- From: mathib via GitHub <sysbot+gh@w3.org>
- Date: Thu, 11 Mar 2021 17:21:28 +0000
- To: public-dxwg-wg@w3.org
> About your question, DCAT at the moment does not include the features you mention - the main point is whether they are in scope with DCAT or better left to DCAT profiles (as yours). We'll discuss this. I think it is, as I'm probably not the only one dealing with RDF publication mechanisms that include quads. > I see that you have notions as cdc:AdditionAndDeletionDistribution. Would you mind providing a summary of them? This is a bit more difficult to explain and different from the dataset versioning as required in the #1289. I developed the notion of dataset complements, i.e. a distribution of a dataset2 that complements an older dataset1 from another or the same organization (e.g. in the case of heavy collaboration as is normal during a construction project). As such, it's not necessary for the stakeholder who wants to add and/or remove parts of the received dataset, when creating their own contributions, to literally introduce the triples from someone else in his/her new dataset. It's enough that on DCAT level, there's the indication of which dataset distribution adds (`cdc:AdditionDistribution`), deletes (`cdc:DeletionDistribution`) or both adds and deletes (`cdc:AdditionAndDeletionDistribution`) content. For practical situations such as querying and reasoning over a dataset combined with a deletion, there's also an option to calculate the resulting dataset based on the additions and/or deletions. Using the `cdc:StandaloneDistribution` class and `cdc:standaloneOf` property, it's possible keep track of this 'standalone' distribution on dataset metadata level. Maybe the following diagram with an example might help to clearify things (where dataset C comes from stakeholder1 and dataset D comes from stakeholder2 who proposes a correction that consists of a deletion and an addition):  The benefits of this approach is that (as long as the additions and/or deletions are smaller compared to the original dataset), that it's easier to exchange changes and to keep track of who said what on data level (responsabilities). I would say that this collaboration approach is orthogonal to dataset versioning as you always complement a specific dataset version. -- GitHub Notification of comment by mathib Please view or discuss this issue at https://github.com/w3c/dxwg/issues/1241#issuecomment-796903779 using your GitHub account -- Sent via github-notify-ml as configured in https://github.com/w3c/github-notify-ml-config
Received on Thursday, 11 March 2021 17:21:29 UTC