GeoWebCln: An Intensive Cleaning Architecture for Geospatial Metadata

Sheoran, Savita Kumari; Parmar, Vinti

doi:10.2478/quageo-2022-0004

Abstract

Developments in big data technology, wireless networks, Geographic information system (GIS) technology, and internet growth has increased the volume of data at an exponential rate. Internet users are generating data with every single click. Geospatial metadata is widely used for urban planning, map making, spatial data analysis, and so on. Scientific databases use metadata for computations and query processing. Cleaning of data is required for improving the quality of geospatial metadata for scientific computations and spatial data analysis. In this paper, we have designed a data cleaning tool named as GeoWebCln to remove useless data from geospatial metadata in a user-friendly environment using the Python console of QGIS Software.

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GeoWebCln: An Intensive Cleaning Architecture for Geospatial Metadata

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