/ PS M&R – Data ‘Fix’ Support Template

This template is for use by public bodies to propose solutions to clearly-defined M&R data quality problem (e.g. one that has been raised in a data verification assessment (DVA) report):

  • Note that if your problem was identified through the DVA process, your DVA report should include some recommendation(s) on how you can tackle it.
  • If you have more than one data quality problem, we recommend that you use separate templates for each.
  • Please do not include information that is not directly relevant to the defined data quality problem as this will not be considered.
  • Sections 1-3 are mandatory. If a box is too small, please expand it.
  • If you have previously prepared documentation that explainsor supports your proposed approach (e.g. notes, spreadsheets, etc.) please list them in section 4 and include them with your submission.
  • Your proposal should be submitted to no later than 2 February 2018.

SEAI will review your proposal for a solution. You can expect to receive feedback by 2 March 2018, but we may be in touch sooner, especially if further clarification is required.

PB ID No.: / Contact Name:
Organisation Name: / Date:
  1. What is the scope of your data problem?
Clearlydefine the scope of your data quality problem e.g. diesel consumption reported for 2009, 2016 electricity consumption, activity metric value reported for baseline.
  1. Define your data quality problem
Clearly explain your quality problem. Include reference to any DVA findings related to your data problem.
  1. Explain your proposed approach to rectify the data quality problem
Provide a robust explanation for your approach. While you must provide sufficient detail to demonstrate that your approach will be sufficient to meet SEAI’s data quality requirements, you don’t have to fill the box if you don’t need to – be as concise as possible.
If your approach includes calculations, list the main inputs used (including units) & explain their source:
If your approach includes calculations, list the main assumptions and the basis for them:
If your approach includes calculations, give details of any conversion factors used (if relevant):
If your approach includes calculations, please comment on the overall accuracy of the results - are you aware of any discrepancies between the results and actual values, e.g. data gaps? If yes, please estimate the scale.
  1. If you have any documentation that explains or supports your proposed approach (e.g. notes, spreadsheets, etc.) please list them here & include them with your submission.
Please provide explicit references to relevant sections, page nos. etc.

Public bodies are responsible for reporting complete and robust data.

1 of 3
Ref: 469-X0113
FBS: 469.01.16.04