Table 3

Sharing OSs with the scientific community. Access could be extended to a lay audience; however, the nature of the information will be most useful to scientists. Modified from Khoury et al. (26).

Information type Comments
Data set registrationShould be feasible to achieve in large scale; each data set registers the variables that it has collected and their definitions; this would allow knowing how many studies with how many participants who have measured variables or markers of interest, instead of guessing what data are available on that marker beyond what has been published
Availability of detailed dataIndividual-level (raw) data are made available; this practice may be subject to policy/consent/privacy constraints for past studies and their data; easier to anticipate and encourage in the design of future studies
Availability of data, protocols, and analyses codesOptimal ability to evaluate the reproducibility of analyses, to maximize the integration of information across diverse studies, and to allow improvements on future studies based on exact knowledge of what was done in previous studies
Live streaming of analysesInvestigators not only post all their data and protocols online, but analyses are done and shown in real time to the wider community as they happen. Live streaming can be coupled with crowd sourcing of analyses across large communities of analysts