Advances in Civic Co-management Within the Geospatial Ecosystem Applied to Disaster Risk Management
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| License | CC Attribution - NonCommercial - ShareAlike 3.0 Germany: You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this | |
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| Production Year | 2015 | |
| Production Place | Seoul, South Korea |
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00:00
Online chatVideo gamePresentation of a groupInequality (mathematics)Context awarenessAreaStudent's t-testResultantProjective planeDifferent (Kate Ryan album)Proof theoryDenial-of-service attackGroup actionLevel (video gaming)Observational studyCASE <Informatik>CircleFocus (optics)Open sourceWater vaporPattern languageInformationBitData conversionDigital rights managementPlastikkarteExecution unitMultiplication signLogical constantForcing (mathematics)TwitterConservation lawCausalityContent (media)Computer animation
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DataflowChaos (cosmogony)Water vaporVideo gameDigital photographyType theoryMultiplication signRankingInferenceDependent and independent variablesMereologyDivisorDenial-of-service attackExtension (kinesiology)
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MetreAreaDenial-of-service attackBuildingWater vaporDrop (liquid)Proper mapBitLevel (video gaming)Reverse engineeringStrategy gameSlide ruleAbstractionRoot
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Projective planeMedical imagingWater vaporDataflowLogic gatePopulation densityLevel (video gaming)DivisorFlow separationSpeicherbereinigungGraph coloringDenial-of-service attackMultiplication signCondition numberTwitterIntegrated development environmentCASE <Informatik>CodecNormal (geometry)Line (geometry)Decision tree learning
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TwitterHypermediaTransportation theory (mathematics)Event horizonTablet computerData conversionMedical imagingDenial-of-service attackWordPrice indexComputerPopulation densityCASE <Informatik>Real-time operating systemDependent and independent variablesSoftwareStudent's t-test
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Video gameProjective planeData conversionHypermediaGroup actionDenial-of-service attackMessage passingTwitterMereologyInformationWordLevel (video gaming)Medical imagingVideoconferencingDataflowMultiplication signInferencePanel painting
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Point (geometry)Process (computing)WordMessage passingInformationTraffic reportingVideoconferencingLevel (video gaming)TwitterData conversionPresentation of a groupDenial-of-service attackMultiplication signAreaProxy serverHypermediaOnline helpReal-time operating systemRight angleEvent horizonGraph (mathematics)Virtual machineFunction (mathematics)DatabaseDependent and independent variablesPhysical systemComponent-based software engineeringService (economics)Context awarenessDigital photographyNeighbourhood (graph theory)Condition numberHazard (2005 film)Pattern languageEndliche ModelltheorieLocal ringFamilyPopulation densityWater vaporOpen sourceIncidence algebraLatent heatPower (physics)Key (cryptography)Time seriesState of matterReading (process)Exponential functionPrice indexBitDefault (computer science)SoftwareObservational studySystem callTelecommunicationVector potentialGroup actionVotingFormal grammarWave packetDigital rights managementDifferent (Kate Ryan album)DataflowParallel portLine (geometry)FrequencyWebsiteMobile WebLink (knot theory)Server (computing)Slide ruleFreewareSet (mathematics)
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Decision theoryPhysical systemPresentation of a groupQuicksortOpen sourceDenial-of-service attackOffice suiteBitSet (mathematics)Open setTouch typingImage organizerAreaInformationDependent and independent variablesReal-time operating systemNumberLine (geometry)Level (video gaming)Power (physics)Process (computing)Digital rights managementFile formatTwitterMereologyoutputSoftwareHypermediaData conversionTraffic reportingAddress spaceSummierbarkeitExistenceVotingWater vaporContext awarenessComputer animation
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Physical systemLine (geometry)Denial-of-service attackRevision controlFunction (mathematics)Dependent and independent variablesProcess (computing)
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Real-time operating systemDevice driverDenial-of-service attackLevel (video gaming)Line (geometry)Open sourceProcess (computing)Meeting/Interview
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SpacetimeLevel (video gaming)RectifierOffice suiteGame controllerDifferent (Kate Ryan album)Field (computer science)Multiplication signJava appletLine (geometry)Physical systemRepresentation theoryAreaState of matterScripting languageDecision theoryWater vaporDenial-of-service attackPlanningSubsetProcess (computing)DatabasePrototypeInformationGeometryDigital rights managementSet (mathematics)Open sourceSlide ruleBridging (networking)Computer animationProgram flowchart
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Process (computing)Presentation of a groupDigital rights managementTwitterOpen sourcePower (physics)
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2 (number)TwitterCombinational logicBit rateDrill commands
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Computer animation
Transcript: English(auto-generated)
00:03
I don't think I've had such a welcome to a presentation ever in my life and apologies to all of the PhD students at the back who have just been forced to attend this session. So I guess we can have more of a conversation. So if you have any questions as I'm talking
00:21
or if I'm talking too quickly because I'm a native English speaker and people often complain that I speak too quickly and tell me and I will speak slower. I want to talk to you about a project or more of an idea but then I'm going to present a project as a proof of case study around the use of open source GIS to pull together different
00:46
information sources in a disaster risk management context. So I should also mention that there's a few of us that work on this project. I work at the University of Wollongong in Australia and I'm from the smart infrastructure facility there and so hats off to Etienne, Rohan and Matthew who co-lead this project with me.
