Heh, there are a lot of ways to model it, and we've iterated on the details quite a bit and I imagine we'll iterate more in the future, but here's a quick explanation:
In our model, a node is a "run", which is an experimental procedure performed on a sample (or sometimes multiple samples). Each run has input samples, output samples, and structured data results. A notebook entry can have multiple runs associated with it, since a scientist will likely be processing many runs at once, and every run lives in exactly one notebook entry.
A common use case is to take some input sample, perform some transformation on it, and produce a new output sample that will be used downstream. Another common use case is a "screening" step where you take a collection of samples (one run each), run some analyses on those samples, and discard the ones that don't meet certain criteria. So sometimes the output is a new sample, sometimes it's the same as the input, and sometimes there's no output.
An edge indicates that the output of one run will be automatically fed into the input of the next run, and generally shows the flow of physical samples through the different stages.
In our model, a node is a "run", which is an experimental procedure performed on a sample (or sometimes multiple samples). Each run has input samples, output samples, and structured data results. A notebook entry can have multiple runs associated with it, since a scientist will likely be processing many runs at once, and every run lives in exactly one notebook entry.
A common use case is to take some input sample, perform some transformation on it, and produce a new output sample that will be used downstream. Another common use case is a "screening" step where you take a collection of samples (one run each), run some analyses on those samples, and discard the ones that don't meet certain criteria. So sometimes the output is a new sample, sometimes it's the same as the input, and sometimes there's no output.
An edge indicates that the output of one run will be automatically fed into the input of the next run, and generally shows the flow of physical samples through the different stages.