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Making Sense of Sensor Data with Maps

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as per usual prepared far too many slides so if you don't get a chance to ask me any questions on or disagree with me out publicly you're welcome to treat me on my e-mail address and Twitter up on the board now on and that element of making sense of sensor data with maps on the desired social machines and open source maps and Israeli and I work at Carter which is an open source mapping company in my familiar with and I started the top not with a picture of a sensor but on a picture of a kind of an image produced by a sensor kind of sensor a satellite image this is set from the Landsat database which is NASA's public repository of satellite images and it's actually showing up on the border between North and South Korea and right along the DNC and you can see by the colorized images so it use infrared photography or as a layer on 2 highlight the fact that there's a burn scar from that follows that borders so the red part of the EC is actually a prisoner and I liked it shows satellite images and went up but just maps in general mostly because they're so data dense and so high resolution and we rarely kind of achieve that same reflexive rendering and in any kind of application that uses of drawn base maps or or something created by humans right photograph gives you a remarkable density information on with immediate feedback and we're always of striving for that immediacy in applications but rarely do we achieve it on so as his November the
things that you can see the satellite images right this is seaweed agriculture and off the coast of Korea and you can see the kind of grid pattern as you zoom into the high resolution level on that there's this this sort of patchwork of of seaweed on the sort of growing stations and on certain example of something that you would see that and that I think really it demonstrates the purpose of sensors which is to deliver you information that humans would necessarily be able to aggregate themselves right and we have a lot of sensors that detect ambient sort of conditions and environmental factors and blight and remote sensing achieves a satellite images kind of aggregated stated that there's no way he would have scope on on with the human eye right this shows you a view of the world that you would never be able to achieve without that kind of imagery and found and that's with sensor data should give us right view of the world that we wouldn't be able to feel ourselves necessarily as another
example I'm a bit obsessed with the lake culture across the world and if you you can kind of that achieve a sort of time series of capture our caption of the world the satellite imagery if you take satellite images over time right so this is earlier in the eighties found the lakes are kind of thinking that can which is in Argentina on they shrink a little bit by 2013 so even in the static images right you get a sense of of of space time of of change over time and and a lot of with sensor technologies allow you to aggregate this kind of time-series information so it's
a good starting point so this cannot outlet of women talk about senses in spatial information on the internet nothing's I have some critical views about the Internet of Things and our techniques and cartographic some talk about the case study projects and I've worked on specifically and some that I haven't I'm showing how you can use sensor data to force a meaningful and and then on the future of things and then what I see is that how that
will proceed and hopefully they will serve as a good introduction to the rest of the as so this is me the undercover of you gotta make it have and you'll see that I do most JavaScript and intonational CFS and not necessarily the languages of sensor technologies by now well they can be because there's so many frameworks developed telescope developers working in node and to program on dissenters
so this is a kind of these can mostly visualizations and mapping visualizations the case and work in the winter of mapping company so I do a lot of charts and graphs that whole data from our data stored on bias equally API and arsenic literatures general maps from but so I do mostly that kind of thing but I also run on my series of me that's called Note box that work which the programmers that prevented to make machine so it's idea that in addition to visualization and the background of kind of follows
both of those structures both hardware programming and software I used to work at a company culture he which is on another open-source mapping company focused mostly on crisis mapping eyes aware that means witness in Swahili and then it was a company developed in East Africa after the 2007 Kenya elections when there are a lot of riots and they wanted to crowdsource citizen opinion about what was happening and where pockets of islands were springing up and not being controlled reported on on the so well all of these messages taken from feature phones would plot on which you located plot to a map that them with public to journalists who could report on what
was happening and down don't always crises and posted the government and there is some power riots for example they were on sometimes that disasters people need to be mapped districts and so users and base layers as well so that was a combined effort and with its is reporting about where needs were and plotting this to match so that people could try to find those people and help them those Haiti
doing and the code is open source c could play itself and the necessary before what we're doing I we want people to be able to deploy maps anywhere on and a make required a nontrivial not a programming background but but you could still you can still do it and the
