Networked Electronic and Manual QA of Conversion Data
Electronic QA and Conversion Issues
The combination of an aggressive conversion schedule and the accuracy requirements of the conversion contract (100% connectivity and 98% attributes) created a challenge in QA of converted data. UtiliCorp’s intent is to be able to receive converted data as rapidly as possible and then rigorously examine the quality of this data. It became necessary to develop efficient and flexible QA procedures to detect the types of errors encountered in each phase of the conversion.
The electronic QA tool became the first line of defense in the examination of 63 conversion delivery packets. The electronic QA tool was originally developed by UtiliCorp’s application vendor and was configured by the vendor and UtiliCorp for use on this conversion project. The primary capabilities of the tool are to verify connectivity, object placement, and object attribute values. Toggle settings allow the user to query on all objects or on a partial subset of objects. The size and composition of the sample data set is also user defined. The sample can consist of the data representing the facilities in a defined geographical area, in an entire network, or in the total GIS. The tool also can generate a random sampling to check attributes for a subset of a large number of facilities.
The electronic tool can be configured to make connectivity checks based on UtiliCorp conversion rules. It is also possible to configure the tool to make attribute checks based on UtiliCorp conversion rules. The configuration can be readily altered based on changes in rules from company to company or on evolving standards. The tool provides interactive capabilities— it provides GoTo functionality on flagged errors as well as the opportunity to examine the attributes of a flagged object while within the tool.
The electronic tool is very good at checking facilities information-phasing compatibility, pipe termination, correct number of connections, annotation placement with respect to its object. However, it can’t be expected to do much for certain proofreading needs, especially with regard to landbase features, such as correct road names, presence or absence of features, or non-rulebased attribute checks. Thus it became necessary to develop a scheme for conducting manual QA.
UtiliCorp was fortunate in acquiring the services of a Kansas City minority small business engaged in AM/FM work for utilities. A methodology was developed for taking a random sample of the 1:100 scale map grids, plotting the grids, proofreading paper copies of converted data against paper originals, and generating statistics on each map grid. The statistical methodology is based on UtiliCorp’s U.S.-wide grid system and FAME’s capability to count total objects by type in each grid. Sample sizes are determined using a single sampling method based on Dodge and Romig’s Sanmling Irumection Tables.
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