Big Data for a Public Good

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Big Data for a Public Good
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Big data will not change the world unless it is collected and synthesized into tools that have a public benefit. In this talk Sarah Williams will illustrate projects from her research lab, the Civic Data Design Lab @ MIT, that have transformed data into visualizations that have had an effect on policy reform.
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Maxima and minima Summierbarkeit
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Arithmetic mean Lecture/Conference Personal digital assistant Robotics Videoconferencing Physical system
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Point (geometry) Area Texture mapping Identifiability Information Model theory Projective plane Planning Data stream Spur <Mathematik> Roundness (object) Lecture/Conference Order (biology) Videoconferencing Router (computing) Routing Physical system
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Mobile Web Standard deviation Group action Context awareness Information systems Projective plane Type theory Lecture/Conference Semiconductor memory Lie group Computer network Software testing Formal grammar Physical system
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Metropolitan area network Time zone Arm Lecture/Conference Factory (trading post) Field (computer science)
Area Word Greatest element Matching (graph theory) Lecture/Conference Code Civil engineering Directory service Client (computing) 19 (number) Sinc function
Multiplication Dialect Hausdorff space Texture mapping Lecture/Conference Projective plane Sound effect Smartphone Distance
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Metropolitan area network Lecture/Conference Website Representation (politics)
Point (geometry) Area Metropolitan area network Arm Texture mapping Multiplication sign Cellular automaton Data storage device Maxima and minima Morley's categoricity theorem Estimator Uniform resource locator Lecture/Conference Different (Kate Ryan album) Computer worm Office suite
Metropolitan area network Information Average Multiplication sign Maxima and minima Data type
Type theory Mathematics Goodness of fit Building Meeting/Interview Multiplication sign Projective plane Data analysis
Metropolitan area network Numerical digit Lecture/Conference Semiconductor memory Hypermedia Normed vector space Projective plane
Metropolitan area network Goodness of fit Transportation theory (mathematics) Open source Lecture/Conference 1 (number) Similarity (geometry) Mortality rate Open set
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homo along the time or only a means
ready I 1st was going on the conference presenters for inviting me here I'm really said it's been the land and particularly said it yesterday to
see made a which the activities of the sum the do you know farm why did everybody comes who think through the fire this that came here the Berlin people the 1 from the if and Boston
OK you come from where I come from a fire that had been a long kept so I didn't talk
about how we hear that the rise of big data is going to change the world that we live in but I think that big
data will not change the world unless
it's collected and synthesized into tools that have a public benefit am I run something called the civic data design and that my research lab we take data something that looks like this a spreadsheet and and translated it and to visualisations that we hope
expose effect policy issues so I like to use this example this project I worked on with Laura Kurgan where we took incarceration data uh places where people lived before they were put in prison we
added up block by block and found there many blocks in the US where over a million dollars is spent to incarcerate people these 17 blocks in Brownsville book Brooklyn almost
17 million dollars was spent to incarcerate people from these box the little money was the allocated to the types of resources that would alleviate them from going to prison so these are things like job training programs reentry programs and the idea was to visualize this data and bring it to a broader public on these maps found ended up in the museum of modern art is paired with a map that shows where all those resources are going to prisons upstate New York I and I think 1 of the things that's interesting about this particular project is this idea of bringing it to people on so they
can use it in the way that they want to use it and so actually congressman this map in the museum of modern art and use it in his presentation to Congress to our work on the Criminal Justice Reinvestment
Act of 2010 so he asked if he could borrow some of our images for his presentation I'm at the end of his our maps and none of the results but we affected
Our politician in allocating 25 million dollars to reentry programs in the US which would help people returning home from prison so that idea the visualizations and bringing them to broader public's can
activate a kind of change and
so I think we've heard a lot today about how you use may have data visualization and data that can I be harmful to a private privacy but I did it can also be used for public good so I think it can be used for both sides of the force good and evil I think I try to work on the side of Yoda bomb and bring us data visualizations of a public good in my lab
I make 3 cause I think we need to have a call for data literacy more open data means mean have more access to it but that doesn't necessarily mean we have people who were literate to use that data
