easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application

Autor: Matteo Di Bernardo, Timothy A. Crombie, Erik C. Andersen, Daniel E. Cook
Rok vydání: 2021
Předmět:
Atmospheric Science
Nematoda
Computer science
computer.software_genre
Field (computer science)
Environmental data
Database and Informatics Methods
Data Management
Multidisciplinary
Ecology
Data Collection
Sampling (statistics)
Software Engineering
Eukaryota
Animal Models
Mobile Applications
Disparate system
Experimental Organism Systems
Caenorhabditis Elegans
Computers
Handheld
Medicine
Engineering and Technology
Mobile device
Sequence Analysis
Research Article
Genotyping
Computer and Information Sciences
Geospatial analysis
Process (engineering)
Bioinformatics
Science
Environment
Research and Analysis Methods
Specimen Handling
Set (abstract data type)
Computer Software
Data visualization
Meteorology
Model Organisms
Animals
Molecular Biology Techniques
Molecular Biology
Metadata
business.industry
Data Visualization
Organisms
Biology and Life Sciences
Humidity
Invertebrates
Earth Sciences
Animal Studies
Caenorhabditis
business
computer
Sequence Alignment
Zoology
Software
Zdroj: PLoS ONE
PLoS ONE, Vol 16, Iss 10, p e0254293 (2021)
ISSN: 1932-6203
Popis: Large-scale ecological sampling can be difficult and costly, especially for organisms that are too small to be easily identified in a natural environment by eye. Typically, these microscopic floral and fauna are sampled by collecting substrates from nature and then separating organisms from substrates in the laboratory. In many cases, diverse organisms can be identified to the species-level using molecular barcodes. To facilitate large-scale ecological sampling of microscopic organisms, we used a geographic data-collection platform for mobile devices called Fulcrum that streamlines the organization of geospatial sampling data, substrate photographs, and environmental data at natural sampling sites. These sampling data are then linked to organism isolation data from the laboratory. Here, we describe the easyFulcrum R package, which can be used to clean, process, and visualize ecological field sampling and isolation data exported from the Fulcrum mobile application. We developed this package for wild nematode sampling, but it is extensible to other organisms. The advantages of using Fulcrum combined with easyFulcrum are (1) the elimination of transcription errors by replacing manual data entry and/or spreadsheets with a mobile application, (2) the ability to clean, process, and visualize sampling data using a standardized set of functions in the R software environment, and (3) the ability to join disparate data to each other, including environmental data from the field and the molecularly defined identities of individual specimens isolated from samples.
Databáze: OpenAIRE
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