Data Philanthropy: Four Common Steps to Collaboration
Mellyana Frederika for Data Innovation for Policy Makers Conference 2014
Living in Jakarta can mean spending hours at a time on the road. Traffic congestion is such that it is considered normal to commute two to three hours a day from home to work. In this situation, real-time data about traffic flow is welcome information. Waze, a community-based traffic and navigation application using global positioning system (GPS) support is becoming increasingly popular in helping commuters get real-time data about traffic jams. It was good news for Jakarta residents on Tuesday 11 November 2014, when Muhammad Akbar, the head of the Transportation Agency, announced a new collaboration between the Jakarta Provincial Government and Waze.
Will we see more of these partnerships?
Here are four steps that could help, as discussed by data innovation practitioners at the international conference on Data Innovation for Policy Makers, held in Bali on 26-27 November 2014:
1. Identify a need and find the data to help with the answer.
In South Korea, eight out of 10 people use smartphones. They use social media to vent their frustration about traffic conditions. Here is one tweet that was shown at the conference: ‘Buses don’t run at the time I get off work. I don’t have a car. I hope there will be buses available late at night.’
Every tweet counts for the Seoul Metropolitan Government. They listened to the conversations captured through social media and began to consider how best to provide a late night bus service. The analysis of social media, as well as 3bl mobile phone call records, showed where people wanted to go late at night and helped to plan nine late night bus services.
2. Who has the data?
More and more, data is becoming a valuable resource. In an example from Indonesia, data from major timber companies located in Sumatera and Kalimantan helped Global Forest Watch monitor conservation concession areas. This helped Global Forest Watch provide information to government agencies about changes over time. Another example presented at the conference showed that data are part of everyday communication through social media. Tweet flows analyzed using the hash tag ‘banjir’ (flood in Bahasa Indonesia) provide Jakarta residents and emergency intervention agencies on-time information about floods. This information complements existing government alert systems.
The conclusion is that data are stored in more than just one location or digital space. What matters is which data source can provide added value to existing data systems, and the type of analysis that will be undertaken to get the right answers.
3. Start small and learn.
Data can help find an answer to problems. To do so, experimentation is extremely valuable. We need to start small, learn and grow in terms of discovering the opportunities data and data analysis provide. This approach requires identifying small-scale experiments in small and safe-to-fail policy areas. As highlighted at the conference, it is important to start and proceed, and not be afraid of experimentation. Results from small trials, whether successful or not, will pave the way to more tangible interventions and development.
4. Develop data collaboration strategies.
There is no fixed formula when it comes to collaboration for data innovation. For example, a presenter at the conference mentioned it can take six months to reach an agreement with a telecommunications operator. Moreover, there are concerns about privacy and security issues linked to the access and use of digital data. The public sector can play an important role in facilitating collaborative initiatives and consortia. A partnership agreement between the public and private sectors can save money and secure the best technology from private enterprises. On the other hand, a partnership such as this gives the private sector access to government data. A strategy is needed to turn these benefits into reality.