01:08
And so we're working on a project which I actually presented the very beginnings of at FOSS4G last year in Portland and so it's really nice to be able to be here again and now kind of show some results of the fruit of our labour and show what we've done.
01:22
So a bit of context, so I live here in Australia and our focus is on South East Asia and our focus is on South East Asia because that's where everybody lives or at least half the people. So half the world live in this circle by population and there are 20 mega
01:41
cities within that circle and of those mega cities 14 of them sit on river deltas and so you can kind of guess where I'm going to go. We know I'm talking about disaster risk management but we'll keep going. 18 of them have experienced flooding in the past decade and so the IPCC recognises that flooding will be one of the most significant impacts to mega cities in the future as a
02:06
result of climate change because as sea levels rise and precipitation patterns change our ability to deal with all of that water inside a mega city is decreasing or at least is challenging us in new ways. And so there's a large group of people that live there and we're
02:24
focusing this project, the Peta Jakarta, the Map Jakarta project on the city of Jakarta in Indonesia. So this is Indonesia, an archipelago of 16,000 islands and then this is the city of Jakarta. So in this mega city, the capital of Indonesia, resides the population
02:43
of Australia in the wider urban conurbation and in the city itself, this light grey area in the middle, there are 14 million people. And this city is served by 13 rivers that flow from the south to the north to the sea. And so that causes quite a problem.
03:00
And so every year during the monsoon season, the rains come and the city floods. And so the city, this is the CBD, this is the Bank of Indonesia or the Grand Indonesia Hotel and then this is all of the financial district in the city centre. And all of these key economic institutions are being flooded because of the city's inability to manage
03:22
the movement of water through the city. And it's worth noting that last year the city experienced 50% more rainfall than the previous year. So a 50% increase in water. And so what's quite nice about this photo is that this fountain, which is part of the independence, one of the independence monuments in Indonesia, people are sat with their backs to the fountain
03:44
looking out on the flood. It's a very Indonesian outlook on life to be sandwiched between two pieces of water to kind of observe the chaos going on in the city. And so this becomes an annual fact of life. During the monsoon season, people here are evacuating as their houses are being flooded. And it's important to realise that this
04:04
disaster happens every year. So it's not an earthquake which you can predict to some extent but may happen at any time. Just this morning there was an earthquake in Chile which has caused tsunamis in the Pacific. But this type of disaster happens every year. So you know that it's coming and we know when it's going to occur.
