Most importantly -- when researchers
know their data and methodology will be out in the open they'll have a big incentive to make it look clean and presentable. They know they risk getting called out on excluding certain segments of the data set, so they'll have to at the
very least add a small remark in the spreadsheet justifying their decision. It also makes it really easy for other researchers to pick other start and end years to test if the result only holds for the original data. Which again, encourages researchers to explain justify the input data they've chosen.
In addition, researchers are likely to discover mistakes while cleaning up the excel sheet, data sources and code before publishing it. Just like we find mistakes in our work while refactoring and cleaning up code before we push it to github.
So even when nobody ever looks at the data and code we can expect the quality of the research to improve significantly: just because the code is there to be looked at.
I think the case in favor of making data & code public for academic research is pretty overwhelming.
In addition, researchers are likely to discover mistakes while cleaning up the excel sheet, data sources and code before publishing it. Just like we find mistakes in our work while refactoring and cleaning up code before we push it to github.
So even when nobody ever looks at the data and code we can expect the quality of the research to improve significantly: just because the code is there to be looked at.
I think the case in favor of making data & code public for academic research is pretty overwhelming.