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rOpenSci - open tools for open science

rOpenSci - open tools for open science
Open Tools and R Packages for Open Science
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Published

rOpenSci HQ rOpenSci received a $678K award from the Sloan Foundation to expand Software Peer Review. We are hiring for a new position in statistical software testing and peer review. Join our next Community Call on Reproducible Workflows at Scale with drake September 24th. Videos, speakers’ slides, resources and collaborative notes from our Community Calls on Involving Multilingual Communities and Reproducible Research with R are posted.

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Introduction The availability of large quantities of freely available data is revolutionizing the world of ecological research. Open data maximizes the opportunities to perform comparative analyses and meta-analyses. Such synthesis efforts will increasingly exploit “population data”, which we define here as time series of population abundance.

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Ambitious workflows in R, such as machine learning analyses, can be difficult to manage. A single round of computation can take several hours to complete, and routine updates to the code and data tend to invalidate hard-earned results. You can enhance the maintainability, hygiene, speed, scale, and reproducibility of such projects with the drake R package.

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Authors Karthik Ram, Noam Ross

Are you passionate about statistical methods and software? If so we would love for you to join our team to dig deep into the world of statistical software packages. You’ll develop standards for evaluating and reviewing statistical tools, publish, and work closely with an international team of experts to set up a new software review system.

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The grainchanger package provides functionality for data aggregation to a coarser resolution via moving-window or direct methods. Why do we need new methods for data aggregation? As landscape ecologists and macroecologists, we often need to aggregate data in order to harmonise datasets. In doing so, we often lose a lot of information about the spatial structure and environmental heterogeneity of data measured at finer resolution.

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Authors Karthik Ram, Noam Ross

We’re delighted to announce that we have received new funding from the Alfred P. Sloan Foundation. The $678K grant, awarded through the Foundation’s Data & Computational Research program, will be used to expand our efforts in software peer review.

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Our 1-hour Call on Reproducible Research with R will include three speakers and 20 minutes for Q & A. Ben Marwick will introduce you to a research compendium, which accompanies, enhances, or is a scientific publication providing data, code, and documentation for reproducing a scientific workflow.

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Three members of the rOpenSci team - Scott Chamberlain, Jenny Bryan, and Rich FitzJohn - as well as many community members will give talks at useR!2019. Many other package authors, maintainers, reviewers and unconf participants will be there too. Don’t hesitate to ask them about rOpenSci packages, software peer review, community, or just say hello if you’re looking for a friendly face. We’ve listed their talks for you.

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rOpenSci HQ 👨🏽‍💻👩🏼‍💻 🏗️ Join our next Community Call on Involving Multilingual Communities June 28th. Video of our Community Call on Security for R is up, with a long list of resources. Our Community Manager, Stefanie Butland, spoke at R-Ladies Seattle and Fred Hutch about rOpenSci, Learning R, and Building Community May 22nd.

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rOpenSci’s community is increasingly international and multilingual. While we have operated primarily in English, we now receive submissions of packages from authors whose primary language is not. As we expand our community in this way, we want to learn from the experience of other organizations. How can we manage our peer-review process and open-source projects to be welcoming to non-native English speakers?