All posts (Page 78 of 125)
eBird is an online tool for recording bird
observations. The eBird database currently contains over 500 million
records of bird sightings, spanning every country and nearly every bird
species, making it an extremely valuable resource for bird research and
conservation. These data can be used to map the distribution and
abundance of species, and assess how species’ ranges are changing over
time. This dataset is available for download as a text file; however,
this file is huge (over 180 GB!) and, therefore, poses some unique
challenges. In particular, it isn’t possible to import and manipulate
the full dataset in R. Working with these data typically requires
filtering them to a smaller subset of desired observations before
reading into R. This filtering is most efficiently done using AWK, a
Unix utility and programming language for processing column formatted
text data. The auk package acts as a front end for AWK, allowing users
to filter eBird data before import into R, and provides tools to perform
some important pre-processing of the data. Them name of this package
comes from the happy coincidence that the command line tool
AWK, upon which
the package is based, is pronounced the same as
auk, the family of sea birds also
known as Alcids.
🔗
Motivation
Note: Recently, two new UMAP R packages have appeared. These new packages provide more features than umapr does and they are more actively developed. These packages are:
...umap, which provides the same Python wrapping function as umapr and also an R implementation, removing the need for the Python version to be installed. It is available on CRAN.uwot, which also provides an R implementation, removing the need for the Python version to be installed.
tl;dr: we propose three calls to action:
- Share your curricular materials in the open.
- Participate in the rOpenSci Education profile series.
- Discuss with us how you want to be involved in rOpenSci Educators’ Collaborative.
In previous posts in this series, we identified challenges that individual instructors typically face when teaching science with R, and shared characteristics of effective educational resources to help address these challenges. However, the toughest challenges that educators in this area face are human, rather than technological. Our shared experiences highlight the need for a strong community of innovative R educators. However, this community is currently not well-connected or easily discoverable.
...In the first post of this series, we sketched out some of the common challenges faced by educators who teach with R across scientific domains. In this post, we delve into what makes a “good” educational resource for teaching science with R.
For instructors teaching sciences with R, there are a number of open educational resources that they can reuse, tailor to their own teaching style, or use to inspire them in creating their own materials. Some examples:
...
Educators who teach science using R tend to face common pedagogical problems, regardless of their scientific domain. Yet instructors who teach with R often feel isolated at their institutions. They may be the only ones in their departments to teach using R. Even if there are others, the culture of collaboration around teaching is generally impoverished, unlike the rich culture of collaboration around research. In this three-part series of blog posts, participants at the rOpenSci 2018 unconf briefly survey the state of teaching science with R.
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