Urban Data Analytics for Indonesia Development

Presented at Indonesia Mengajar Development Class

Transcript

1. Urban Data Analytics for Indonesia Development Jakarta, September 17th 2016
2. Hi[0] Ramda Yanurzha medium/@ramda twitter/@ryanurzha github/ramdaffe +628118600960
3. Hi[1] NYU Center of Urban Science & Progress ‘15 Urban Data Science & Informatics RTI International Data Scientist
4. Why cities?
5. 511 Kabupaten & Kota 78 with pop. > 100.000 26 of them > 500.000 >50% of Indonesia pop.
7. Jargons • Big Data • Open Data • Smart City • Data Science • ….
8. Technology used by government and citizen helps create a better, more livable city but in what way?
9. Them:
10. Us:
11. Urban Data Analytics is the pursuit to understand how city works by applying analytical process on data generated, collected, and published by the city itself.
12. City planning City operation City analytics • Resource optimization • Business process improvement • Policy analysis • Long-term evaluation • Pilot projects
14. Our Mindset • We hunt for problems ◦ Driven by intellectual curiosity • The more data, the merrier ◦ As granular as possible ◦ Usually not “big data” big, but we’re okay with that • Respect regulation and pursue collaboration ◦ We do love some civic hacking!
15. We tend to know where to start to look for data (or whether it actually existed at all)
16. We usually are not the domain expert, but we possess the ability to use (and make) complex tools to help them
17. We do it just for fun... ….you want to optimize for a wait time that’s less than 30 min in 90% of the cases. Then the max time you should wait is about 11 minutes until giving up.
18. As a result, the department sent a training message to all officers clarifying the rule change …thanks to this analysis and the availability of this open data, the department is also taking steps to digitally monitor these types of summonses” ….or drive changes.
19. But we can be wrongly driven by interest...
20. ...and being open can be embarrassing
21. Why should we expose our faults and cede control of what we want to tell to the public, just for a slim chance that someone will do good?
22. Why not increase that slim chance?
23. How NYC did it.
24. NYC is a data factory because it generates data through regulation.
25. In all, a terabyte of raw information — enough to fill nearly 143 million printed pages — passes daily through Mayor Office of Data Analytics
26. Case Study As once-struggling neighborhoods prospers, landlords have financial incentives to push out lower-paying tenants… ...landlord threats, frivolous lawsuits and withholding repairs such as not fixing an elevator in a building for seniors.
27. NY State Attorney General NYC Department of Housing Preservation NYC Department of Buildings NYC Department of Health NYC Mayor Office of Data Analytics Citizen Online Report E-mail & Phone Call Building Inspection Nonprofits Identify apartment tenant experiencing harassment by the landlord Pattern & Likelihood
28. Indonesia?
29. At least we start to use analytics result to inform policy outcome.
30. “Somewhat ironically, more fine-grained official statistics would be necessary... ….since our food inflation ‘ground truth’ data was aggregated monthly it is necessary to throw away much of the detail in Twitter content ”
31. Indonesia US Price Rp. 1-10/KB (agg) Rp. 5-100/KB (microdata) Free Process Time 3-7 days Instant Detail As-is w/ Margin of error Granularity Kabupaten/kota (>20.000) Census tract (1.200-4.000) A Difficult Start Can I get data on median income?
38. Zoning Affordable Housing Social Mobility Homelessness Mental Health Social Assistance Public Transit Safety Gang Crime Lingering hard questions.
39. Thank You. Q & A