Careful evaluation of your data is necessary if you want to achieve accurate and reliable results from SmarterWX. If your project or exclusion zone boundaries are drawn incorrectly, or dates are entered in error, then any opportunities and/or conflicts reported may potentially be false. Ensure your data is accurate, complete, current, contains the correct spatial reference and has been approved prior to loading it into the SmarterWX system.
How your data is organised will also have a big impact on how opportunities and/or conflicts are reported. It is strongly recommended that you group tasks or child projects within a defined area and time into a single project. As an example, you may be installing TGSIs (Tactile Ground Surface Indicators) to improve the safety at an intersection. This should be entered as a single project for all four TGSIs not four separate projects. Remember projects are defined by a region and time range and should not be individual tasks. If four projects were created in this example sixteen opportunities could be falsely created.
The areas you need to check before loading you data are:
- Projects and exclusion zones must be stored in separate files (or separate feature services for Live Connect)
- Data is created using an appropriate spatial reference (eg. MGA94 Zone56)
- Data is stored in a supported format (see list below)
- Data is the most recent data available
- The start and end date information entered is formatted correctly for all records
- End dates occur after the start dates
- Any use restrictions that may limit or prevent you publishing your data to SmarterWX
- Accuracy of data. If possible use polygons captured at a larger scale.
- Data can be added to SmarterWX using Point, Line, Polygon or Multi-Polygon geometries. Point and line features will be buffered to turn them into polygons as part of the publishing process.
- Data uploaded using a CSV file will include latitude and longitude columns.
- Esri File Geodatabase (.gdb)
- Esri Shapefile (.shp)
- MapInfo TAB File (.tab)
- KMZ (Google) (.kmz)
- Comma Separated Values (CSV) (.csv)
You can discover errors in your data through a combination of automated and visual checks
- Automated checks allow you to use ArcGIS to create tables or other data to quickly assess whether you have spatial or attribute errors. These automated checks are often done before the more time-consuming visual checks of your data. The ArcGIS geodatabase also has specialised functionality that can help you locate both attribute and spatial errors in your data.
- Visual checks are often time-intensive and involve symbolising data and labeling features to look for completeness, consistency, and accuracy errors.