- From: Eric Stephan via GitHub <sysbot+gh@w3.org>
- Date: Thu, 02 Jul 2020 20:18:36 +0000
- To: public-dxwg-wg@w3.org
@dr-shorthair - I prefer hasPart because it has an inverse relation isPartOf that I can use to represent a list, tree or any dag structure for a dataset composed of other datasets. @riccardoAlbertoni - A classic example in the modeling and simulation (M&S) world where a published dataset is comprised of many other datasets (in this case a dataset could be a file or a directory of files). simulation run dataset A is composed of other datasets that includes: - human readable description of the simulation experiment - input parameters - model that was used for the simulation (for example network feeder model for power grid study - configuration settings for the simulation - domain specific output produced by the simulation - logfiles or provenance explaining lineage, errors during the simulation A sensitivity study is where the simulation is run a thousand times altering only one or two input parameters to understand the input's impact on simulation output. In this case, the sensitivity study is a dataset, the 1000 simulation datasets are a part of the sensitivity study, and all of input parameter, model, configuration settings, output, and logfile datasets are a part of a given parent simulation. Yes this does have overlaps with Provenance for the simulation team running the experiments, but the consumers of published simulation runs and sensitivity studies are more interested in the composition of the dataset when analyzing published experiments. Does this help? -- GitHub Notification of comment by ericstephan Please view or discuss this issue at https://github.com/w3c/dxwg/issues/1243#issuecomment-653202976 using your GitHub account
Received on Thursday, 2 July 2020 20:18:37 UTC