🎯 Data is power — but only when it’s clear, accurate, and meaningful.

I had the opportunity to present on Data Quality and Accuracy for Rural Contexts during our first workshop with the 16 selected RURACTIVE innovators. It was an engaging session focused on helping teams design better monitoring frameworks to track real-world impact in rural innovation projects.

🔍 In rural contexts, data collection can be messy — missing logs, inconsistent formats, sensor issues, and a tendency to collect too much without clear purpose. My presentation focused on:

• Why data quality matters: Small errors can lead to big decisions.
• Key dimensions of quality: Accuracy, completeness, and timeliness.
• Common pitfalls in rural projects: Disconnected systems, incomplete metadata, and over-collection.
• Best practices: Selecting indicators, using templates, and storing data securely.
• The critical role of metadata: Making your data understandable and reusable.

💡 The main takeaway?

You don’t need more data — you need better data.
And better starts with clarity, relevance, and documentation.

Thanks to all the innovators for your thoughtful questions and to the RURACTIVE team for supporting this important discussion!

Tags:
#RURACTIVE #DataQuality #RuralInnovation #Monitoring #ImpactEvaluation #SmartCommunities #OpenData #MetadataMatters