Error and Uncertainty
A key issue in geographic analysis are the many types of error. Error in measurement and attribution of data can propagate into further analysies, which in turn may be based on faulty assumptions. Errors in code can be remediated in open source projects by having several editors, though bugs in analysis and interpretation can still enter the final product. Often in STEM classes students are asked to interrogate the assumptions made when preforming certain calculations, as I did just now with my geohcem homework. Some assumptions make equations or models unworkable or worse, meaningless. Often in research the models, data collection, and the computers themselves have assumption baked in. Assuming that a reproducing study would have, or know the exact version of software, date of data collection, or acess to certain servers can and often does make reanalysis unworkable.