Random notes during the session:
Setting up regional initiatives
Stop talking about open data and begin talking about issues.
Open data should not be an end in itself.
How do we cope with encouraging regional initiatives while keeping the interest in the local impact. How do we keep the regional nodes locally grounded.
- Having other stakeholders in the projects so that they can make it socially sustainable, like data journalists.
- Connect researchers and practitioners.
- Establish fellowship programmes.
- Repository of best practices.
- We have to do the open data revolution from below. We have to start infiltrating the system.
Instead of putting out solutions, put the spotlight on problems, create conditions/spaces where problems can be shared: crowdsourcing, crowdfunding, hackathong, etc. so that people that have the solutions can joint the people that have the problems. Putting out the solutions will not necessarily attract people with the problems.
- Be more able to connect people: citizens, sectors, governments, etc.
- Pre-events have been very successful.
- Have to make connections more continuously, with consistent engagement.
More sectorial work. Infiltrate sectors. Adaptive approach.
Better research. Map out good practices.
Re-use of apps.
What format is useful, what content.
How to go beyond the programme.
- Not lobbying, but helping governments to manage change.
- Focus on use, focus on the demand side. How do we stimulate the demand?
- Sector focused initiatives.
- How to embed our thinking as a tool to achieve governments’ goals.
The technicalities of open data is not the most important thing.
Help communities how to have good ideas and how to use open data to achieve them.
Having a champion is very important.
The best way to foster the supply side is to support the demand side.
We have to stop talking about ‘open data’ and focus instead on vertical communities: e.g. open data and agriculture, open data and transportation, etc.
In some countries is not anymore a matter of evangelization: governments are convinced. Thus, it is again a matter of technology, of providing (technical) solutions.
We have to institutionalize open data initiatives, make them mainstream at the highest government levels.
How to institutionalize it, though? Help governments to actually implement things.
- Political will and capacities.
- Continuity, stability.
- Think about demand and how to contribute to it: developers, data scientists, etc.
Still working in silos. Support open culture across governments.
Use and reuse of data
If government discloses only what’s convenient, this leads nowhere.
Demand mapping: open data availability is different from usefulness.
Citizens don’t necessarily use data –> build capacity of intermediaries.
Offline engagement is critical.
Open data for transparency, how to?
Fellow selection is critical.
Reuse will benefit from problem-solving.
Data collection is a crucial skill. Data literacy.
Measurement and impact
How governments are investing, what actions they are taking.
None of these indices are talking to each other. How to define measuring.
Data does not produce impact: people produce impact.
What is the immediate outcome and what is the long-term effect of open data.
Different levels of impact: economic impact, social impact, etc.
One of the first places to look for impact is in the flow of feedback and what the demand side is saying about open data.
4th International Data Conference (2016)
If you need to cite this article in a formal way (i.e. for bibliographical purposes) I dare suggest:
Peña-López, I. (2016) “OD4D Summit (I)” In ICTlogy,
#157, October 2016. Barcelona: ICTlogy.
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