04:24
And it happens because of the features that are shown on this map. And so here's where all the people live. There's 40 million people in Jakarta City proper. So there's 13 key rivers that flow through the city from the mountains in the south. And this is the ocean. Now, already something like 40% of the city is at risk from flooding because
04:45
it's below sea level. And the city, this dark blue bits are the areas that are sinking the fastest. And those areas are sinking, those areas are sinking up to, that doesn't work, quarter of a metre per year. Well it's half a metre, quarter of a metre per
05:01
year. Every year the city is sinking. And it's sinking because, I'll go back to using this, it's sinking because not one drop of the water that comes from the rivers is used for drinking. So every house and every building in the city of Jakarta has an aquifer, like it has a pump down to the aquifer and it's abstracting that
05:20
groundwater for drinking purposes. And so the city is slowly sinking into the sea. So the sea wall runs along here and the sea wall is as tall as I am. So you go to the edge and the sea wall, which is about this wide, is here. The school is where this guy sat and the fishing fleet is above you because the ocean is now above the city. And so we have this phenomenal density of urban
05:46
infrastructure in a megacity environment with this very serious condition of flooding which happens every year and a condition which is increasing in severity year upon year because of climate change and because of urban densification. So this is a really interesting image because we see one of the
06:05
main canals, one of the main rivers in Jakarta. And so this is a lock gate which controls the flow of water through the city. This is the original Dutch lock gate built in the 1800s by the Dutch settlers of the city of Batavia as it was then. So this used to be the edge of the city. It's
06:24
now the middle of the city. And you see the main east-west railway line. So this is the main train station here which abuts the lock gate. And then you see the main north-south road which goes below the level of the water. So this infrastructure density is also another critical factor in understanding
06:43
why Jakarta is so severely prone to problems when we have flooding. And so this image really typifies the whole essence of the project that we're working on where we have the flood condition and then we have an informal economy which has sprung up around that. So these guys are Garibak garbage
07:02
collectors. So they have a Garibak cart. Normally they'll be collecting the garbage from everyone's house but in this case this guy is paying them to give them a lift across the intersection, across the flooded road. So it's important to realize that in a city of 14 million people you can't evacuate everybody. You have to just move everyone around to the driest bits
07:22
possible at that time. But what's really interesting about this image is what this guy is doing here. He's tweeting it out saying, hey if you're coming to work on this highway the guys are here just give them you know just give them a couple of a couple of dollars and they'll take you across the flooded intersection. And so with this we had a thought. Can we use
07:47
that Twitter data, the social media activity, as an indicator of where flooding is happening in real time? So these are all the tweets and there are around four million of them that occurred with the word flooding or
08:00
Bangea in Indonesian during the 2013-2014 monsoon season. And what's amazing about this image is the density of coverage. So what's important to realize is that more than half the population of Jakarta have two mobile phones. So people don't really have desktop computers but everyone has a
08:22
phone and a tablet or two phones or even three phones. And so everyone is using social media perhaps like in the West we originally started using SMS and so there's a vast quantity of social media conversations going on in response to the real time events taking place in the city, in this case flooding. And what's really fascinating is that you can almost pull out the
08:42
transportation networks of people on their way like that guy and then stuck in the traffic jam because the road is flooded ahead and so sending the tweets saying I'm stuck again the flood has come. And so one last image. So you see here this is a really nice image of one of the canals down near
09:02
the coast and people actually graffiting with their Twitter handles. So it's important to realize that Twitter and social media as a whole is really part of daily life in Jakarta. But I think what's interesting to note is that what's going on in the city is that people are having conversations about
09:21
flooding but those conversations are really relevant to the situation at that time. And so in previous projects that we've seen some of the work done by for example Ushahidi and the Humanitarian Open Street Map team and Patrick Myers group is where they've maybe passively taken social media activity scraped if you like to try and infer what's going on to try and say well if
09:44
we know people are talking about flooding we can just take that information and we can make a map. Now our approach was slightly different because if you just take people's information if you just take their Twitter handles and their Twitter conversations we don't know if you're talking about flooding now or last year or somewhere else in the city. So what we
10:01
did is we convinced Twitter to allow us to send out a message to everyone in the city when they said the word flood. So if you guys in the front are having a conversation about flooding in Jakarta or with this keyword flood then you get a really nice message from us saying hey are you talking about flooding? Are you being flooded now? Can you send us a selfie of the flood of you in the flood? And so we created a very short video which was sent out to two
10:25
million people in Indonesia in Jakarta this year to ask them to tell us about the flooding in real time and that we would put that information on the map. So I'll show you this video see if this works. There is a new tool in
10:52
Jakarta bringing together mobile mapping and local flood information. This community flood map is available anywhere alerting you to water impasses
11:01
in real time to help you navigate the city. We know that the citizens of Jakarta have the best information on flooding conditions. You are already tweeting each other helping friends and family avoid hazards around the city. Peta Jakarta uses this on-the-ground information to give you a comprehensive map of the flood conditions. When you see a flood tweet
11:22
Benjir at Peta Jakarta and your report will appear on the map alerting the community to the flood. Remember to turn on your phone's geolocation so we can pinpoint the report. The more people used Peta Jakarta the better the map will be. Working together we can help everyone bypass flooded areas saving time and avoiding danger. Visit Petajakarta.org to get started.
