Application integration in data conversion quality Measurement
For some required data, indirect checking is the only feasible way to estimate or validate
facilities attributes. The best example of this is determining the interior conditions of water
distribution piping. By running a model of the water system developed from the GIS data, the
field versus model comparison can be used to assign pipe interior condition parameters (Hazen-
Williams C factor, Darcy-Weisbach friction factor, effective inside diameter, and/or pipe
efficiency) that result in the best match between the recorded pressures and flows and the model
results. The results of the field and hydraulic model comparison may dictate the need for some
field testing to measure individual pipe capacities for critical backbone lines.
Figure 1 illustrates a data discrepancy that would be difficult and time-consuming to find using
traditional data checking, but should be uncovered by a network model.
Figure 1: Example of System Piping Connections Best Checked Using Hydraulic Modeling
Much could be said about approaches to conducting field and record checking, including how to
determine the appropriate statistical sampling groups. Further exploration of field and record
checking is outside the scope of this paper. Therefore the following sections concentrate on the
opportunities to incorporate indirect checking that results in enhanced GIS data quality and
reduced expenditures.
Indirect Data Quality Evaluation
Indirect checking applies in cases where the question: "If my model reasonably matches the
system instrumentation, will my confidence in the GIS data be enhanced?" can be answered
"Yes". There are two important criteria that must be considered in addressing this question.
They are:
- Is there sufficient system instrumentation and is it accurate enough to support an indirect data check?
- Is the software capable of building the model from the GIS data and does the application
provide results that are sufficiently accurate for this type of comparison?
The first question has several very important considerations. The existing system
instrumentation may not be adequate in terms of having a sufficient number of instruments in the
required locations. System instrumentation is generally prescribed by the operations department
and is targeted to meet operating needs. Typically, there is monitoring of key external or internal
supplies and regulation points, recording of conditions for important customers or those with
contracts that specify the service quality (voltage, pressure, etc.), and at a few locations that have
had past pressure or voltage concerns.
Compared to the considerable savings and benefits that result from indirect data validation, the
cost to incorporate sufficient additional instrumentation is minor. Beyond the GIS validation
benefits, the resulting data will also support more accurate calibration of the network model. A
more accurate model can be leveraged into better work prioritization, reduced capital
improvement project costs, and improved service in terms of service quality and outage service
restoration. Some utilities have reduced the net cost of expanding their instrumentation coverage
by optimizing the locations of existing equipment and maintaining an inventory of mobile
instruments that are rotated through the system to support calibration data collection.
The leading edge network modeling software has evolved to the point where predictive models
of any size network can be created, with the resultant model accuracy ostensibly limited only by
the validity of the underlying facility and consumption data. Likewise, moderate priced desktop
computers will support detailed integrated facility and customer usage models for large systems,
including modeling the implications of multiple supplies, parallel regulation, and temporary
backfeeds to customers. These desktop applications can now utilize the highly granular data in
GIS systems, with model simplification/skeletonization being an option, not a requirement.
Computing and instrumentation technology are at a point where accurate network analysis
software and instrumentation to support model calibration can be implemented at any utility with
moderate cost. For a GIS project, the savings resulting from greater use of indirect data
validation and higher quality data sets will overshadow the cost of implementing a network
analysis system sophisticated enough to support the GIS project quality assurance program.
Advantages and Benefits of Indirect Checking
Incorporating applications that use the GIS data into the quality assurance system provides a
number of direct and indirect benefits to the utility, including:
- Reduced costs of topology and attribute data validation
- More efficient prioritization and use of field check staff, by focusing the initial field checking on areas identified by the application's results
- The ability to further prioritize field-checking, for example, by concentrating on areas the network hydraulic analysis identifies as having marginal capacity. Typically, some of these problems are caused by data errors, while others may result in the discovery of areas in need of reinforcement.
- Ability to evaluate system conditions to the level of detail included in the GIS. For example, the GIS-based model will identify localized system deficiencies that would not appear in a simplified (skeletonized) model or summarized data set.
- Using key applications early in the project proofs the adequacy of the GIS data schema and interface to support internal and external applications vital to the business.
- Applications that use the GIS data provide a check of the project data capture and data conversion processes. On the contrary, field checking and record checking refine the source data but provide no GIS database population processes checking.
- If an outcome of the GIS project is the replacement of a software application that has high user confidence with a new application that is more GIS-centric, the end users will have more time to become comfortable with the new application and will be able to check that the GISbased system can produce the same results for equivalent system conditions
- Use of key applications can serve as tools in the project quality assurance system, reducing the need to develop project specific quality control applications.
- Using key applications early in the data conversion process minimizes the project risk by avoiding unpleasant compatibility surprises and expensive re-work in the late stages of the project.
- Forces the GIS development to have a strong user focus.
