quality assurance for a local government geographic information system: a geo-facilities project...

Cornput., Environ. and Urban Systems, Vol. 12, pp. 13-24, 1988 Printed in the USA. All rights reserved.

019%9715/88 $3.00 + .oo Copyright :C: 1988 Pergamon Press plc

QUALITY ASSURANCE FOR A LOCAL GOVERNMENT GEOGRAPHIC INFORMATION

SYSTEM: A GEO-FACILITIES PROJECT PERSPECTIVE

P. D. Zwick D. P. Costakis

GEOPLAN Center Department of Urban and Regional Planning

University of Florida

ABSTRACT. Of all the procedures utilized in the conversion phase of implementing a Geograph- ic Information System (GIS), perhaps the most important are those pertaining to quality assurance. It is especially important that sound quality assurance procedures be established for the conversion of the base data or base Iaye< as erroneous data may be carried into subsequent databases, thus compounding problems and diminishing the perceived usefulness of the system. This article discusses the quality assurance process and control procedures invoked in the conversion of the property base layer for Alachua County, Florida (GEOMAX project). Since the Alachua County GIS employs a facility management model, specific examples of quality control procedures presented are from that perspective. However, common problems encountered during the conversion process of GIS projects are discussed, along with solutions used to locate and correct those problems within the GEOMAXproject.

Dueker (1979) defines a Geographic Information System (GIS) as “a special type of information system in which the database consists of (1) observations on spatially distributed features, activities, or events, which are definable as points, lines, or areas; and, (2) procedures to collect, store, retrieve, analyze, and display such geographic data” (p. 384). Chapin and Kaiser (1979) describe an urban information system as a tool for maintaining and storing geographically related data, that is used for analysis and decision making, and which is normally located in a central facility. Therefore, “Geo- graphic Information System” may be broken down into three fundamental parts: (1) data, (2) information processing, and (3) a practical usefulness.

In developing a GIS system, project conversion (the transfer of information from manual to digital form) is normally among the first tasks. Since no project conversion is ever totally accurate, a process must be installed into the project that will correct errors generated during conversion. This process called “quality assurance” includes man-

Requests for reprints should be sent to P. D. Zwick, Ph.D., GEOPLAN Center, Department of Urban and Regional Planning, Room 431, Bldg. ARCH, University of Florida, Gainesville, Florida 32611.

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14 P. D. Zwick and D. P. Costakis

agement support, a policy statement and plan, data integrity, and quality control procedures. Furthermore, the quality assurance process must be cost effective. One method to increase cost effectiveness is to correct errors as they are generated.

This article outlines the quality assurance process and control procedures used in the GEOMAX project, in Alachua County, Florida. The article is structured as follows: First, a general method for quality assurance is described. Next, is a presentation of geographic information systems from a facilities management perspective. Third, the quality assurance process as developed within the GEOMAX project is discussed. Last, the results and conclusions from quality assurance in GEOMAX are summarized, with recommendations for the development of quality assurance processes.

QUALITY ASSURANCE METHOD

Quality assurance plans and control procedures are more often employed in private industry than in the public sector (Hunter, O’Neill, & Wallen, 1987). However, guide- lines for quality assurance employed in the private sector can readily be adapted for use

by public agencies. Typically, a quality assurance process (Figure 1) includes (Stebbing, 1986; Ingle, 1985; and Juran, 1988):

Management

POllCY

statement &

Direction

Education 61

Training

I I I I

FIGURE 1. Quality Assurance Process Diagram.

Local Government Geographic Information System 15

1. A policy statement reflecting upper management’s support for an ongoing maintenance of a high quality product;

2. The design of procedures to carry out the quality assurance plan; 3. Education for quality control personnel; 4. The institution of quality audits; 5. The development of quality assurance loops; and 6. The institution of quality circles.

Steps 1 to 4 are self explanatory. Quality assurance looping means to develop feed- back of information and materials from steps located at the end of a quality assurance process in order to analyze the effectiveness of the process. Quality circles are groups of quality control personnel who meet, either on their own time or during scheduled company meetings, to discuss how to better existing quality control procedures.

