Quality Assurance/Quality Control (QA/QC)

QA/QC and Data Quality Standards

Standards (and standardization) ensure that the organization can build a reliable and accurate database that meets the needs of the users. Standards may vary greatly depending on the organizations intended use of the data, internal policies and mandates, and contractual requirements. However, data quality is typically measured against the specified standards.

Data quality standards are based on one or a combination of the following:

Independent standards: These standards may be designed by the organization for internal purposes or for a specific project. Ad hoc standards may limit the organization's ability to share the data or use the information with other projects.

National standards: These standards are developed by government agencies to promote data sharing, understanding, and collaboration between agencies and between government and the public. Examples are the National Map Accuracy Standards by the U.S. Geological Survey (USGS) and Content Standard for Digital Geospatial Metadata (CSDGM), Version 2 (FGDC-STD-001–1998), by the Federal Geographic Data Committee (FGDC).

Industry or international standards: These standards are purchased or obtained from nongovernmental organizations, such as the American National Standards Institute (ANSI) or the International Organization for Standardization (ISO).

Well-documented data quality standards facilitate communication between data producers and quality control managers.

When is a QA Program Initiated?

Ideally, a QA program is initiated at the same moment when design of the GIS database begins. For example, the GIS database schema (or structure) represents one aspect of the quality standard needed or required by the organization. The names of feature classes, tables, and other components of the database are part of the schema. The relationships between those components are another part. Examples of other schema considerations include the following:

• Feature and attribute types
• Field names
• Subtypes and domains
• Aliases
• Topologies
• Networks
• Cartographic representations

The QA program uses the database schema design as a set of rules and constraints that are used to control [Page 358]the quality of stored data. For example, valid field values in an attribute table can be limited to a specific set of values or range of values by using subtypes and domains. Often, the database management system includes tools for ensuring that schema requirements are met during data loading or editing.

In addition to database schema, the QA program can be expanded to include rules for procedures or other specific project requirements. For example, the expectations for data quality can be set by establishing best practices for data processing, including data collection, editing, database migration, spatial analysis, and map publishing.

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