Exploring big data for local government: notes from West Nusa Tenggara, Indonesia
The Province of West Nusa Tenggara (NTB) comprises the western portion of the Lesser Sunda Islands in Indonesia. I have just returned from a several days mission there to explore big data with colleagues from the Office of the State Minister of National Development Planning (Bappenas), the Department of Foreign Affairs and Trade of Australia (DFAT) and the World Bank – pictured here with colleagues from NTB government’s information center.
Our objective? To talk data innovation with local government authorities and non-governmental organizations: to learn about existing systems, identify where the ‘wicked’ issues are, and discuss new sources of data and analytic methods that might have an impact on the ground.
Our findings? Top 5:
1. Enthusiasm for data innovation and recognition of a need for change
The need for more timely, cheap, and understandable information for decision-making was recognized across the board – as was masses of enthusiasm for any way that we might be able to get there.
2. Existing initiatives to build on
Local governments innovative activities to collect digital data – for example an SMS center to receive and respond to citizen’s complaints and electronic fingerprinting to improve government representative attendance rates.
CSO networks using technology to improve communication with the community and NGOs for decades – everything from using wired radios to connect villages in 1979, to techies doing data analytics and building websites today.
3. Lots of ‘unused’ data
Data is not a lot of use if it just sits there – but processing data using traditional methods is time intensive. Could new analytic, visualization and mapping methods help us move from data to usable information more quickly?
4. Diverse sources
With SMS complaints and information requests, photos, written reports, radio broadcasts, routine data collection systems, data collected in surveys, news sources, and the use of social media – the sources available are already pretty diverse. And there are the potentials - anonymized mobile phone call records? Infrastructure sensors? Financial transactions? Imagery from satellites?.....
5. Data stuck in silos
The data ecosystem is fragmented. Information is often held in ‘silos’ – isolated units of information – in different formats and different systems that differ both by organization and the units within them.
These silos of information don’t just exist on one horizontal ‘layer’ e.g. different units within the local government. They also exist vertically. For example, information from citizens may be held in silos in Civil Society Organizations, but not fed into silos in the local government – and then not linked to silos in the national government.
Do big data analytic methods have a role in rapidly pulling together and gaining insights from fragmented data so that the ‘big picture’ is more apparent? and in presenting it in a cohesive way for decision-makers?