I also think we need to make a call for a new data visualization and collection tools in order for us to tell our own stories from are communities perspective we need to create tools from that perspective in order to tell governments about our needs and 3 I think we need a private data for a public would something like ET per cent of the data now stored is owned by private organizations but has a possible public benefit I am today what I wanna talk to you about is number 2 new data visualization and collection tools and I think deeded tools for policy development can be really impactful they allow citizens to collect data outside the formal channels of government and really tell their own story so I wanna tell a story about 1 of my data
collection projects it's called digital Metock use is a partnership with the uh Computing and Informatics Department at University of Nairobi I had the US Center for Sustainable Urban Development at Columbia University my research lab at MIT and is funded by the Rockefeller Foundation and it started
from this premise on that Nairobi suffers from severe congestion problems and this is a very typical seen on the streets of Nairobi traffic jams and this is an issue in many of our fast developing cities across the world I don't working in Nairobi for some time I checked created 1 of the 1st GIS datasets for Nairobi I'm looking at issues around transportation and congestion we created a a I'm transportation model in which you can see here which looks the tree congestion along the roadway we also created a density map for that not all but 1 of the biggest issues as we were have trying to think about how we plan and redirect traffic in Nairobi as we did not have
information on mitotic use these are the small bands on that 3 . 5 million people in Nairobi depend upon to get around the city but yeah she gets
out from this give you a little
video of what I'm at to it is just in case you don't know how more in her own doing just what thing know know if you would know that you could be a
political robot which would know during the meaning that Estonia roving what's this poem is like this you know because in the stomach after Wilhelm well-meaning or only the
circuitry of the joints the name of Timor-Leste and usually works with 3 right which nowadays is more like 30
cents in grams or a where conductors here on the theory that
that our transforming them mitotic elucidate the
reality of millions of variants it so no matter what is
are something that everybody in Nairobi loves to hate dislike most public transport at the top of the conversation and to get some attractive you simply have the real registered in the government and then have somebody make you assignments is actually a matatu signed over and compare of the number 8 is to compare but this is is
hard to navigate we didn't know where y center had added to our model we went to the city council and this was the best dataset that we go find my new there's 132 immortality round these were then sprouts that we found in city council clearly not 2 so we
can't help it create broad data firm model to better transportation planning in Nairobi but that create data that everyone can access in use and benefit from I Nairobi
and use is cell phones for almost everything in the 1 example of that is something called and pays that you can buy coffee with MPC union by matatu ride with and his it's like your credit card itself sends cell phone minutes I have forecast I n we got a factorial
leverage the ubiquitous nature of cell phone use in Nairobi Kenya to capture data about the informal transit systems which most citizens depend upon an open that data for anyone to use and build upon we developed an app
I which B. Broder on on news on metallic to its
on and we collected data in something called G TFS has anybody heard of G TFS it what person that's more than most
times that I ask that question we you probably all use GTF as today in order to find your way in public transport on Google Maps are the underlying data structure is G TFS so you use TFS all the time interval allows us to outperform routing and its it many open source software products are built on this system so we decided to collect data in the system so that anybody could benefit from the many open source tools that use this as package for transportation routing so what is GTF actually
look like I am at here it is our duty of that's coming into our data stream it it really is just a unique identifier and has information about the latitude and longitude of stock and has information about routs and and as you put it together it begins and as the data was coming and it creates a map and here it is the map that we began to create of Nairobi's mitotic system and 1 of the things that you can see and here's we collected data on stops both informal and then these blue which are in and I'm sorry formal what is and an informal is blue and and this was very important for a model but what issues we have is when you look at this is hard to read It's not accessible to everyone in looks simply like the roadway so we started to play around with how can we translate this into something that I people in Nairobi could read I can understand we began to this is that the the road routs you see there's 10 different routs that kind of splinter off how can we make sense of this data we began to create a legend that we played around with colors and in ultimately I we began have something like this but it was still quite hard to understand I the and so we just I just stylized it in a style very similar to something that you would see I'm in the London subway system repairs or even Berlin's NewYork and agree stylized map of Nairobi's armor tattoos on and we did this for a very important reason I'm we wanted to make a point about how extensive the system was compare all ball to other global cities we wanted people in Nairobi to feel proud about the matatu system but we also wanted the government to feel proud about the system as well but we use methods in which to create a system that we're very of important in Nairobi this stops that you see here are landmarks on in Nairobi they use landmarks to get around the city so you see that we can have all the stocks that we collected originally in the dataset but we created strategic stops in order for people to read the maps themselves ultimately we created a map of the whole system i which you can
