Abstract
Although data quality has been well accepted as an essential component of geospatial data, it has not received its deserved attention in geographic information system (GIS)-based applications over the years. Users are forced to deal with data of unknown or ambiguous quality, and thus unpredictable risk in decision making is inevitable. Quality information must be fully assimilated into the design of GIS functions and further extended to the visualization of processing results. This requirement is particularly necessary for users who do not possess the required knowledge to correctly interpret the outcomes of GIS functions. We propose a quality-aware workflow design approach driven by standardized quality information and then use the data select-by-region function as an example to demonstrate how quality information changes the traditional design principles of GIS functions. The proposed workflow not only improves the interoperability of heterogeneous geospatial data but also significantly increases the intelligence of GIS-based functions.
Original language | English |
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Title of host publication | Uncertainty Modelling and Quality Control for Spatial Data |
Publisher | CRC Press |
Pages | 45-66 |
Number of pages | 22 |
ISBN (Electronic) | 9781498733342 |
ISBN (Print) | 9781498733281 |
DOIs | |
Publication status | Published - 2015 Jan 1 |
All Science Journal Classification (ASJC) codes
- General Mathematics
- General Engineering
- General Earth and Planetary Sciences
- General Environmental Science