utility went well beyond maps so not everyone made a crisis map some people may bite maps on this was crowdsourced fake information and and then we also branched out to solve a few other problems we saw with endemic to East Africa are 1 being blackouts and an internet from lack of Internet infrastructure which was very problematic for a start up based in Nairobi greatly needed to have Internet in order to build a product and down so we developed a particle break which is about the size of a few cell stacked and you could pop in 90 GSM on for a chip and that would connect adjacent satellite network can amplify that signal to support up to 20 devices on a local network so and so we worked on that I didn't work on the hardware part necessarily evidence of the web interface stuff like the visualizations the dashboard by on it also had a bunch of sensor reports that you could collect field data in places where there was no internet from distribution so
caesarian then the product actually for and for she he different for the maps was was fairly friendly in its latest version I the versions of the future versions of was a little bit could you're looking but we try to make it more friendly because we felt that the the worst thing you can do to people in crisis is given that software and then tell them they have to do something with it the so and so that Kennedy shows followed
it on to the next 1 so of employment with security I'm a basically a press consideration the cloud that allows you to track and up-to-date into its run queries on the fly across its to filtering metadata then on also apply courtesy assessed to it to change on how your data will display visually and I had a problem
area was different it was just crisis mapping mapping and this is a project worked on was and she he called then classes a partnership with an infinite Sonja actually and to allow reporters away of reporting about accepted industry in East Africa and the problem here and was and so the problem is to set Lucia he was not built as a platform to allow people to build maps with their data is built as a platform for people to report and crowdsourced people's reports on in real time so uh so this is indeed we had reporters who wanted to make maps with the data that they couldn't make it with our software I this ability action which is a wordpress theme on for for maps but
some but then intra-coded DVD which is a company that allows you to map with the data on the code is also open source people use it for crisis mapping as well but they use it for many other things on here a few
examples of data maps is uh map of people tweeting about a bowl of the center is a map of if a district of London on kind of chloroplast out so that uh prioritizing certain features of those neighborhood so you can determine where you want to reside and then the 1 on the far right is passing prejudicially and developed to give different environmental scores different countries on based on information about how eco-friendly the government is and so the not a different the
projects that can be made with it and the product and look something like this so dragging your data and it you could sit for you and then plotted to a map which you can style and like I said 1 little support queries across Armenia in kind of gooey trade in the browser and then you can also use various other supply reasoning he has to to make it work right and and it's a certain is more introduction on maps mostly because I feel like the way that present information on 3 intuitive for people to to read and you read it and sort of a narrative way in ways that other visualizations and honest transparent so box and whisker plots or bar charts for example on require some kind of digital literacy and so necessarily require and so when you're trying to make sense of data that is essentially opaque to a broad population you need something that will visualize it in a way that is compelling to your audience and to a broader audience right ideally like maps
non-computerized and so i is open-source important to this and this is a predator the hacker uncle disputed territories of the students through their IP addresses 2 different locations and then took captions of Google Maps and what would render in those locations depending on where you were so for example if you're in good time and you are computers located in baton you have a full country on but if you're in China China owns per photon suddenly according to Google Maps quarters and so it's important to have citizens that are capable of making maps right because we often rely on maps these on very in and full of integrity sources for us to follow and help us navigate the world and in reality there is political as they always have been and certain areas might be slated in various projections or in in these that's developed by a certain company they might have a different agenda and so it's important to let people make maps from the data In Advances that
process is an example of OSN at its sound understandable by staining actually for humanitarian relief by using to work which is our library for time series data visualisation is cut her to see the animations that shows people editing eroding a road infrastructure and Paul right after the quake this is another
example of how you can combine kind of just general environmental sensor information with mapped data and in a way that is compelling sensors at a series of charts small multiple charts actually of bird watching in Europe it was for a project called the over mortal arms that we collaborated with a series of organizations on by palm allowed you to create a split-screen map and used
to work make data across it so what you can see is sightings of a particular species of bird on the left and on the right and different environmental factors like temperature you can see how the birds migrate north in when it gets hot and how they might itself when it gets cold either the detected environmental sensors or humidity in other factors you could cross correlate with the bird sightings and and that might make the sensor data more useful right and so that's what we're we're striving for the this enters a spatial information
