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Data processing

A data flow model is needed to outline data management procedures for systematic processing of PRTR data in each step of the PRTR reporting cycle. These steps include receiving reported data from point sources; generating data for non-point sources (if covered by a PRTR); compiling and storing data for point sources and non-point sources; revising data to resolve data quality issues; and disseminating data.

Factors to consider when devising a data flow model include:

  • Data Quality. Data quality controls should be implemented at all stages: data development, collection, compilation, processing, storage, revision, and dissemination.
  • Transfer of data among governing agencies. In PRTRs where data is collected by local authorities and then transferred to a national authority, it is important to consider how to coordinate data processing and transfer between the authorities. For example, use of compatible computer systems can ease transfer of data from local authorities to national authorities.
  • Security. Data management procedures may be developed to identify and protect data claimed as confidential by reporters. Note that additional considerations for designing a PRTR to protect trade secrets and other sensitive information are discussed in Section 2.4.2 of Guidance on Elements of a PRTR: Part I.
  • Automation. Automating data processing steps can improve efficiency of data management procedures and data quality.

For a cost-effective management scheme, you may wish to implement the next sub-element (Infrastructure and Database) or choose another element from the Management scheme elements list.


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