see here but but what things that was really important to this data collection project is that he has people in Nairobi on what they thought of the maps and they help us actually build this dataset so what you're seeing right here I'm are them and talk to drivers helping at an are mapped and 1 of the things that's very clear and this particular video is the lack of rounds in the north of the city in the mitotic drivers instantly that begins edit the map and think about new routers that they could add in that area and the 1 of the important things about being able to visualize this particular dataset is that we could have created a planning tool that is not just something that used indeed and models but a planning told that everybody in Nairobi can access and use on and so the top drivers were very excited to use this map and I think that's 1 of the
important things about any data project is it shouldn't just be something that you do in isolation we included government stakeholders and NGOs mitotic drivers and owners in the process all along we invited them to join us in our data collection process we have held workshops now that doesn't mean that the government necessarily per participated but it does mean that they have by and tell you a little bit more about that in a 2nd but I think that we
did and this is actually editing the map with a group of stakeholders
and and ultimately releasing this version of the map
that included a matrix in the back which helps people are better navigate their particular stop we also
held at Hackathorn and this is really important because of the deer format DTF as is known to many people in the transportation field but not everyone in a free 1 at the local tech community to build apps with that they needed to know how to use this status standard but there are now 5 apps that
use this data products it with this is a SoNaR which is a popular routing up Nairobi as well something called
mockery rout out which is also a very popular at in Nairobi which people use it to rout themselves but also complain about traffic accidents and tell us about local conditions on the road of crashes and accidents can change dramatically your commute and I can take it from a half an hour to 2 hours and so this après become a 1 of the biggest absent and which was started off of our dataset on but I did that the
most interesting and exciting moments for us use when we got invited to a press conference by the government where they told us this
is the new official map
of the city this is then giving it to the governor of UN Nairobi
and I think also this is really important is because because they included the government in the data processed they don't OK acquiring the mass and put making it the official map of the city even though they didn't necessarily participate in the data collection project they could finally see the benefit and value to them and they could trust the data because we were open about how we were creating it the maps went viral are ones the government rare supported dead and and that yeah
1 of the things that I like to talk about is how do you measure success in an open data project I think that's 1 others is leverage the data we generate 2 create their own policy change so here the government are released the now but since this time I've seen a map
in many different locations is a meeting I thought anew and habitat and you see the map at the top I mean they use the day that you are analyzed new commuter rail out and this
is the ultimate rout map for commuter rail looks very similar doesn't it guys sometimes on the color is even maybe the Figaro is oranges now this immorality but it was really important about this is that this deletion and has an effect on public consciousness because the popularity of the digital mitotic to maps with us something that the UN Habitat wanted to leverage for their own change in getting people to support the commuter rail lines I
since the time of the map we had many other cities assets to help out and they've been doing this work on their own composite 1 opera another 1 they just completed their maps I just heard that Dominican Republic has just finished their own maps there's also group and on my and
I'm then I I'm really excited to say that in our guests that Google made Nairobi the 1st informal transit system in Google Maps so you can actually have navigate the city of Nairobi and find out which matatu you can take by searching on Google well
so all of so I think this is a really interesting pictures as that the global release but in that center is the head of the National Transportation Safety Association who was really excited that we release this data Google Maps and now willing to share data with us and I think opening of data allows you to receive data and then allows you to create more policy changes you can make more decisions are with better data
system a formal transit provides mobility around the world and right now we're really interested in creating a resource network in almost OpenStreetMap type system for creating TTS test data for these informal systems almost every day somebody calls me about whether I can do their own city and the 1 of the next steps in this project is to create a research center and standard so that other people can do this work I right so this is
