Quality Data, How do I recognize it?
Donald E. Ramsay
Logica, 10375 Richmond Ave., Suite 1000
Houston, TX 77042
Email: ramsayd@logica.com
Abstract
The key to any GIS functioning as expected is quality data. The old adage of “garbage in –
garbage out” still holds true. With the amount of existing digital data available today, combined
with the new and traditional means of developing digital data from paper sources, it is critical
that a common means of identifying and describing quality data be introduced. Many GIS
Project Managers and users know they need quality data but they are unsure of exactly what
quality data is and more importantly how to define it in a set of project specifications. This
paper will first describe what quality GIS data should be and then provide the reader with the
tools to write a data quality specification. The reader will also gain the knowledge enabling
them to establish a quality control procedure that will ensure that quality data is accepted and
introduced into the GIS on a consistent basis.
Overview
When developing a set of data quality specifications associated with accepting data and
eventually loading that data into an enterprise GIS, it has in the past been a gray area as to
exactly what was meant by quality data. Many GIS Managers simply went with a generic
quality value of anywhere from 96% to 99.5%. This level of accuracy may sound good on a
conversion specification and everyone within the organization may feel that they will be getting
quality data. This paper will describe how even with a quality data standard of 99.5% the data
may not be acceptable to run certain applications or even be able to be loaded into the system at
all.
With the amount of existing digital data available on the market today it is critical that GIS
Managers are aware of how to identify and qualify GIS data to protect the existing database from
corrupt data files. Now that GIS data is firmly entrenched and utilized throughout the enterprise
it is even more critical to protect the data integrity. In years past it may have been only the
mapping and or engineering departments that were impacted by GIS data but now almost every
department within a utility has access to and makes critical decisions based upon GIS data.
When taking into account the number of mergers and acquisitions that occur within the utility
industry today is becomes even more of an issue to have a means of evaluating the quality of GIS
data when two or more existing GIS systems are merged into one. This factor becomes even
more critical when you consider that the two systems that are about to be combined because of a
company merger or acquisition may not even be the same systems.
