Data quality control in a GIS project
Maria Navarro
Intergraph Utilities & Communications
Mailstop: LR23B2
241 Disk Drive
Madison, Alabama 35758
Abstract
This presentation emphasizes the quality of data, which is one of the most important
elements in an organization. When companies purchase sophisticated technology
solutions that provide analyses for better decision-making processes, the acquisition of
data (spatial and alphanumeric) can become the point of project success or failure, due to
false expectations or not having clear rules established for acquiring data that meet the
company’s goals. This paper offers some recommendations for establishing data qualitycontrol
standards to achieve the company’s goals.
Complex and sophisticated tools can help in acquiring high quality data, but company
rules and practices also need to be established to determine if the data will meet its
requirements.
A search of the sources and types of data will identify the different types of error, which
will help to define the standards.
It is important to define and tune workflows that ensure the quality of the data, and test if
these standards will meet the project’s requirements; the experience and knowledge of the
people involved in the project is very valuable in order to get quality data and help the
project succeed.
A system not only needs to provide good data, but to integrate it and produce useful
information at different levels in the organization.
