By applying statistical tricks to account for sampling bias, the researchers were able to determine that between 45 - 48%, or just under half, of the world's plants are woody. "[The take home lesson is that] all big databases are biased, but by acknowledging that bias is universal and accounting for it we can make better use of them," said co-author Rich FitzJohn of Macquarie University
The researchers learned another lesson when they published their work. Their goal was to make enough information about their methods available such that other researchers could retrace their steps. Could someone -- using the same data and code, but a different computer -- get the same or similar results?
In an ideal word, reproducing the analyses should be as simple as installing the necessary software, downloading the data and hitting 'run.' But software changes from one version to the next. Analysis standards evolve. Analyses that run on one machine don't always work on another.
Making a study easily reproducible, they found, requires a significant amount of time and technical skill. They made sure that everything needed to download and manipulate the data and even create the figures, was written into the code, and explained the thinking behind each snippet of code. They also provided links to tools that would enable researchers to compare changes between different versions of software and restore and run previous versions if need be.
"Nobody denies that researchers should try to make their work reproducible so that others can check their results, but actually making that feasible is easier said than done," FitzJohn said.
|Contact: Robin Ann Smith|
National Evolutionary Synthesis Center (NESCent)