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Our Packages

Use our carefully vetted, staff- and community-contributed R software tools that lower barriers to working with local and remote scientific data sources. Combine our tools with the rich ecosystem of R packages.

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Computing Infrastructure

Workflow Tools for Your Code and Data

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Data Access

Get Data from the Web

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Data Extraction

Convert and Munge Data

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Data Publication

Document and Release Your Data

Visualize Data

Work with Databases From R

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Geospatial

Access, Manipulate, Convert Geospatial Data

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HTTP tools

Interact with Web Resources

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Image & Audio Processing

Use Image & Audio Data

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Literature

Access Scientific Literature Databases, Analyze Scientific Papers (and Text in General)

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Security

Secure Your Data and Workflow

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Statistics

Statistical algorithms and statistics-specific workflows

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Taxonomy

Handle and Transform Taxonomic Information

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Explore Use Cases

Get inspired by real examples of how our packages can be used.

Explore Citations

Or browse scientific publications that cited our packages.

Our Software Review Process

Our suite of packages is comprised of contributions from staff engineers and the wider Rcommunity via a transparent, constructive and open review process utilising GitHub's opensource infrastructure.

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Open Reviews

We combine academic peer reviews with production software code reviews to create atransparent, collaborative & more efficient review process

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Guidance & Standards

Based on best practices of software development and standards of R, itsapplications and user base.

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Active Community

Our diverse community of academics, data scientists and developers provide aplatform for shared learning, collaboration and reproducible science

Review for rOpenSci

Our Community

We welcome you to join us and help improve tools and practices available toresearchers while receiving greater visibility to your contributions. You cancontribute with your packages, resources or post questions so our members will helpyou along your process.

Our community