on how to build sensible city maps
a this is the basic definition of centers on I highlighted some things that sort of highlight and uh change and also use similar terms that you might see in the other sciences such as mapping not coding by upon triggers events and recognizing those events as part of the same family and conversation of our lexicon of terms which is why those things very well together the background is again an Landsat images actually a kind of a colorized abstraction of C O 2 emissions in the oceans I like it because it inverts the paradigm which look at when you look at maps right and look at the land mass and the 1st thing that that's usually what you seek is usually plot data according to its relevance to humans and humans inhabit land but on but this was the oceans right so that's where the the water and sediment interesting and that's what you should you know tried highlighting maps that you feel compelled people write things that surprise them and make them look at the world in a way that's different and they would
reflexively so physical computing a citizen could have and partner pretty nicely and they're pretty affordable on and and the like little microCT machines now acquired of cheap and they offer some kind of traceable time series in a consistent 1 the scripting language ready so you can be just a programmer like I am and still right on to to machines and then on a full status on the external on a lot of people claim competency in too I no 1 really knows hello everything in your mac book pro works right not even an apple developer most people on our very comfortable using technologies that they have no idea how they operate and at least if you build the hardware you build the software you build everything you understand a little bit about the system that you then created and your reliance on other things that is not as thorough for weakening so this is the critical maybe
that appeared in versatility there are various types of sensors on can talk about all of them on but I see most of the center of work that i've done and things that I find useful done with sensors to be all of this kind of decreasing pyramid of utility rates of personal human sensors being like job loans were like a wearable devices not necessarily useful because they're so close to you right like technically I I don't need to know when I go to sleep I I know when I go to sleep I know if I eat healthily I know if I walk enough like this device can prompts me as a sort of on visual prosthetic for a disability that I don't have to and to recognize that I I need to know the pay attention to these data right so I think that's the lowest maybe level of of of sensor data and then is unbeaten environmental which can be helpful but also can be incredibly accessible to your senses right you can if you're in an area we set the temperature sensor you might know you may have a feeling for what the temperature is there might not be an accurate 1 least you have scope on a farm and you don't necessarily need a machine to achieve that scope of active and tactile so things that give you immediate feedback things like fingerprint sensors our for things that require on some kind of interaction I think are quite effective if only because uh the feedback is deliberate and it's not just ambient and sort of in the environment on and they're they're quite there'll be more accurate and remote sensing I think it's really phenomenal and so like satellite imagery for example not necessarily what we think of as developing with sensors that definitely an incredibly perceptive in giving us a scope on the world that we wouldn't be able to get in the way the yeah so a couple of inspiration pieces
and it has the truth and they have and time and I looked on taxes work is an artist he does a lot of large-scale installations and did 1 called space program Mars in the armory in New York with a while ago and he's a hardware programmer so he
built this whole sector with recycled materials of our prototypes for ways to travel to space with like a mobile home that you then outfit with the right arm sort of insulation to travel to space or clothing that would be appropriate for space on this kind of fanciful but
he also built a bunch of tiny machines that did very specific things so this is a little refrigerator it only carries milk and it walks even open the morning and walks back to extinction this acute right but his comment was that we build all of these machines for very specific purposes they don't have a multivalent ability to serve us with anything on we download apps all the time that only do 1 thing that's very wasteful known by and I'll talk about a little later about fridge sensing technologies to think a moderately the winners but only but yes I that was very good point
and and this is a quote that I use that as the my talks with actually some that was she was quoted in an interview after his installation with our space program is expensive slow and crappy and that's why it's magic his son Manasseh right and I think that is analogous to a lot of the GIS software right and it's expensive it can be slow when and and difficult to use and opaque it is not open source and and and so it's magical and obscure to people but it shouldn't be edition hardware right
the and indeed canvases as inversion PC was up project can of coke project with a few companies an asset and Switzerland to distribute sensor Kitson and collect data about cities and then turn all it over to artists and ask them to make all things out it so what they did was actually kind of remarkable on they got a lot of the data they cleaned it themselves so they don't have to deal with some of the issues that you deal with when you get handed sensor data or when you're not very familiar they had engineers who work specifically with that and