1 day this story in memory a developing country context I thought I tell you about another Davis story I n are the US has a very different context and then this is a project that I did in New York City on which is
looking at the garment district and other got District is a district in New York City that has protected zoning that means that but people who manufacture in this district have decreased rents so where might be 18 per square foot it that actual rent as well as a lawyer had that office space would be 52 so they get
huge protections for being in the garment district and you can understand why it's me around all the major subway lines right near Times Square between the Port Authority bus station and the train station at its high value real estate and protectionism is important because
fashion is really produced in the garment
district on these are some of the
factories and you can really see fashion on the street the
I'm still fashion designers were really up in arms by that potential rezoning this city wanted to remove the zoning in the garment district and move it out into a Long Island City in 1 of so far the places the field I'm
in that fashion designers said it's this interworking of wholesalers designers retailers manufacturers that make the district work move the manufacturers out the industry will simply collapse and on the other hand manufacturing United States is the client ED 1 per cent since nineteen ED this is the same for the had near city and the U. S. and in a lot of ileum words were arguing that really there is a lot of the can see in
this district what things that you can see is that I they imperil industry is actually declining significantly in this is that the 1st matches 1994 but it's only being maintained in those areas that have protection so that that code in the last match and bottom have predict zoning protection for manufacturing so is shrinking back to it for the place that it's being
supported and 79 per cent of GA may end up here work happens in this midtown Manhattan region so you can see that there would be a huge effect of this multi million dollar industry if it was moved out of the city I'm mean here is a map showing all of the garment related industry work in and around the garment industry and so I thought how can
we solve this debate the city claims 1 thing the landlords claim not air the fashion designers claimant and not not really proved that really it's the proximity in interworking of the district itself and makes it successful and so we started a project of industry which uses smart phones to explore are
on the uh manufacturing industry in the garment district and so what we did is tracked 100 fashion designers for where
I'm two week period where they
collected data on everywhere they want and so this is actually an intern they checked into 4 square and they also we were tracking them on the phone we collected the data that the the went ultimately to a map we signed that
people up through site to canvassing to get people all
around the city yeah I and this is the ultimate I
representation of that data you see a lot of people go to the Government Center of but what I mean how do we quantify this is during image that shows that there's lots of activity but what we do with that data that to make sense of it I so how we
categorize things into different trips and categorize the checked so this is 1 of my favorite traps the trip is when somebody leaves the studio and comes back this person wants a venue which is a B 8 star new beads the store funded beads speedster time ocean of beta these were all my own points that cells B Q estimates of those because 1 of the things this person was clearly doing was going out of the office getting beaten then coming back and this is 1 of the things that they mentioned as being really important thriving garment industry is the ability to have access to the things that they produce and to do that and time I am so we were also
mapped out all the locations that they went to 1 of the things that fashion designers was telling us is that each avenue is the hub of manufacturing and that's actually what you get from the data result this yellow as all the manufacturing areas and this is quite different from what we saw on the traditional business map that I showed you earlier that business maps should things hugging Broadway so when the city was going to rezone they wanna Bob off that eat Avenue quarter the fashion designers were saying no no it avenues is more important I should cut off Broadway arm and this helped us to prove
that information that I think that we found is that people inside the garment district those fashion designers at work inside it and those outside both benefit from the garment district so they both make about the same amount of trips 101 minutes a about 150 minutes of trip time per day but garment district designers to make 9 trips so they can go out whenever they feel like it but those outside can benefit from it they make 4 trips and on average per day on so they come in they chain their trips and then they go out so they benefit from this agglomeration economy we
also found that 1 of the comments that the city was making is that it's only small designers that really use the garment district what you can see here is this yellow represents manufacturing it's a large and mid-level designers that are using it the most of what they're doing is they're producing fashion that then gets sent all over the world to be produced so when people talk about uh manufacturing being Badin near a city with you know not happening in these large Ryan's that and J. Crew without actually happening is J. Crew is producing and the styles that then gets sent all over the world in that the garment district and that's a huge industry it's about a 31 billion dollar industry in yards so they would be seriously affected so what