Errors in the quality of a product result from misinterpretation of procedures, inade- quate training or improper technique, inadvertent mistakes, and/or the intentional sabotage of data or product. Examples of these procedural, training, or inadvertent errors encountered during the graphic conversion process of any GIS include:

1. Misspelled words on maps; 2. Incorrect key or link attribute data which causes errors during data transfer from

existing data storage to the conversion database; 3. Incorrect use of mapping labels; 4. The improper use of line types; 5. Errors in map accuracy with respect to the project’s selected coordinate base; 6. The improper use of descriptive labels; and 7. Stray lines from partially digitized features, such as parcels.

On the other hand, procedures to minimize or eliminate intentional sabotage (destruction of data or product in computer systems) rely on passwords and security systems for entrance to production software, the utilization of time logs for building access, security locks for access to sensitive areas, and limited access to databases for update or maintenance.

GEOGRAPHIC INFORMATION FROM A FACILITIES PERSPECTIVE

The GEOMAX project is the development of a geographic facilities information

system for use by agencies within Alachua County, Florida. The county is mostly residential, containing 84% of the total number of parcels. The basic layer of the GEOMAX system is the property tax parcel database. Alachua County encloses an area of 965 square miles and contains approximately 70,000 parcels of land. The property appraiser’s office has maintained as many as 1,500 hand-drawn property maps to identify property lots for the ad velorum tax database. Digitizing of the 1,500 property maps is complete.

Agencies currently using the system include the Alachua County Regional Informa- tion Center, the City of Gainesville, Gainesville Regional Utilities (GRU), and the University of Florida’s Geo-Facilities Planning and Information Research Center (GEOPLAN). The long range goal is to involve other Alachua County departments by having them “acquire” the system, providing their own thematic databases.

The GEOMAX project employs an IBM Geographic Facilities Information System


(GFIS) (IBM, 1987). GFIS’s are different from GIS’s. The primary differences between other geographic information systems and IBM’s GFIS are: (1) the development of a database management system used by GFIS for the interactive manipulation of multiple databases, graphically displayed at a computer workstation; (2) the ability of GFIS to maintain, store, and retrieve for update or analysis graphic and attribute data structured within virtually the same database record; and (3) the ability of GFIS to identify or trace network facilities as the result of a structural continuity model, rather than by attribute query.

Interactive Management of Multiple Databases

The ability to interactively share data from as many as 256 separately maintained database provides for a greater flexibility of applications development because data can be maintained at the facilities level (for inventory or accounting requirements), and yet aggregated between databases to develop more comprehensive regional policy analysis or plans from these detailed data. Therefore, the aggregation of detailed facilities data provides users with an interactive method of transit between the micro and macro worlds (Figure 2). When owner agencies maintain high quality data about individual facilities, analysis of complicated regional problems can be accomplished more easily and accurately.

One example of this approach is the mapping of existing land use via the aggregation of property information from the county’s property appraisal database. Because the property appraiser collects and maintains land use data for individual property parcels, that is, property facilities within Alachua County, county planners can aggregate individual parcel information to generate county wide land use maps, and accomplish the task in a fraction of the time previously required.

Single Database Record for Graphics and Attributes

A geographic facilities information system utilizes facilities as objects (parcels, power poles, or buildings) or occurrences (crimes, fires, or floods) that have a particular spatial reference. Facilities, complete with any number of graphical representations and data attributes, may be added to a specific database, at a specific spatial location. When facilities are retrieved from one of the interactive databases the data retrieval needs only to get one record (in two parts) from the database. Therefore, the data manager does not have to be concerned with maintaining linkages between facility graphical representations and attribute data-database design insures that they are permanently linked.

Geographic Facilities Continuity Model

The GFIS continuity model is a powerful concept, employed to trace and maintain networks as a result of the models physical structure instead of collecting the segments of a network by query of an attribute field identifier. For example, an electrical power system maintains a closed network through the use of insulators, thereby segregating its high voltage lines from other structures. The network structure model also allows for data retrieval, maintenance, and storage by network; and provides a means of extract- ing selected networks, or portions of a network, from an appropriate database. Once a network model, perhaps arterial roads within a county, is received into the workspace

Local Govern~e~i Geographic infor~atjo~ System

FIGURE 2. Interactive Multiple Databases Providing for Method of Transit Between Micro and Macro Worlds.

environment, an operator has the ability to structurally trace the network from intersection “A” to intersection “B” and to calculate the distance of the trip without querying any attribute fields.

