SCOPUS: | Data standardization of plantâpollinator interactions |
| Título de la Revista: | GigaScience |
| Volumen: | 11 |
| Editorial: | Oxford University Press |
| Fecha de publicación: | 2022 |
| Idioma: | English |
| DOI: |
10.1093/gigascience/giac043 |
| Notas: | ISI, SCOPUS |