GRASS GIS Basic Datasets

Background

Standardized basic GRASS GIS dataset is an updated, restructured dataset to be used in manual pages, tutorials, courses, code testing, development and OSGeo Live. Localized versions of the dataset support common instructions, tutorials and teaching materials for different regions in the world.

Datasets for GRASS7 and GRASS8

• Wiki page with examples and list of existing datasets is at GRASS Wiki: GRASS GIS Standardized Sample Datasets.
• Track wiki page with the original discussion for GRASS 7 is at GRASS GIS Sample Datasets.
• Download links on GRASS GIS website: GRASS GIS Sample Data

Common rules

• Names of map layers must be the same for all standardized datasets. No additions to names such as `_10m` or `_wake_county` are allowed. This also implies that names must be in English, national language is not allowed for national standardized datasets (however, if desired, we can can work on a script which would automatically rename multiple maps in dataset and would also find and replace names in documentation and tutorials).
• To keep the basic data set simple, specialized map layers are moved into separate mapsets, for example, statewide data at lower resolutions or high resolution lidar or UAS based data, data time series, etc.
• Description in tables here should be usable as title of the map. Separate details in description, which should not be part of the title, using commas or parentheses. Titles can differ between standardized datasets and can use national language (unlike names).

References

• Petras, V., Petrasova, A., Harmon, B., Meentemeyer, R.K., Mitasova, H. Integrating Free and Open Source Solutions into Geospatial Science Education. ISPRS International Journal of Geo-Information. 2015, 4, 942-956. doi:10.3390/ijgi4020942 (Contains explanation of usage of the GRASS GIS commands concept to get teaching materials which are easy to maintain.)

• GRASS GIS Standardized Sample Datasets, 2016. Past examples for North Carolina; Piemonte, Italy, and Czechia.

• QGIS Training manual which uses similar concept and has instructions to create similar dataset to the provided one with the local geospatial data and has a script to replace some values in the teaching material itself.

Funding

• NSF POSE II # 2303651 Growing GRASS OSE for Worldwide Access to Multidisciplinary Geospatial Analytics