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Product quality assurance for GIS life-cycle
Quality in context of GIS Quality is commonly used to indicate the superiority of a manufactured good or to indicate a high degree of craftsmanship or artistry. Quality is a desirable goal achieved through management and control of the production process (statistical quality control). ). Many of the same issues apply to the quality of GIS databases, since a database is the result of a production process, and the reliability of the process imparts value and utility to the database [ 4 ]. Spatial Data Quality Data quality is the degree of excellence in a database. It can simply be defined the fitness for use for a specific data sets. It is fully dependent on the scale, accuracy, and extent of the data set, as well as the quality of the other data sets to be used. The conventional view is that geographical data is “spatial”, so a better definition of geographical data should include the three dimensions of Space, Time and Theme (where-when-what). These three dimensions are the basis for all geographical observation ( 1 ). Data quality also contains several components such as accuracy, precision, consistency and completeness. The result is a matrix as defined below. Table 1: Matrix showing geographical dimensions & Quality 
The three components of space, theme, and time are covered by the first three Primary Parameters. The last two indicate: on the one hand if the data set is complete in terms of the queries that one wants to answer with the help of this data set and on the other hand if the representation of the data is consistent within itself. If all possible accuracy values have to be evaluated the costs of information on accuracy would be too high and thus not affordable [ 1 ]. Quality Parameters In the following a closer look at each of the five Primary Parameters pertaining to GIS quality and their associated sub-parameters are discussed. Accuracy Accuracy is the degree to which information on a map or in a digital database matches Actual/ True or Accepted values. The discrepancy between the encoded and actual value of a particular attribute for a given entity is defined as an “error”. Accuracy is an issue pertaining to the quality of data and the number of errors contained in a data set or map. In discussing a GIS database, it is possible to consider horizontal and vertical accuracy with respect to geographic position, as well as attribute, conceptual, and logical accuracy. The level of accuracy required for particular applications varies greatly. Highly accurate data can be very difficult and costly to produce and compile. Accuracy is always a relative measure, since it is always measured relative to the specification. To judge fitness-for-use, one must judge the data relative to the specification, and also consider the limitations of the specification itself [ 1 ]. Table 2: Example of E-A-V model.
Definition of accuracy is based on the entity-attribute-value model (Table- 2) Entities = real-world phenomena Attribute = relevant property Values = Quantitative/qualitative measurements Spatial Accuracy Spatial accuracy is the accuracy of the spatial component of the database. The metrics used depend on the dimensionality of the entities under consideration. For points, accuracy is defined in terms of the distance between the encoded location and “actual” location. Error can be defined in various dimensions: x, y, z, horizontal, vertical, total. Metrics of error are extensions of classical statistical measures such as mean error, RMSE or root mean squared error, inference tests, confidence limits, etc. For lines and areas, the situation is more complex. This is because error is a mixture of positional error (error in locating well-defined points along the line) and generalization error (error in the points selected to represent the line) ( 3 ). The epsilon band is usually used to define a zone of uncertainty around the encoded line, within which “actual” line exists with some probability. However, there is little agreement on the shape of the band, both planimetrically and in cross-section. The spatial position of an arbitrary object defined within a GIS data layer has a positional error that can be described by one of the Primary Parameters, Positional Accuracy. Temporal accuracy Temporal accuracy is the agreement between the encoded and “actual” temporal coordinates for an entity. Temporal coordinates are often only implicit in geographical data, e.g., a time stamp indicating that the entity was valid at some time. Often this is applied to the entire database. More realistically, temporal coordinates are the temporal limits within which the entity is valid. Temporal accuracy is not the same as “currentness” (or up-to-date ness) which is actually an assessment of how well the database specification meets the needs of a particular application. Temporal Accuracy occurs if the GIS data set has a temporal dimension and thus the spatial information data type results in the form of: x,y,z,t. For the error model it is necessary to investigate this additional coordinate for dependencies with the other three in order to pay attention to existing correlation. |