happens from this data analytics we were able to shell the rezoning and they actually modified the zoning to keep the 8th Avenue to open up much of the Porter along Broadway and shows that data can be really informative and possible and I'll creating change in the district so
I say to you is the new infrastructure we think we need to think about how we can use data as a public goods so just like we were building types at the turn of the last century we're building data pipes time at this time and so many many of the projects that I work on I advocate for data
literacy this is a project that I worked with New York City public schools where we're using lottery data I to understand
probability and more recently were
looking at the issue of ghosts cities there's cities that are completely developed in China and that nobody lives in
memory able to identify those ghosts cities using
activity on social media
and so this is 1 of the ones that we identified so I'm with that I wanna open up for questions and really talk about how you might use data
our for a public good in your city
thank you of tools but I think he siliceous I'm sure is enhanced if you have questions these are the there's 1 gentleman and little the 1 who knows G. offense he was the 1 you know that now but you know on the spot at the end of my questions of all just a 1st if you compare and there'll be a role with Germany you know mortals similarities about the data and the problem was Germany's that we don't know what have or almost no of timetables intuitive histories on the Open Data In the whole Germany it with hundreds of transportation companies who have around 5 to 7 companies which publish do this as data as open source and you're absolutely right you can do a lot of good things so
that but how do we persuade organizations to release their data so that we can so use this data for the public good what would be your own arguments and this is a very good question and this was actually a huge issue in the US so we started to use GTF as our because technically I'm yeah the public organizations are very worried about opening the speed up because they're afraid of getting you'd for inaccuracies in the data I and we had a number have force kids course cases in our legal system to allow it so that they would not get
sued for some of it in accuracy if it went up into google on
and so I think How do we ensure that we can have open data in in many ways They think there's a lot of policies that still need to be developed to help protect those people you want to put the data are on so who's responsible that's incorrect is 1 of the biggest concerns I think for some of these transport systems and why they're not putting the data on another issue I think and 1 of the things that really helped push this forward in the US so we have a lot of problems in this 1st started using fast and it was really Obama created the open data
law which really sad government agencies need to put out data any data that government agencies create a date and it has to go up now the MTA or other public
transborder not and governmentagencies but because they do receive funding from government they do that have to put their data up into the system maybe 1 more right in front yeah up
here I think it's you yeah thank you
yeah thank you very much for the speech and talk
on help army you mentioned a lot about organization and you played around with colors on how did you do that like this part of the team Walker disciplines all involved in the whole thing up there are also many of the questions really that yes the question because I think
to make data work you really need to go work with teams of people and so in the Nairobi project we have a team of people so I'm I'm D-Day analyze a data technician but we also have graphic designers on our team working with us and man is not as graphic designers have policy as protecting whenever you work on a particular project you need to have somebody who specializes in that particular policy to help that team really guide as features of the criminal justice they should at the beginning we actively justice policy experts and the Nairobi project we have people of policy experts and transportation and I am the same way that the zoning issues in New York I think it really helps them figure
out the best way to target your audience but then also have analysts I usually have 3 people my graphic person I have my data analytics person in my policy person and then my person with local knowledge on which we had also in and Nairobi sometimes I act as the graphic indeed a person but it's nice to have 2 people on that team that building teams to work with data is essential and I would encourage from unless
1 hand goes up very quickly that
soul I think we have time for all have on stage right now
I just wanna say in this is really so that you hear I so enjoy your toolkit and I know your map from walking into I have seeing it that and it was great to have everything put into
context here and what is take the opportunity to point out that we actually have a 1 of the founders Jessica colossal
here I haven't says here from I Love and so endurance so people working in different corners of that organization
of mostly hanging around the big make space so as a really great also to the other and I just figured that I have not been the different map from are mapped the day-to-day stylized version of that which is a beautiful but it is 1 of the sure clear especially the ones I have people
in a book a failure of it's so great to make the action and yet I so much for
being with us hope really hanging out with a yet another thing out of our answer question and I have here
on the ground of those surveys things if
thank overwhelm the unit