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add eduWRENCH learning resource #78

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2 changes: 2 additions & 0 deletions documentation/1.0/glossary.md
Original file line number Diff line number Diff line change
Expand Up @@ -69,3 +69,5 @@ Processes can run in three different ways:
1. Results can be pre-computed by creating a ***batch job***. They are submitted to the back-end's processing system, but will remain inactive until explicitly put into the processing queue. They will run only once and store results after execution. Results can be downloaded. Batch jobs are typically time consuming and user interaction is not possible although log files are generated for them. This is the only mode that allows to get an estimate about time, volume and costs beforehand.
2. A more dynamic way of processing and accessing data is to create a **secondary web service**. They allow web-based access using different protocols such as [OGC WMS](http://www.opengeospatial.org/standards/wms) (Open Geospatial Consortium Web Map Service), [OGC WCS](http://www.opengeospatial.org/standards/wcs) (Web Coverage Service) or [XYZ tiles](https://wiki.openstreetmap.org/wiki/Slippy_map_tilenames). These protocols usually allow users to change the viewing extent or level of detail (zoom level). Therefore, computations often run *on demand* so that the requested data is calculated during the request. Back-ends should make sure to cache processed data to avoid additional/high costs and reduce waiting times for the user.
3. Processes can also be executed **on-demand** (i.e. synchronously). Results are delivered with the request itself and no job is created. Only lightweight computations, for example previews, should be executed using this approach as timeouts are to be expected for [long-polling HTTP requests](https://www.pubnub.com/blog/2014-12-01-http-long-polling/).

To learn more about the concepts of cloud computing and processing modes in general, have a look at the online course [eduWRENCH](https://eduwrench.ics.hawaii.edu/ "The goal of eduWRENCH is to achieve various learning objectives in the areas of parallel computing, distributed computing, and cyberinfrastructure computing").