11:48
So this is the point that was the point that I got to at the end of last year's FOSS4G presentation in the US. Like we have this idea Twitter's on board we're going to send out these videos so now I can tell you what happened and tell you the story of flooding in Jakarta during this
12:04
year's monsoon season from December to March. And so we had these wonderful wonderful messages. So this is a timeline of Twitter messages through our automated process of asking these people to confirm. So this first message is just someone you can see here he's saying there's flooding happening
12:23
he's retweeting the news company TV One News in Jakarta talking about the flooding. So then he gets a message from us in an automated manner that says are you flooded if so activate your geolocation and send your report to us and then check the map at Petajakarta.org. And so then he says
12:45
yeah it's flooding it's 50 to 60 centimeters here's a photo of what's going on in my street great this is where this is my postcode effectively and I'm in North North Jakarta. And so then we send a message back saying thanks Nicky check it out your reports now on the map the map will be used
13:02
or map is publicly available so anyone can see what's going on. And so then we see an activity graph that happens like this of five key flooding events occurring during the monsoon season when people were 6,000 people were evacuated. And we see these spikes of Twitter impressions as we send out these messages automatically saying please tell us please confirm and tell
13:23
us what the situation is on the ground. So what do we do with those reports when we get them from the users? Well we do two things but with one map it's a GIS conference right it's got to be some maps in there somewhere. So the first thing is when you visit Petajakarta in the city on your mobile
13:41
device then just like Google or any other proprietary maps you get the blue dot shows you where you are and then you see all the reports that are around you so if you're going to work or if you're taking the train to school you can see what's going on and say oh I should go this way or this there's flooding coming or I should just check in with my neighbors. But then if you load the same map on a desktop device you see an aggregate overview of
14:03
activity as an indicator of potential flooding across the whole city. And so this design was conceived in response to the government of Jakarta's need for real-time information. So prior to this system it took them six hours to
14:23
compile all of the 911 calls and all of the formal information about flooding that they had to produce a map of where the flooding was in the city to then action response to send the boats to create an evacuation shelter to send aid to the different villages within the city different neighborhoods. And so a brief word on the software which is called
14:44
Cognicity and that allows us to collect these tweets and to put them in a database and then put them on a map and it's free and open source and I'm not going to go into this too much because it's really boring to see schemas on a slide but so Twitter, enter some reports, put in a database, serve it
15:01
out, put it on a map, see it on your phone, use it for disaster response. And so here's a screenshot of the desktop map during flooding in January this year and so those guys are getting pretty wet in northeast Jakarta because it was flooding quite a lot. And so you can see all of the rivers and you can also see all of the pumps and the floodgates that control the flow of
15:24
water through the city. Now if you remember I said that flooding was the impact of flooding was compounded because of the infrastructure density in the megacity and so what happened this year is because electrocution is the biggest cause of death during the flooding of people go into the water but the electricity is on and so then electrocuted the
15:43
power company often turns electricity off to neighborhoods to say we're going to turn the power off so that we know it's safe. Unfortunately they turn the power off to some of the pumps and so the water couldn't be pumped over the seawall and so it just starts to fill up because it's a big bowl and so by trying to turn the power off to a neighborhood they turn the power off to the
16:02
pumps causing a cascading failure and an exponential increase of the amount of water which then proceeded to back up into the CBD. It's worth also noting that many of the other government systems that are available for the government to see the emergency management agency to see where flooding is happening in real time were offline by this point I guess because some of
16:25
the servers got quite wet. Luckily we were still operational and so we kind of inadvertently became the first the first line of hazard information for the government to see where flooding was happening. So here's an example of
16:40
if you take that map and then drill down because you want to see a specific neighborhood or a specific message I can see one of these tweets that's been put it on the map and there's a link and I apologize that you can't read it but it's saying someone's saying yep here's a report of flooding in my neighborhood and here's a photo that I've taken two photos actually to show that flood. Here's the same map on the mobile device so this is where where
17:02
