[This article was first published on GivenTheData, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Alois Stutzer and I recently contributed a guest post to the BITSS-Blog (of the Berkeley Initiative for Transparency in the Social Sciences). As a big part of it focuses on R-related topics, I figured it might also be of interest for readers of this blog. Here the gist:
“The replicability of social science research is becoming more demanding in the age of big data. First, researchers aiming to replicate a study based on massive data face substantial computational costs. Second, and probably more challenging, they are often confronted with “highly unique” data sets derived and compiled from sources with different and unusual formats (as they are originally generated and recorded for purposes other than data analysis or research). This holds in particular for Internet data from social media, new e-businesses, and digital government. More and more social scientists attempt to exploit these new data sources following ad hoc procedures in the compilation of their data sets.
…”
The entire post can be found here.
In this context, I also want to explicitly point to all the very relevant contributions listed in the CRAN Task View on Web Technologies and Services, the CRAN Open Data Task View, as well as the contributions by rOpenSci.
“The replicability of social science research is becoming more demanding in the age of big data. First, researchers aiming to replicate a study based on massive data face substantial computational costs. Second, and probably more challenging, they are often confronted with “highly unique” data sets derived and compiled from sources with different and unusual formats (as they are originally generated and recorded for purposes other than data analysis or research). This holds in particular for Internet data from social media, new e-businesses, and digital government. More and more social scientists attempt to exploit these new data sources following ad hoc procedures in the compilation of their data sets.
…”
The entire post can be found here.
In this context, I also want to explicitly point to all the very relevant contributions listed in the CRAN Task View on Web Technologies and Services, the CRAN Open Data Task View, as well as the contributions by rOpenSci.
To leave a comment for the author, please follow the link and comment on their blog: GivenTheData.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.