QUALITY ASSURANCE FOR THE GEOMAX PROJECT

Quality assurance consisted of (1) the acquisition of management support and the drafting of a policy statement; (2) the development of a quality assurance plan; (3) methods to ensuring data integrity; and (4) the development and institution of quality control procedures.

Management and Support and Policy Statement

After the successful completion of the project piiot study, the project team recog- nized the necessity for a full-time quality assurance effort. The pilot study indicated that digitizing and conversion errors would occur no matter how careful or diligent conversion was accomplished. As a result, upper management support for the quality assurance plan was perceived to be of paramount importance. In fact, the success of the project relied upon a sound management quality assurance statement or directive.

While profit margin does not play a role in determining management’s support of quality assurance in a local government, cost savings does! However, upper management support in a local government environment means obtaining support from city or county managers, numerous elected officials, and various government agency directors and their staffs. To obtain such support the GEOMAX project provides countless demonstrations to elected county officials, agency directors, public and private special interest groups, and city and county professional staff, thereby, developing a strong support base for the total project and consequently developing support for a quality


product. Through these efforts the funding to accomplish quality assurance was achieved and continues to be renewed annually.

At the project level, the Director of the Regional Information Center, the Director and Associate Director of the GEOPLAN Center, and the Director of Gainesville Regional Utilities, all participate on an executive committee for the project. This committee has stated its commitment to the development of a quality assurance plan and to an iterative review of the quality control processes. Furthermore, all project staff (no matter which agency they are employed with), understand the commitment to quality assurance that exists within upper management. This understanding was developed by providing all digitizing and quality control employees with a demonstration of the project’s applications and by informing them as to the necessity for a high quality conversion product.

The Quality Assurance Plan

The GEOMAX quality assurance plan closely resembles the general quality assurance plan depicted in Figure 1, including all of its major components. Management staff at the Regional Information Center in conjunction with research personnel at the GEO- PLAN Center formulated a policy plan for quality assurance, requested and received a management policy directive on quality assurance, instituted a training program for the conversion digitizing and quality control employees, installed GEOMAX staff and user quality audits, and frequently conducts quality assurance circles between management staff and employees.

While Gainesville Regional Utilities entered the project late, at least from a conversion and quality control effort, it has been involved in the quality assurance process from the start of the project. GRU also provides action as a user audit for the Phase I spatial edge matching and alignment of property map sections. The property appraiser’s office has also played a large role in the quality control effort, reviewing map discrepancies and aiding quality control employees when any questions arise.

Methods for Data integrity

The most important aspect of any computer project is the integrity of the data. Data integrity with respect to quality assurance means (1) that the data source is acceptable to the project’s users, and (2) that data stored in individual owner databases are secure from inadvertent destruction or sabotage.

With regard to data source, the property base layer was converted from the existing legal property data. The quality control effort here insured that there are no differences in the accuracy of these data caused by conversion. In fact, conversion has identified some errors in the existing property files and therefore the data are expected to be more accurate upon completion of conversion.

The protection of databases from sabotage and inadvertent destruction requires security procedures. GEOMAX protects data integrity through a number of steps including but not limited to:

1. Owner databases are protected from other interactive users by update security for the database;

2. Data are protected from development destruction by the creation of a development environment, a testing environment, and a production environment;


3.

4.

5.

6.

Data are protected against inadvertent destruction by an inexperienced applications employee through the restriction of add/delete coding (the employee cannot add or delete facilities from the database); Data are periodically (weekly) protected by automatic backup of databases to magnetic tape for off-site storage; Data are protected from power failure by a backup electrical system including batteries and an emergency electrical generator; and Data are protected from sabotage by building security systems, off-site data backup storage, and limited update access.

Quality Control Procedures

Since the project’s inception, the quality assurance plan and quality control procedures have undergone an iterative review. However, solutions to production quality problems often result in revisions to the quality control procedures (Figure 3), rather than to the quality assurance plan.

Since all programs developed at the GEOPLAN Center are production tested at the Alachua County Regional Information Center, production recommendations or changes are reported back to the GEOPLAN staff. These recommendations result in revisions to existing programs which are then invoked for a second iteration of testing; the process is then repeated until the desired level of program efficiency is attained. The

FIGURE 3. GEOMAX Quality Control Procedure.


iteration of development programming modified through production experience is precisely the process that evolved into “phased” quality control procedures within GEOMAX.

