- From: Karen Coyle via GitHub <sysbot+gh@w3.org>
- Date: Sun, 28 Feb 2021 00:45:50 +0000
- To: public-dxwg-wg@w3.org
Thanks, @andrea-perego. The use cases that I'm aware of for time-based datasets are: * For a an ongoing serially issued dataset, the ability to know when each issuing cycle or date is expected such that one can program automatic downloads (e.g. first of every month) * Conversely, this also allows a user to quantify if a scheduled update has not been received * The complication is that there are often exceptions to the regularity (e.g. published every week except for the week including December 25 and no publication from August 15-31). Although it may be hard to develop a predictive algorithm* it could be useful to respond via API with helpful comments. The "next" could be a solution if "next" will include a future dataset. (Feb 27 current; next March 6, as recorded on Feb 27) I'm still concerned that "datasetSeries" may eventually need a more specific definition. "... share some common characteristics that groups them" could possibly be augmented with "area of coverage, source of data collection..." and other "characteristics" that will help users know if what they have is a series. \* Libraries have these for serial publications but they are horribly complex -- GitHub Notification of comment by kcoyle Please view or discuss this issue at https://github.com/w3c/dxwg/issues/1272#issuecomment-787211229 using your GitHub account -- Sent via github-notify-ml as configured in https://github.com/w3c/github-notify-ml-config
Received on Sunday, 28 February 2021 00:45:51 UTC