we are at this point in time and then I can see the tweets around me and I can also see the flood infrastructure and the pumps to give me some geographical context to the flood information I'm seeing from other citizens. And so here's a time series of maps for those same five key flood events that I showed on the original bar graph so we can see quite high levels of
17:23
activity in February actually the flood the monsoon came quite late this year the monsoon pattern is changing and so flood three and four and five were quite severe and required some significant evacuations. And so over the whole monsoon period which is about 60 days we had a thousand of these
17:42
confirmed flood reports so a thousand citizens saying yes I would like to say that it's flooding here. There are about 70,000 users on the website and there were over a hundred thousand flood conversations going on in the city. Now this is really important to note based on what we're trying to achieve
18:01
here is that there were a hundred thousand tweets with flood or banjir in. So originally people scraping that data just taking it and then passively looking at it might say there's a hundred thousand flood events or there's a hundred thousand. What we've shown is actually that's not true because a large proportion of these are people talking, are you okay? The news and the media they're not
18:23
flooded where they are but they're reporting about the flooding and so they're sending those messages out. What we've developed is a real-time filtering process to say was a hundred thousand conversations which translate to a thousand confirmed reports on the ground of the flood hazard. And I think this is really important because we see a lot of people approaching this kind of
18:43
challenge under the guise of big data and saying we need to we've got a big data set we've got a hundred thousand tweets we need to try and understand them. So let's teach a machine to think like a human to understand what the tweet said, machine learning. What we did is just ask the people who are already really clever and say can you just tell us if it's flooding? And then
19:03
what we're doing is developing Twitter, not developing a new app, not developing Twitter for emergencies but just using the existing Twitter communication network that people are already using because there's already a hundred thousand conversations going on anyway without us to then act as a process of please tell us in a crowdsourcing manner please confirm the situation on the
19:22
ground. And so the information was used live by the emergency management agency in their control room to make decisions. And so just a couple of examples of people sending us sending some great tweets in and I think this is a really nice example flowline again of tweets to really summarize the
19:42
civic co-management part of my talk which I haven't really touched on yet. But one of the things that we're trying to say is that if the citizens can report to the government and the government can report back to the citizens citizens in real time about a disaster and that's really a process of civic co-management through geosocial intelligence. So we're taking a social
20:01
media network that exists already and we're putting two players together who probably don't trust or necessarily want to talk to each other the government and its citizens but we've found them a way through Twitter that they can have a conversation in real time about what's going on. So here the governor of Jakarta is commenting about the flooding and saying if there's a flood
20:21
please report it to us via Twitter at the Peder Jakarta using the Peder Jakarta system so that the emergency management agency can see what's going on so that we can respond so that we can send a vote so we can set up an aid shelter. And I just love this response of this person saying yep there is some flooding happening maybe maybe we could do with some aid here and this guy who's ingeniously found some
20:41
sort of magical plug for his bathtub and it's just paddling down the street. Amazing. Now in the last few minutes of my presentation I just want to then talk about where we go in the future and the work that we're trying to do this year. So that's great. So we've got all of these people who are tweeting and this is a system which we can easily access as an API, it's geospatial data, we can ask people
21:05
turn on your phone, send us a selfie in the flood like this guy. What do we do about all of the other sources of information that exist for the government in a disaster risk management context for both preparing for disasters, responding to them in real time and then the management that obviously comes after a
21:24
disaster has occurred. And I really kind of want to throw this down as a bit of a challenge to the free and open source geospatial community because I think that free and open source GIS offers us an ecosystem within which to bring all of these things together. And we've seen some great presentations and Alicia
21:41
touched on this from from Mapzen this morning at her keynote talking about how we are an ecosystem and we're all a sum of a number of parts and that we can work together now with these very mature and stable open technologies to say well we can take that data in whatever format it is and put it into some sort of systems that we can understand it and make it actionable. And so here's an
22:02
example of a paper-based report of an area that's been flooded that is still being collected during the monsoon by volunteers on the ground and so there's some geospatial information, here's an address, postcode, phone number even, but these are still being given in to the emergency management agency. So what does a system look like where you have both this amazing tweets going on but then