Division of the GEOMAX quality control procedures into phases simplified the assignment of tasks and responsibilities, and facilitated the tracking of property maps through the process. Phasing also provided a method for the quality control of select map units required by the utility department before its staff could begin their conversion effort. In addition, the conversion of utility data progressed more rapidly than did

conversion of the property layer. Since there are fewer data to convert on utility maps, the GEOMAX land database staff was required to provide the utility with Phase I quality controlled map areas at an accelerated rate. The utility’s accelerated demand was met because phasing allowed all quality control employees to concentrate on com- pleting Phase I quality control tasks for the utility service area.

To date, Phase I quality control is complete, and Phase II has been tested and is underway. Phase III procedures have been tested and are in an iterative process with some modifications expected before this phase is placed into a production mode.

Phase I

The first phase of quality control contains those procedures used while the property maps were being digitized and involves: (1) in-stream error checking (the automatic quality control of digitizing work while it is underway; (2) correction of operator labeling errors; (3) aggregating maps into larger areas (edge-matching and aligning of maps) to form a continuous surface database; (4) creating plot files of the maps; and (5) creating parcel key number and label files.

In-Stream Error Checking By coding the conversion programs to include error checking as the data are input,

the operator is notified of a discrepancy for immediate correction. For example, zip code boundary labels can be confirmed to lie within the valid range of zip codes for the given region, and if an invalid zip code is entered, the operator is prompted to re-enter the proper code. Additionally, if a particular error is found to occur on a frequent basis, conversion programming can be changed to include a check for that error, or program code can be modified to require that the digitizing operator select a response from a predefined list of correct selections.

Two other in-stream error checking procedures included notifying the digitizing operator if an incorrect data type (character instead of number) had been entered, and notifying the operator as to the “correctness” of the map document fit into specified coordinates (RMS error). If the RMS (Root Means Squared) errors were too large, it meant that the operator made an incorrect pointing, an error when entering the map coordinates, or that the map was improperly drafted and did not actually fit within the coordinate base. Once notified of an error, the program instructed the operator to make corrections and to again register the map. If the second registration of the map produced a high RMS error, the employee notified his or her supervisor and referred the map to the property appraiser’s officer for correction.

Another problem that occurred during the digitizing effort was the incorrect generation of parcel boundaries. This problem was critical for GEOMAX because improperly digitized parcel boundaries interfere with the ability to accomplish both accurate graphical representation of the parcel and future applications. Many of the future


applications planned for GEOMAX depend on the ability to automatically generate shaded parcels or areas, and to accomplish this task the area boundaries must be closed perimeter facilities. For example, the automatic generation of shaded areas is important for identification of property land use for land use mapping; for the identification of lots with greater or less than a specified acreage, building area, or property value; and for the identification of parcels which are located within a specified flood area, soil type, geological, or political boundary. The ability to check for closure of area boundaries was, therefore, an important part of the quality control effort. For GEOMAX, the digitizing program automatically checked each parcel boundary for closure and invoked an error message on the alphanumeric screen when closure did not occur.

Even with these simple digitizing checks, some parcel boundaries were digitized incorrectly. These errors usually resulted from one of two operations. First, a digitizer would begin a parcel and stop for a number of reasons (breaks, lunch, or simply to answer a question), and upon returning to his/her work, he or she would inadvertently forget to complete the parcel area. Second, a digitizer incorrectly entered the parcel number or label and started the parcel boundary process again, forgetting to delete the incorrectly digitized parcel. Both of these errors resulted in boundary segments added to the workspace map which could not be located by visual inspection of the workspace. To locate and remove these errors, programming was written that automatically eliminated such parcel boundary segments.

Operator Labeling Errors Another technique employed by the GEOMAX staff to locate errors in the digitizing

process was to color code similar facilities (i.e., brown for parcel side length labels, blue for street labels, etc.). This solution was implemented because some operators were inputting labels with the handiest (“current”) label, and could not tell when they had input an incorrect label. Because many labels appeared identical on monochrome screens (which were employed for digitizing early in the project) incorrect label errors were difficult to locate. The addition of color monitors to the project greatly simplified the task of locating improperly labeled facilities.

