Quality assurance (QA) is like putting railings on stairs: the goal is to prevent problems before they happen. QA is the proactive process intended to minimize the chance of an error being inserted into your data. Practicing QA throughout the monitoring process (Figure 1) can help ensure that the data you are collecting is high quality, follows AIM guidelines, and can be stored in national databases (TerrADat and AquADat).
QA measures include strategies like using electronic data capture tools (e.g., DIMA or SARAH) which warn users of invalid data values as they’re entered, calibrating field crews on the methods used, and confirming the completion of all collection methods and forms before leaving a survey plot.
- It is the primary responsibility of the Crew Lead to fully QA/QC the project database. The Project Lead should provide oversight of this process, and should review the database again once the Crew Lead has gone through it. This process will be more intense at the beginning of the season while the crew is stilllearning.
- It is the responsibility of the Project Lead to field data requests from other specialists, and work with the Crew Lead to fulfill those requests where appropriate. However, it is the responsibility of other specialists to become familiar with the DIMA interface and retrieve data for their own projects/documents.
QA advice from other project leads:
- Pay attention to GPS coordinates during the QA and QC process. I found many of the sample points were not at the randomly generated target. This error appears to have been the result of the crew using a graphical interface to navigate to points, rather than waypoints.
- Check for errors in data collection at the completion of each line and plot.
- Maintain a spreadsheet of unknown plants in the field and update in electronic form on a regular basis.