How do you ensure the quality and reliability of geospatial data collected by volunteers using QGIS?

1 Define your goals and requirements

Before you launch your geospatial data collection project, you need to have a clear idea of what you want to achieve and what kind of data you need. What are the objectives and questions of your project? What spatial and temporal resolution, accuracy, and completeness do you require? How will you use and share the data? Having a well-defined scope and criteria will help you design your data collection methods, tools, and protocols, as well as communicate them to your volunteers.

2 Train and support your volunteers

Your volunteers are the key to your data quality and reliability. Therefore, you need to provide them with adequate training and support to ensure they understand and follow your data collection guidelines. You can use QGIS to create user-friendly forms, maps, and instructions for your volunteers, as well as to check and validate their data submissions. You can also use QGIS to communicate with your volunteers, provide feedback, and acknowledge their contributions. Training and support can improve your volunteers' skills, motivation, and trust.

3 Choose and customize your data collection tools

QGIS offers a range of tools and plugins that can help you collect geospatial data from your volunteers. For example, you can use QField, a mobile app that allows you to collect data offline and sync it with QGIS, or Input, another mobile app that integrates with Mergin, a cloud service that enables collaborative data editing. You can also use QGIS to create web maps and surveys that your volunteers can access online. Depending on your project needs, you can choose and customize the data collection tools that best suit your volunteers and your data quality standards.

4 Implement quality control and assurance procedures

Even with the best training and tools, errors and inconsistencies may occur in your volunteer-generated geospatial data. Therefore, you need to implement quality control and assurance procedures to detect and correct them. You can use QGIS to perform various quality checks on your data, such as spatial accuracy, attribute validity, completeness, and consistency. You can also use QGIS to compare and integrate your data with other sources, such as authoritative or peer-reviewed data sets. Quality control and assurance procedures can help you improve and maintain your data quality and reliability.

5 Document and share your data and methods

Finally, you need to document and share your data and methods with your volunteers and other stakeholders. Documentation is essential to ensure the transparency, reproducibility, and usability of your data. You can use QGIS to create metadata, reports, and visualizations that describe your data collection project, methods, results, and limitations. You can also use QGIS to export and share your data in various formats and platforms, such as GeoPackage, CSV, or OpenStreetMap. Documentation and sharing can enhance the credibility, accessibility, and impact of your data.