Map Section Aggregation Into Larger Areas Once the property maps were digitized, the maps with unacceptable RMS errors were

“warped” (spatially inserted) into known control points. This was done by pointing to identified map corners on the digitized property map, then pointing to the correspond- ing base coordinate points, calculating the warping parameters, and invoking programming to adjust the map to the specified coordinates.

Individual maps were then combined into large areas by retrieving adjoining workspaces and checking for edge-alignment problems. If a polygon did not align properly across map boundaries after the maps had been shifted for edge-matching, the polygon was deleted and redigitized. Next, the combined map area workspaces was saved and archived on tape in database file format.

Plot Maps The next step in Phase I was to create a plot file of the map workspace. The operator

first invoked a menu key which assigned proper color to all labels. The frame size (area to plot), plot display angle, and scale for the plotted map were then determined, and the plot file was created. The resulting plot file was created in an Industry Standard Plot- ting Command (ISPC) file, which was then plotted (in Phase II) using a microcomputer and an “E” size plotter.


Creating Parcel Key Number and Label Files The last step in Phase I involved checking the entire workspace for parcel labels, and

writing a list of these parcel labels to a flat file for verification in Phase II. Upon completion of Phase I, a copy of the workspace was sent to Gainesville Regional Utilities for the support of electric facilities conversion.

Phase II

Phase II procedures are used to (1) verify parcel labels and numbers (which are links to the property appraisal database), (2) to plot and visually inspect plotted maps, and (3) to correct errors found on plotted maps.

Verify Parcel Labels and Numbers To verify the parcel labels and numbers, the parcel label file generated in Phase I is

cross-matched with the parcel numbers from the property appraiser database, and a list of “exceptions” is generated. Exceptions occur when a digitized parcel label is not found in the property appraiser list, or when the property appraiser file contains parcel numbers not found on the digitized maps. In addition, any duplicate parcel numbers found in the digitized workspaces are noted for verification. Duplicate parcel numbering may occur but it is rare and verification of these numbers reduces the possibility of duplicate data or mismatched data transfer. Exceptions are usually caused by improper parcel identification by the operator, improper parcel labeling on the original property appraiser map, or inconsistencies in the property appraiser parcel numbering algo- rithm. All discrepancies are checked against the original maps, and labeling mistakes are noted. However, some discrepancies may be due to errors on the original maps, and these discrepancies are verified with the property appraiser prior to modification.

The computer programming that creates the exception files also calculates the accuracy of the data entry phase of the project. Two accuracy ratings are calculated. The first rating computes a percentage of digitized parcels that match data records in the existing property database. This percentage indicates the effectiveness of the digitizing process. For example, a map section contains 2,000 digitized parcels. When the map is checked against the property data file 1,978 digitized parcels match records in the property database. The remaining 22 exception parcel numbers are written to a data file for manual verification, and the effectiveness ratio of digitized is 99%. The second accuracy rating compares the number of parcels in the Property Appraiser’s existing files to the number of parcels digitized. Using the same example from above, however introduc- ing a new fact, the property appraisal file has 2,055 parcel records-55 more than indicated on the parcel map. For those 2,055 parcel numbers only 1,978 parcels were actually matched, leaving 77 unidentified parcel data records. These exception parcel numbers are also written to a file for verification, and the effectiveness ratio for the second test is 96%. Preliminary results from Phase II checking indicates that the digitizing effort is 98% effective; and that exceptions found for the second effectiveness ratio are the result of parcel splits creating new parcel numbers and additional data records within the existing property data files after the beginning of project conversion.

Plot and Visually Inspect Property Maps The next step in Phase II is to download the binary plot file from the mainframe to

the microcomputer, using PC3270 file transfer hardware and software. The file is then plotted using a microcomputer program developed at GEOPLAN. The program allows the user to plot the file at any scale; however, for quality control purposes the maps are


plotted at the same scale as the original property appraiser maps. The plotted map is then superimposed over the original map, on a light table, and visually inspected for errors. All errors found by visual inspection are corrected.

Correct Errors Found on Plotted Maps Once the property maps have been plotted and visually inspected to locate any map

discrepancies, then the map workspace will be reloaded to correct any graphical or parcel number errors. In cases of label errors the appropriate label will be employed to replace the improperly digitized label.

