Modèle de maturité sur l'éthique des données


je vous partage ce modèle d’auto-évaluation sur l’éthique des données repéré dans la liste Responsible Data. C’est très intéressant mais plus orienté sur les données personnelles.


Hello RD Forum Friends!

I hope everyone is well. I’ve been working over the past couple of months on developing a “Responsible Data Maturity Model” (RDMM) for CARE, together with Kelly Church. The RDMM would eventually be shared under a creative commons license so that others could adapt and use it in their own work. At this point is it still very much a draft for community comment and we’d love your feedback.

The main audience for this MM would be a more experienced RD practitioner who is responsible at the strategic/big picture level and would need to adapt or use the model in ways that are appropriate for others who do not have RD as their main, day-to-day responsibility. But the MM could be adapted and used in various ways with other teams.

We are imagining that the model could be used in many different ways:

• As a diagnostic or baseline and then a planning tool for organizations to see where they are now, and where they would like to be in 3 or 5 years and where they need to put more support/resources. E.g., Where are you now? Where do you want to be? What do you need to get there? (People can also pick and choose the areas that they find applicable to their organization and its work and then iterate/adapt the framework for their own use and context)
• Linked to the above, it could be an audit framework for RD (if that is of interest)
• It could be a retro-active, after-action assessment tool or case study tool for looking at a particular program and seeing which of these elements were in place and contributed to good data practices and developing out a case study to highlight good practices and gaps
• It could be used as a tool for evaluation if looking at a baseline/end-line for organizational approaches to responsible data.
• It could be simplified and used in workshops as a participatory self-assessment tool to 1) help people see that moving towards a more responsible data approach is incremental and 2) identify what a possible ideal state might look like and/or adapt the tool to what each organization would see as their ideal state
• As a way of helping management understand and budget for what might need to be considered if an organization is moving towards a more Responsible Data Approach
• With an adapted context or “persona” approach - what might RD maturity look like for a particular project or program? For HQ versus for a country office? For the board versus for frontline implementers? Or what might be the aspects that a particular role within an organization would be concerned with in the wider move to Responsible Data?
• It could be shared with donors or HQ as an investment roadmap; as an iterative pathway to action

Some elements from the RDMM were floated at the OCHA Data Responsibility meeting in May and we got some initial feedback from Stuart, Jos and Caitlyn from OCHA’s Centre for Humanitarian Data on how it was received. Mainly: 1) people liked the idea, 2) it helped people see that RD could be invested in and implemented incrementally; by laying out the steps and levels, it felt less overwhelming and clearer how RD could be addressed in stages over time, 3) the idea of a MM felt concrete to people and helped bring RD to a practical and manageable level, it gave them guardrails 4) the entire model is too complex for everyone; it’s more appropriate for people with more RD experience, 5) it was nice to think of the early stages as more individual and institutional, and as maturity grows, it become more collective and sector-wide 6) the rows in the MM are actually interrelated and interdependent, so some discussion prompts on that would be helpful.

Before we go any wider with it, we hope to get feedback and input from the forum. Once we have additional feedback, we’ll incorporate it, create an introduction page, ideas on how to use it, include a glossary, and then share it more widely under a creative commons license.

If anyone on the list has a chance to give any feedback on the following aspects, we’d be very grateful:

  1. Audience, purpose and use — any additional ideas on how it could be used?
  2. Design — how can we make it friendlier?
  3. Language — it too complex? too jargoney?
  4. Content — anything missing? too much content? too specific? too focused on traditional data collection?
  5. Levels — do the levels and descriptions make sense, both individually and as a whole?
  6. Any other thoughts or comments also welcome
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