Dear IATI Community-members,

We are pleased to share the Background Paper for Discussion #1 of the Data Quality Index Consultation!


Following the structure of the Background Paper we have proposed specific questions under each proposed measure that we would like to get your feedback on. Questions have been split into four specific subsections, including an overall broader section giving people an opportunity to comment and add ideas for any questions we might not have asked. 

Click on the buttons to access each of the four subsections, check out the guiding questions and share your views!

Timeliness

Data Availability

New Measures

Overall Questions


We would like to give all our users the opportunity to feedback on the proposed measures by responding directly on Connect by Thursday 30 September 2021. You don't have to respond to all questions to get involved in the Consultation and we do welcome feedback from all our stakeholders. General comments you can share via the comment box below.

Following the deadline we will be providing a summary of your comments that we can all discuss at the Virtual Community Exchange (12 & 13 October) and during a webinar in mid-October. 


In case you have any additional questions related to the Consultation, please contact us via support@iatistandard.org

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Comments (3)

Melinda Cuzner

Bringing in some comments from me and my team:

We look forward to having an Index/dashboard that is inclusive for all publishers. The quality measure look reasonable, but are they still orientated to OECD publish norms? I was hoping to learn here how other types of organizations would answer here. I would expect that the methodology would be adapted to the type of organization/role in the aid chain. As an example, it is reasonable that a local NGO reports incoming funds, but not bilateral donors. This might be found in the more detailed methodology with primary/secondary source. But still, what is the initial reaction of other types of publishers?

More specific comments:
Data quality: Using the term Data Quality Index may be misleading as it mostly is a measure of data availability. Availability does not guarantee quality. It can look great but be nonsense information.

The purpose as it is described in the paper ensures availability rather than the content holding good quality.

Trust: The measure needs to be a balance between transparency, sensitive data and data quality. Currently, the definition of trust is very narrow. As it stands redacting sensitive data would give negative points.

The word Trust points once again to the impression that the data is of good quality, not just available.

Also, the time frame needs to be considered here, is it changes withing the last year? It will be difficult for "good publishers" to get points here, and if it is time it takes to correct data it requires open feedback loops and the requests for improvements have to be reasonable, and somehow objectively measured.

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  • Melinda Cuzner

    And for those who. like me, missed to read the instructions properly, you can see more comments under each subsection by pressing the yellow buttons up top :-)

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