22:23
also has all these other ancillary sources of information that exist. And I just want to touch on this as a good example. So some of the communities that are worst affected by the flooding in Jakarta are the urban poor and that's because all of the high bits of land are where the rich people live and so when
22:42
you arrive to move to Jakarta, you're an economic migrant, you've moved from elsewhere in Indonesia, you come to the city looking for work, the available area of land for you to build a home or to set up a home is typically near the river or nearest the river and so it's the urban poor who are most frequently affected by flooding because they live nearest the waterways. But actually many
23:03
of these communities are incredibly self-resilient to a lot of these processes already and so that we see these communities independent of the government or independent of any agent or actor outside of the community developing processes of community resilience and so this is a main street that you can walk this main street of this community and what they do is they
23:21
put this rope line in because the flood water comes really fast and it's dark and the power has been turned off but you know if you need to get out then you can get on the rope line and you can pull yourself to safety and everyone in the community agrees that if you go that way then it's going to go to a high ground and you're going to be safe. Now the government response to
23:41
flooding is this which is great it's fantastic it's a boat it's what you need but unfortunately there's a really strong material conflict between the propeller on the boat and the rope line so when the government goes to rescue the people in the community that are most affected by the flooding they override the two systems clash with each other and they override the existing processes of community resilience because they cut the rope line. So what
24:06
can we do? Well can we make a map of where the rope lines are before the flood using free and open source GIS to then give to the government in advance so they can see it in real time so they can ring the boat driver and say don't go down that street because there's a rope line there you need to go
24:22
around the back and so that's what we did we started to try and do this mapping process but as well as just physically mapping where the rope lines are we also asked people about that how they were impacted by the flooding last year and so here's a map of that this is one community which is on the Chile River and you can see how they're really affected by flooding
24:42
because they're really in the middle of these two big meanders and so that the water comes every year and so that this red line here is the rope line these are the main main streets so that you know if you go if you're going this way then you're going to pull yourself to safety or indeed up here this corner with a bridge over the river. We also asked those people how
25:01
we're doing for time yeah okay okay we're very quick we also asked these people how they were affected by flooding last year and I can talk to people about this after and say like how high was the flood when the flood when the flood came how were you affected and we also are trying to
25:24
understand those existing processes of mapping that are already within the community and so many communities are already doing their mapping like this on paper and but it's quite a challenge to then geo rectify a paper map in the GIS to say well this is the actual representation space that you all work on but here it is in real geographical space and so here's a map
25:45
of that then geo rectified it's very crude very quick drawing that we did in the field but then it allows us to see which homes were most affected so we've got the darkest blue saying this is where the water was highest last year so we can start to do planning processes for DRM to say well this these
26:01
are the areas that we need to prepare for the most so I'm at the end last few slides so that our proposed system is using open source GIS so we have a post GIS database we're not building new technologies per se we're using what's there we use JavaScript we need to use node.js we use geo JSON to say how can we pull all these things together to harness them in one
26:24
way so that the government can see all of that information but so can the citizens to make more informed decisions during the flood and so we've got different data sets coming on the left-hand side and then we're pushing those into the map and then the government can make a decision and then they can push out a new map to say the boats on the way or this is
26:42
where the aid shelter is and so this is a prototype of a system that we're working on this year ready for the monsoon season in December and the summary of the whole presentation is that the free and open source GIS that's going on down here is the tool and the technique and the ecosystem that enables citizens and the government to work together and build a
27:04
process of civic co-management for disaster risk management thank you so that the tweets data the of the people saying it's flooded on the
27:37
individual tweets are refreshed every 60 seconds but then the aggregates are
27:41
available one hour six hour or 12 hour intervals so you see you can see the aggregate of the last hour basically and you can drill down and see what's happened over the last hour but they're refreshed every 60 seconds sounds your question