For this project, I have developed a pilot software for data quality assurance of 3D buildings. The software checks the CityGML and CityJSON formats againts pre-defined quality rules and creates an output report containing all founded violations in the tabular or geometrical format.
Totally the software contains over 40 quality rules or criteria mostly focusing on the building geometry. For example, it checks that 3D buildings do not intersect, overlap, contain spikes, invalid orientations, duplicates and so on. The complete list of implemented rules can be found from the GitHub and it is always possible to create new rules for more specific use cases.
Some rules are stricter than others. If the feature do not pass the rule, there are three options. First, the software can fix features automatically. If that is not possible, the software either discards features or write down all errors. The image below illustrates the hierarchy and workflow of implemented rules in the case of CityGML data.
In addition of achieving high quality data sets, this kind of quality assurance software is an excellent tool to facilitate data integration processes. It ensures that all data sets from multiple sources have a same quality level, which is needed for successful integration. The software is based on the FME Desktop, so it is relatively easy to use and modify. For that reason, everyone can utilize the software for their own purposes.
If you want to improve your data quality, you can download and try the software from the GitHub (requires the FME licence). And don’t forget to check our e-learning module about data quality assurance!