How do you prove GIS quality assurance and validation improves decision making?

1 What is GIS quality assurance and validation?

GIS quality assurance and validation are the processes of checking and verifying the quality of GIS data, methods, and outputs. Quality assurance involves defining quality standards, criteria, and procedures for data collection, processing, and analysis. Validation involves testing and evaluating the data, methods, and outputs against the quality standards, criteria, and procedures. The main goals of GIS quality assurance and validation are to identify and correct errors, inconsistencies, and uncertainties in the GIS data, methods, and outputs, and to ensure that they meet the needs and expectations of the users and stakeholders.

2 Why is GIS quality assurance and validation important?

GIS quality assurance and validation are important for several reasons. First, they can improve the accuracy, reliability, and credibility of the GIS data, methods, and outputs, which are essential for making informed and evidence-based decisions. Second, they can reduce the risks of errors, biases, and misinterpretations that can lead to wrong or ineffective decisions, or even legal or ethical issues. Third, they can increase the confidence and trust of the users and stakeholders in the GIS data, methods, and outputs, which can facilitate communication, collaboration, and coordination. Fourth, they can enhance the efficiency and productivity of the GIS workflow, by avoiding unnecessary or redundant data collection, processing, or analysis.

3 How to prove GIS quality assurance and validation?

GIS quality assurance and validation can be proven in various ways, depending on the type and purpose of the GIS data, methods, and outputs. Documenting the sources, methods, and outputs is a common practice, as well as performing quality checks and tests. Additionally, comparing and validating the data with other sources of information is important. Afterward, the results of the quality assurance and validation processes should be reported and presented using appropriate formats, such as tables, charts, maps, reports, or dashboards. Lastly, it’s essential to communicate and discuss the results with users and stakeholders using clear language.

4 How does GIS quality assurance and validation improve decision making?

GIS quality assurance and validation can improve decision making in various domains, such as environmental management, urban planning, public health, disaster response, or business intelligence. It can provide more accurate and reliable information for decision making by reducing errors and inconsistencies in the GIS data, methods, and outputs. Furthermore, it can support more effective and efficient decision making by providing relevant and timely information that meets the needs of users and stakeholders. Additionally, GIS quality assurance and validation can enable more robust and flexible decision making by providing information that can handle different scenarios, alternatives, or uncertainties. Lastly, it can foster more collaborative and participatory decision making by increasing the confidence of users and stakeholders in the GIS data, methods, and outputs while also facilitating communication, collaboration, and coordination.

5 What are some best practices for GIS quality assurance and validation?

To ensure that your GIS quality assurance and validation processes are successful and beneficial, it is important to plan and design them before starting your GIS project, aligning them with the project objectives, scope, and resources. Quality standards, criteria, and procedures should be defined and documented for all data, methods, and outputs. Reliable tools and techniques should be used for quality checks and tests throughout the GIS workflow from data collection to output delivery. Furthermore, data, methods, and outputs should be compared and validated with other sources of information as well as feedback from experts or peers. Quality assurance and validation results should be reported in a clear and transparent way to users and stakeholders. Finally, the process should be monitored and evaluated with adjustments or improvements as needed.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?