Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Comparative analysis of GeoWebCln tool_
| Cleaning using QGIS functions | Cleaning using GeoWebCln |
|---|---|
| The user must have prior knowledge of GIS cleaning functions and its steps. QGIS is a vast software having various functions. New users are not aware of these functions and need a tutorial before performing the cleaning process. | Users can perform cleaning using a single function with a single click in QGIS. There is no need to analyse the dirty data. A user just needs to import the cleaning function in the Python console of QGIS and click on the run tab. The vector layer will be cleaned. |
| It is suitable for trained GIS users. The cleaning needs expertise in QGIS and cannot be handled by novice users. | It is suitable for all types of users. |
| It is a time-consuming process as it requires operation and analysis of various GIS functions such as JOIN, DELETE and SQL Query in Advance Filter Expression. | It is a very fast cleaning process. There is no need for any GIS function and query execution. |
| It is not an interactive approach as no input is asked from the user. The user is not aware of the work performed by the GIS functions. | It is interactive and user-friendly as input is asked from a user before the removal of duplicate values. |
| It is less reliable as cleaning performance depends on the skills of the user. If the user chooses wrong functions, then cleaning is not done properly. | It is reliable as cleaning is performed by the GeoWebCln tool itself without depending on the skills of the user. |
| Incapable to provide cleaning information of attributes. The summary of cleaned data is not available. | Provide cleaning information of the attributes as shown in Figure 12. |
| The cleaned layer cannot be automatically saved. | The cleaned layer is saved as a new layer automatically after cleaning. |
| Metadata information of spatial data cannot be stored for future use. | Metadata information of cleaned data is exported as CSV files and can be used for comparison and analysis. |
| Data quality parameters such as completeness, consistency and accuracy cannot be perceived by the users after cleaning as no cleaning information is provided. | Users can easily judge the quality parameters after analysing summary information. |
| Output as cleaned vector layer is not distinguishable from the dirty layer. | Output as the cleaned vector layer is apparent to the dirty layer as shown in Figure 14. Spatial data in green is cleaned data and is free from errors. |
Algorithm: GeoWebCln Algorithm
|