so i they built these dashboards for cities so that you could travel between cities and the whole project centered around the map right which is why I talk about it because that maps come but you could compare different cities you have all these like little work charts and small multiple graphs and then and you can also view the winning projects some of
project this was like a real time tracker arm of of various uh had topples for different sensor readings and tragedy that and it didn't use to work although it did illustrate time series in video format on this beautiful right a beautiful representation of the data and a beautiful way to expose the public to the information that they might find useful after on band the artist
and she's a collaborator with a few other people we talked about on the whole this showcase how difficult it is to deal with these data rates and data is not particularly easy sometimes they can be a bit obscure gives a signal in a timestamp you don't necessarily know how to transform that into something useful or plausible on a map or even has a unit that anyone would recognize only and so so I think it's
a good 1 important thing so in things on
I just wanna talk about a different a few different approaches to making sense of sensor data maybe just independent of maps people love to be dashboards right their data services like will be dots on which provides kind a a default little Cui for reviewing your sensor data on the plug and play it is also freeboard on its open source i a t in Internet of Things buzzwords cover the pages and the advertisements on then there's things like our
social services for machines like meet which is like Twitter for machines and they can tweak the readings and you can consume that like you with the Twitter API and use that for your applications on so they have an SDK for dealing with no in multiple languages for dealing with this data and then making them are reformatting and funneling them for the same quarter come anything that tend to what is really
awesome that they have over 200 different EPI services and they provide you with generated code based on which are interesting in programming were machine to on the provide echoed in many other languages they have as decays to support only once including job script in and everything they're pretty great and I use them a little bit for some of the products of shown
a minute then add sexual development the project Open acute gives you on that there are also data providers in addition to data services right there people were giving the sensor data that you can then consumed deal with and is a few geospatial focus ones on on what places of another 1 it's a bit older it's actually thanks to the UK of which reveals system problem with the data providers
the different things that you can think of and Viet and then there's a 2nd layer of facts and the unmatched which is a product of mass that gives you kind of scope on climate information and you can consume that as you would find in any kind of got of application or a web application you can also on system use it fired tend to home for your machines and then the person that attractors I like
to highlight this because and this is my view of my job won't on not particularly useful because my sets right it's very pretty charts and graphs because we know relevant things so if if you 2 minutes of cheese and to pursue passed on we things I think is interesting because of that await the scale like overweight scale thing but it also has an environmental readings on its I don't know if you get on the scale in the morning and feel like you need to know the weather or you need to know are the ambient temperature in the room and that has somehow affects weight but I'm not sure it really does so we have all of these arms solutions will built on sensors for problems so we don't assume we have and that's that's that's important to
consider on this sort of a timeline of of of future fridges right on this in the sixties actually the computerized like kitchen but on the people assigned to get more acquisitive and jokey about the Internet of Things of what could possibly actually do for
us that is that the 2 projects before I finish and it I might skip over this monitoring and tracking I wanted show GPS
information because I never thought I'd and work on it for for my particular projects under something we do
support Carter be armed with 6 tables and with to work you can create kind of real-time visualisations with them with your GPS information or with other to look at
information so we have tutorials on this topic on we also have simple functions and which assumptions that you can run across it to make it a little bit more human readable friendly and connected and look more like a router and less like a series of points
on the other projects built this was built by journalists to track the GPS sound sensor readings on as snowplows in Chicago to show where the cluster the cross-correlated this with the location of different on Alderman city alderman in Chicago to see if they favored their neighborhood or not
on people also doing real time but visualizations artists in LA and is a
product of a student actually to show using the accelerometer stony extracted that data and built incurred interview with that for visualization to show what parts of Brooklyn New York bond biassed for a bike rider on this is another project
which here a collaboration with your maps to use work again to show 1 network activity and therefore like traffic general traffic and also to give it kind of time-series pinpoints telling you what was happening during the day throughout London in different cities that is about it I worked
on follows it through very fast in society and it's over some agriculture security and people use a lot of ambient sensors right to understand and that the cultural landscape of our world so this was a product they were time
she he that a use occurred to be actually for it because we didn't have the infrastructure to support that mostly made for environmental monitoring to drive agriculture sustainability and found it involved the distributed data collection of across a series of different sensor collection points this is of the project was
