Urban Data Analytics: Lessons from NYC

Transcript

1. Urban Data Analytics Lessons from New York City Jakarta, August 26th 2016
2. Hi[0] Ramda Yanurzha medium/@ramda twitter/@ryanurzha github/ramdaffe +628118600960
3. Hi[1] Civic Tech & Open Data data.go.id The World Bank TNP2K The Asia Foundation Nagara.io
4. Jargon Concepts • Open Data • Big Data • Data Science • Urban Informatics • Smart City • Sustainable City
6. 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.
7. People: why are there more and more traffic jams?
8. City Planners: Duh
9. Business: problem = opportunity = $$$
10. Us: here’s what actually happens.
11. 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!
12. We tend to know where to start to look for data (or whether it actually existed at all)
13. we are not the domain expert, but we should possess the ability to use complex tools to help them
14. Daily Tools & Libs Large Data Geospatial Statistical Visualization Others MapReduce Apache Spark Apache Pig ArcGIS QGIS Shapely Geopandas Pandas Numpy R Matplotlib Plotly D3 Jupyter Networkx Tableau*
15. City planning City operation City analytics • Resource optimization • Business process improvement • Policy analysis • Long-term evaluation • Pilot projects
16. To What End? Analytics is a postmortem autopsy if not followed by inputs to policy makers to drive change. Consequence: Government has to be willing to listen (and do some part of it themselves)
17. But we can be wrongly driven by interest...
18. ...and being open can be embarrassing
19. 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?
20. Why not increase that slim chance?
21. How NYC did it.
22. NYC is a data factory because it generates data through regulation.
23. In all, a terabyte of raw information — enough to fill nearly 143 million printed pages — passes daily through Mayor Office of Data Analytics
24. Government Business Academia & Researchers Media Motivation Regulate, serve citizens Make profit, social good For science! Public understanding Role Provide data, Regulate companies to provide data Develop product & tools Produce research based on urban data Transform & use data into accessible narrative Example NYC Open Data cartodb.com citymapper.com NYU CUSP fivethirtyeight.com vox.com Enabling Environment
25. 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.
26. 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.
27. 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.
28. 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
29. Indonesia US Price Rp. 1-10/KB (agg) Rp. 5-100/KB (microdata) Free Process Time 3-7 days Instant query & download Detail As-is w/ Margin of error Granularity Kabupaten/kota (>20.000) Census tract (1.200-4.000) Open Data : Game Changer Can I get data on median income?
30. Demo time
31. Community
32. Business Opportunity
33. Indonesia?
34. 511 Kabupaten & Kota 78 with pop. > 100.000 26 of them > 500.000 >50% of Indonesia pop.
35. Spatial Planning Affordable Housing Social Mobility Homelessness Mental Health Social Assistance Public Transit Safety Gang Crime Should we start trying to answer difficult questions?
36. Do hundreds of shiny things... ...drive us to come up with the question that matters?
37. and answer it in the most impactful way?
38. after all, we have our own unique questions why don’t we try to address those?
39. Thank You. Q & A