All posts (Page 66 of 123)
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Importance of Hydrology
Given that liquid water is essential to life on Earth, water research cuts across numerous disciplines including hydrology, meteorology, geography, climate science, engineering, ecology, and more. Numerous R packages have emerged from this diversity of approaches, and we recently gathered many of them into a new rOpenSci task view which we broadly titled ‘Hydrology’ and published to CRAN. Our intent is to be exhaustive and compile R packages to access, model, and summarise information related to the movement of water across the Earth’s landscape. We hope to contribute to a nascent community of hydrological R users and develop an infrastructure of packages that provide a comprehensive toolkit for water practitioners who use R as their preferred computational analysis tool. Making sense of water data is critical to understanding the response of landscapes to a changing climate. Consolidating water-related packages will promote their usage and discovery and ultimately facilitate reproducible workflows for water research. Since this is a new task view, it serves our purpose to evaluate the current State of Hydrology in R and look at the interdependency of hydrology packages relative to some better known collections of packages in the general R ecosystem.
...Version 7.0.0 of drake just arrived on CRAN, and it is faster and easier to use than previous releases.
install.packages("drake")
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Recap
Data analysis can be slow. A round of scientific computation can take several minutes, hours, or even days to complete. After it finishes, if you update your code or data, your hard-earned results may no longer be valid. How much of that valuable output can you keep, and how much do you need to update? How much runtime must you endure all over again?
...Our next Community Call, on March 27th, aims to help people learn about using rOpenSci’s R packages to access and analyze taxonomy and biodiversity data, and to recognize the breadth and depth of their applications. We also aim to learn from the discussion how we might improve these tools. Presentations will start with an introduction to the topic and details on some specific packages and we’ll hear from several people about their “use cases in the wild”....
Citations are a crucial piece of scholarly work. They hold metadata on each scholarly work, including what people were involved, what year the work was published, where it was published, and more. The links between citations facilitate insight into many questions about scholarly work.
Citations come in many different formats including BibTex, RIS, JATS, and many more. This is not to be confused with citation styles such as APA vs. MLA and so on.
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Introduction
stats19 is a new R package enabling access to and working with
Great Britain’s official road traffic casualty database,
STATS19.
We started the package in late 2018 following three main motivations:
- The release of the 2017 road crash statistics, which showed worsening road safety in some areas, increasing the importance of making the data more accessible.
- The realisation that many researchers were writing ad hoc code to clean the data, with a huge amount of duplicated (wasted) effort and potential for mistakes to lead to errors in the labelling of the data (more on that below).
- An understanding of the concept of ‘modularity’ in software design,
following the Unix
philosophy that
programs should ‘do one thing and do it well’. This realisation has
led to code inside the rOpenSci-hosted package
stplanrbeing split-out into two separate packages:cyclestreetsandstats19.
We have a wider motivation: we want the roads to be safer. By making data on the nature of road crashes more publicly accessible to inform policy, we hope this package saves lives.
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