funded by the Gates Foundation very well funded and unfunded for the past 50 years they've been collecting data for forever in Tanzania and in different east African on countries also in West Africa to try to determine on the ideal agricultural conditions for people to have formed helpfully and sustainably in those areas the the problem is that the data was
of max as you might imagine right you're dealing with sensor data that's been collected from the sixties some people have been manually collecting that data on some has there been written in sometimes they've been typing it sometimes it's been transcribed sometimes an auto ported from devices I'm so is of wide range of the mass of information and it was all given to be in text files on text files with a nonstandard naming conventions with new units and this is very common to what you'll see with the deal with third-party sensor data right you get these files that you can even read on you don't know there's there there's always null values they had every datatype possible in some of the blog entries I would have numbers of plosives of strings and given as entries because these were collected across many different gauging stations so they had a series of rate of water heating stations and they had a different data collected those points a temperature readings at a flow rate on and they wanted that all be consumed in the same application and visualized in a way that was compelling enough to make the Gates Foundation expand their funding on but the problem was that actually will had been collecting the data very thoroughly and this is something you could of known without visualizing it all the colored stations are actually stations that had no usable data on which they did know about because they had just been relying on people to collect the data over time and have been checking on it or making sure that graft appropriately so we need this partner visualization of of map and graph on where you could click on a gauging station the low different graphs that was shown by the data associated with that place and would also 0 out all values and things so that they could really understand what what was lacking and so it worked somewhat like this 1 and over the whole time which is kind of had the full complicated station and now the charts that would display like flow rate temperature and you could filter the charts and everything on yeah so there's an
example dealing with other people sensor data on this is more of a product was to home cost may hurt it's called the value it's of the monitoring of the problem space in this
case and is that these are dying globally in a lot of places it's actually affecting human ecosystems so I'm so I have a lot of these and where the pretending Argentina a letter behind and we wanted to monitor those sensors and this is not a new project right as a group at Yale doing it's there they have on beehives on the roof of on the Paris Opera of people have been maintaining these in and the culture and trying to use machines to understand how the thriving or not after a while but we wanted to aware
project and so we contacted a group this is the map actually was pretty the showing that the the arm the the loss rates in different states so this is
anti-gay which is where around when talking about in Argentina ties between Argentina right actually delta River Delta it's almost like tennis but they have the lot huge the culture there and so as a
particle the basis behind such provides you with like some code in some sense it indicates if you mail them on the use case unit centered at you and they have a network of different beehives globally and so they've been collecting the sensor data and trying to cross compare them and so we built a
little of our project local to us and with the center on mostly marital sensors so temperature humidity also wait things like weight to the hives which will tell you a lot about population and driving around
and then the kid actually is pretty simple as a series of scene of sensors you hook up with Arduinos because he's Raspberry Pi depending on how remote you from it and then you can continue with can do and and uh also use
25 which is that just framework on that uses a protocol called for model to correspond with which we don't have and microcontrollers over USB so on 7 and I worked on that so I knew about that project and that kind of we wanted to use on this is how you would do
like a temperature reading code of a 25 from this have Fahrenheit conversion construction for Fahrenheit folk and from 1 another so the yes although that's the default reading and so this event is if
you less working on it and there's a designer who is very helpful and then my friend collection maintains the Hyades and then doing was that the coding from work under the idea was to
connect the Beehive maintainers with other people in the community wanna support them so we developed this will just kind of consumed on the sensor information and visualize it missile circle so you could see how driving a healthier throbbing the the these were and then you can also donate to the onto the local B and caretakers to support the project if you felt that it so this can complete the feedback loop from presenting data and on and trying to figure out how to visualize it to actually getting people to do stuff with it groups important so satellite data also skip through a little
bit on the problems with z SUB mn journalism project that showed Louisiana Land loss based on satellite information and it was a huge coding effort it took many months had 2 friends working on this it was a team that 5 people working for a 8 months to get this project up and running so it was a non-trivial effort to deal with satellite imagery so that's that's problematic right people should people should be able to access it internet the scale of this kind of epic narrative but they should be able to to do it themselves
