PRTR operation - Data quality assurance
Data quality is an essential component of a PRTR; high quality data reduces uncertainty in results from analyses of the data and, therewith, optimizes the integrity of conclusions drawn from such results. Maintaining high quality data is important for meeting national goals for the PRTR; for example, high quality PRTR data can be used to perform sound evaluations of the progress of national environmental policies.
Data quality assurance involves reviewing reported and processed PRTR data to identify and resolve inaccurate, incomplete, or missing data and includes the following key components:
- Review Reported Data to identify potential data quality issues (e.g., outliers, records with large changes between years, records with internal inconsistencies, etc.).
- Contact reporters with Potential Data Issues to verify reported data.
- Establish Error Correction Procedures to allow facilities to revise reported data to fix data quality issues.
- Embed Data Quality Checks in Reporting Software: Developing reporting software to check data and notify the user of potential data quality issues so that data quality issues may be resolved before they are submitted to the PRTR.
- Develop Stand-Alone Software to Automate Data Validation: Developing software to use algorithms that identify potential data quality issues based on patterns in reported data.
For a cost-effective management scheme, you may wish to implement the next sub-element (Review Reported Data) or choose another element from the Management scheme elements list.
Relevant tools
- OECD: Pollutant Release and Transfer Registers (PRTRs): A Tool for Environmental Policy and Sustainable Development - Guidance Manual for Governments (1996)
- OECD: Considerations for Ensuring Quality PRTR Data (2008)
- OECD: Guidance on Elements of a PRTR: Part 2 (Not Yet Available)
- UNITAR and IOMC: Designing the Key Features of a National PRTR System, UNITAR Guidance Series for Implementing a National PRTR Design Project, Supplement 2 (1997)