To locate parcels that have improper parcel numbers the parcel label files will be employed to identify which parcel label has an inappropriate parcel number attached. The information to accomplish this task is provided from the parcel exception files created in the first step of Phase II.

Phase 111

Phase III is used to modify exported database files for conformance to a specific data structure, to merge property appraiser data into the file, and to send the modified export file to the database. Normally, database revision is not required. However, the GEOMAX project determined that a new data structure would provide easier interactive access for all data users, and that Phase III was the most opportune time to modify the database.

The workspace structure needed to be altered to accommodate users of the system that did not require the same detailed information about a parcel of land as does the Property Appraiser. This required a modification to the attribute data structure for the parcel facility. The new parcel facility contains two data structures instead of one- the first structure is for general use, and a second substructure contains detailed information for the property office. All users have the ability to retrieve these detailed data from the database; however, some users have determined that they would have little use for these data. This task was accomplished by reading the old graphic and attribute flat file with a FORTRAN program and generating two new attribute data facilities to replace the existing attribute data. A new export file was created with this format change, and sent to a reformatted database.

RESULTS AND CONCLUSIONS

The desired result from any GIS is a high-quality product. That quality is most often reflected in database reliability, the quality of the applications available, and the recep- tion of the database by the users of the system. Originally, the Property Appraiser wanted his office’s maps replicated. This requirement resulted from the Property Ap- praiser’s confidence in his department’s original maps. The digitizing and quality control process for GEOMAX has produced a property parcel database layer that at worst duplicates the Property Appraiser’s previous maps and data.

Digitizing for property base layer has been completed and Phase II of the quality control procedures are underway. Preliminary testing indicates that the database provides all users with the ability to address property data as needed and protects that data from destruction by nondesignated persons. The quality control effort indicates that the digitizing effort was at least 98% accurate with respect to attribute data, the maps are of high quality, easily reproduced, more rapidly maintained, and computer transferable.

Other geographic information projects that have not yet begun conversion should:


1. Develop a quality assurance plan; 2. Recognize that quality assurance is an iterative process and that change will and

should occur in a properly developed quality control process; 3. Get all employees involved in quality control by instituting quality circles; 4. Maximize in-stream quality control checking, so that errors may be detected and

corrected early; 5. Make extensive use of color coding of labels and facilities, thereby allowing for a

more rapid visual inspection of maps or workspace environments on color graph-

ic devices; 6. Verify key linkage attribute fields for any exceptions between existing data storage

and conversion data storage; 7. Test the entire conversion process from beginning to end, to detect weak links in

the process; and 8. Get users involved in quality assurance early in the project.

QUALITY CONTROL is an evolving process. When developing in-stream quality control checks, the program designer may only anticipate the mistakes which will most likely occur, and develop programming accordingly. However, there will probably be errors generated that were not, and could not be anticipated. As mistakes are made, new procedures must be developed to correct those mistakes and to prevent the same errors from reoccurring. However, new procedures might lead to the generation of additional

unforeseen problems. Therefore, the process must evolve into a system which can detect the majority of errors, while utilizing a minimum amount of resources.

Above all else, involve users in the quality assurance plan and in the quality control process-they are the reason for the project.

REFERENCES

Chapin, F. S., Jr., & Kaiser, E. J. (1979). Urban /and useplanning. Urbana: University of Illinois Press. Dueker, K. J. (1987). Geographic information systems and computer aided-mapping. Journal of the Ameri-

can Planning Association, 53, 383-391. Hunter, W. G., O’Neill, J. K., & Wallen, C. (1987). Doing more with less in the public sector: A quality and

productivity progress report from state and local government groups in Madison, Wisconsin. Quality Progress, 19-26.

Ingle, S. (1985). In search of perfection: How to create/maintain/improve quality. Englewood: Prentice-Hall Inc.

International Business Machines (IBM) Corporation. (1987). Geographic facilities information system over- view. Houston: GFIS Application Center.

Juran, J. M. (1988). Jurun on planning for quality. New York: Collier Macmillan Publishers. Stebbing, L. (1986). Quality Assurance: The route to efficiency and competitiveness. New York: John Wiley

& Sons.

quality assurance for a local government geographic information system: a geo-facilities project...

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