Measuring the Barriers to Big Data for Development: Design-Reality Gap Analysis in Colombia’s Public Sector
Liliana Fernández Gómez and Richard Heeks
While big data has the potential to make a significant contribution to international development, that potential is currently constrained by a number of barriers. Systematic analysis of those barriers is rare, so this paper applies the design-reality gap model to identify and evaluate barriers to effective use of big data in one context: the Colombian public sector. The model provides a structured framework that exposes a broad set of barriers, and also helps highlight priority areas for action to accelerate the application of big data. The design-reality gap model can also be seen to provide the basis for related analyses such as readiness for big data, and risk identification for big data initiatives in developing countries.
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- What have been the shortcomings of many analyses of barriers to big data for development? [Section A]
- How is the design-reality gap model applied in this case? [Section B]
- Which are the most significant barriers to big data in Colombia’s public sector? [Section C]
- What should Colombia do to reduce the barriers to effective use of big data in the public sector? [Section D]
- Does big-data-for-development justify the excitement is has generated?
- If attention and resources are put into big data, what other issues should be given less attention and resources?
- What might be the priority application areas for big data in Colombia’s public sector?
- What other frameworks might be used to assess readiness for, or barriers to, big-data-for-development?
- If you were planning to use the design-reality gap model to assess barriers to big data, how would you apply it?