> I’m a bit of an R nerd. Ok, that’s a lie; I’m a major R nerd. But for good reason, because R is incredibly useful in streamlining the scientific process, and increasing the ability to replicate findings with less human error.
If only we could make the spreadsheet not get used by most scientist it would be a better place.
That's why programs like Data Carpentry and Software Carpentry, mentioned in the article, are so important. http://www.datacarpentry.org. Most universities actually don't have good opportunities for active researchers (graduate students, postdocs, professors, research staff) to learn programming or effective data skills. But, researchers are really looking to learn the skills. https://www.embl-abr.org.au/news/braembl-community-survey-re... DC and SWC help fill that gap by teaching two-day hands-on workshops that meet researchers where they are to give them the skills and perspectives to get out of spreadsheets and into R and Python.
I'm no big fan of excel, but the modern xlsx format is "open", in that it's documented (though maybe not perfectly). It certainly is possible to read data from it using a variety of open source packages, from LO Calc to libraries like pyxl.
It's not that it's open it is that all the steps are seen and can be repeated. Excel is just manual labor without seeing how the person took the raw data and got to their conclusion.
If only we could make the spreadsheet not get used by most scientist it would be a better place.