Item talk:Q261616
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Paths to computational fluency for natural resource educators, researchers, and managers", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70223414", "url": "https://pubs.usgs.gov/publication/70223414" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70223414 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.1111/nrm.12318", "url": "https://doi.org/10.1111/nrm.12318" } ], "journal": { "@type": "Periodical", "name": "Natural Resource Modelling", "volumeNumber": "34", "issueNumber": "3" }, "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Natural Resource Modelling" } ], "datePublished": "2021", "dateModified": "2021-08-26", "abstract": "Natural resource management and supporting research teams need computational fluency in the data and model-rich 21st century. Computational fluency describes the ability of practitioners and scientists to conduct research and represent natural systems within the computer's environment. Advancement in information synthesis for natural resource management requires more sophisticated computational approaches, as well as reproducible, reusable, extensible, and transferable methods. Despite this importance, many new and current natural resource practitioners lack computational fluency and no common set of recommended resources and practices exist for learning these skills. Broadly, attaining computational fluency entails moving beyond the simple use of computers to applying sound computational principles and methods and including computational experts (such as computer scientists) on research teams. 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