so what kind of use case would this be useful for the snap déshabillé's pretty beautiful it's it's attractive Frank on it forests vulnerable to forest fires and so having a satellite-based after having some kind of satellite scope on those areas and circuit admissible feeds that you can follow how your force is doing in that kind thing about the forest on
this is a project that with actually and no idea the next round data that life Alex Stewart worked on that shows on users talk to kind of render on this real terms of hurricane tracking using those data from satellite imagery in the back of the great soldiers something were working on actually is to
provide an kind of catches of satellite imagery allow people to add them to the maps very easily and also that allow them to specify the bounding box for the shape of what they want to visualize them on a satellite map rather than go with the defaults from different it'll providers they're actually kind of expensive right and maybe inaccessible to
some people to the idea that the this to be built into the gooey out of our interface and you will be able to apply satellite and remote-sensing information to your sensor data over to your other data on
so that would be great this is actually a satellite image of kind of walking through the process that you could then into occurred the but it it had it visualizes burning man you might recognize it maybe not in this way right if you've ever been but you don't ever see as a as a citizen of a half of the plan at university Burning Man this way unless you have a images so this is the power of remote sensing rank it gives you so let's scope the so the last thing I
want that is no but and I Runnymede up in New York actually and called new about but it's a global is an international group of people who program robots with the JS and so if you are just a programmer somebody who doesn't necessarily work the serial data and the daily on but you want to to write code for a for robots you can do that this is
many up on I I do with a few other friends right but it's pretty Greywood is
definitely we work on projects and there's international there but stay every every year we all can happen on different projects on some of them Geo related some of them out there are kinds of on 10 different chapters and so you can find me
up on that and then and so so this is a summary of remote active sensing I think is the final moment of some of the more passive sensing as less so has has not developed developed echelon of utility where we know people can act on it in the right way and then on simplified script into devices I think it's great you now right scripting languages to to machines on the mapping of 0 there's geospatial information this is pretty phenomenal necessary it took so long really
apologize and and but in terms of questions comments unwelcome critiques of the it's the
and and on sorry yes the but can you see a name please the but what can also serves to you to the adrenal of machine so I will vote no added human worked mostly with environmental sensors civil temperature sensors on humidity sensors you can buy all of those as components such vendors of interacting no on so I want to let Burma sensors and for the vital signs projects but also of sensors but they were more specified to water on water culture measurement so we would measure like water height would measure also rainfall on and I didn't centers myself so I can tell you where to buy them but I can tell you it looks the at the same so they were like stationary and like this and but when only 1 uh and the senses no that the end server there was standing there and measuring 4 of what some of you will become the act of furthermore we had more of a process that will push them online but for the older projects no they didn't have a problem most of the data was still files that and I
had to transform match to the data they were collected with the survey tool that had a dashboard and have a web interface by on but it was hard to make all of that consistent across from all those years the the the but
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Metadaten

Formale Metadaten

Titel Making Sense of Sensor Data with Maps
Serientitel FOSS4G Seoul 2015
Autor Moser, Aurelia
Lizenz CC-Namensnennung - keine kommerzielle Nutzung - Weitergabe unter gleichen Bedingungen 3.0 Deutschland:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen und nicht-kommerziellen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben.
DOI 10.5446/32071
Herausgeber FOSS4G
Erscheinungsjahr 2015
Sprache Englisch
Produzent FOSS4G KOREA
Produktionsjahr 2015
Produktionsort Seoul, South Korea

Inhaltliche Metadaten

Fachgebiet Informatik
Abstract Growth in affordable hardware for sensor data collection is inspiring distributed data mapping globally. From wearables to arduinos, non-profits and NGOs are leveraging small sensor kits as windows into environmental and ecological health, and mapping sensor data meshes increasingly informs how we appreciate the topography of our world. Still, the parsing and processing of these data in meaningful ways remains a non-trivial challenge for most organizations. At CartoDB, we're working on ways to make this more intuitive, and improve access to geo-referenced sensor data for all. This session will tackle a few sensor data case studies powered by a FOSS stack in the domains of: * water quality/availability * agricultural security * ecological sustainability * animal migration And we'll discuss: * sensor data types, kits, and hardware components * data transformation, cleaning and parsing * mapping data dynamically and statically for public sharing We'll explore some of the challenges to mapping and graphing sensor data via a few case studies in the non-profit field and a few tools (CartoDB, Ushahidi) in the open source space.

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