Dancing the mosh pit style with fresh Openstreetmap ideas – Transcription

The next speaker is Javier Tresoldi. Did I say that right? Javier. Hello, there. I know why everyone is on the other side, probably they want to see better the landscape. But, anyway, always appreciated to be invited after lunch, when people are mostly concentrated, or not. But, anyway, they are there, so it is great to be here. I would like to say thank you to the organization, because we have been really well-considered to come here, although we are working with communities, Latino communities here, in the United States, we come from Latin America. Basically, myself, I’m basically from Bogota, the capital city of Columbia, and we have begun working there in 2010, when we begun to use the open streaming platform. So what that has to do with this, I don’t know if any of you have heard about the mosh pit gathering? Maybe going to heavy metal concerts and so on. Yeah, people go to the mosh pit, the stadiums, they begin to jump and clamp. But it is about bringing ideas in this kind of setting, considering that there are other trends that use a more civilized way, and they do bring ideas into the mosh pit, and they take other areas. And generally speaking, it is an idea of gathering together, you know? And we firmly believe in our community, and our sense of community, that we can also sit together with governments and private sector. I mean, it is a long time ago when the sector was so critical about these firms, like Google, Facebook, etc., but now it is easier to work together because they understand better the situation. So that’s the thing about the mosh pit idea. And we started thinking about a certain way to collaborate, not only in the community, but with governments and private sector, and thinking about this mosh pit thing that was happening in an open data conference to take it to national offices. And right here, you do have the Census Bureau, but we have, for instance, the Columbia, the national office, and we have in Canada that is running pilots. We would see that case further. If I have your interest, then I would like to show you a little bit about our story before we get inside the mosh pit and I show you a couple examples on our own stats of project. We have a foundation in Latin America, we are based in Columbia, and we have communities in Chile and Guatemala, we train grassroot organizations and those that are working in statistics. We support people from low-income classes, usually people from university areas that are interested to get support and to get into the mapping of activities there. And we do it by National Statistic Offices. I would say that the skillles at National Statistical Offices are difficult to find, and mostly understanding what we are do. But we are striving around that, and we will do better when the census rounds come in 2020, because so many cartographic census data is needed so people are sent to the field. And we will probably have armchair census data, but this is the future. I don’t think I have too much time until that comes, but anyway. And we also have hacking activities, and opening data for reports, and so on. And we do also have this idea of working with government, trying to elicit data from civil society, but also from other groups. And, we have also trained people with the open streaming platform in many places. I mentioned here, Panama, is a hub for the last of the Latin American region because it is based in the UNFBA fund for Latin America, and it is based for population, that’s the name, the United Nations Population Fund, and also issues related to reproductive rights in women from 12-15 years old. And anyone heard about data revolution here? No? Not even the older people? Data revolution is something that has been summoned by the United Nations general agreement. Michael is right here, he might be able to tell you more about that, because he is an expert on that ground. There is a general agreement that the United Nations has the right to produce data about a character characteristics of the sustainable development goals. These are goals that, generally speaking, we are looking forward and we will try to attain between 2020 and 2030, this is called the 2030 agenda, which is general goals for many issues, you can imagine, there are all kinds of goal. And what we did about this is to approach these types of projects. This is running start-ups within the National Statistics Offices, and trying to support the guys that are there trying to build new ideas. It is really hard to innovate, but it is also harder to explain to an officer from government how do you do that. I mean, open data is something that we all may be familiar with, but not many governments are really there, you know? Mostly in Central America, that is our region of influence, but also in South America, you don’t find a lot of interest officially. And why? Because they feel so powerful with the data, and they don’t want to open them at all. That would be one of the insights. But anyway, how do we measure this? I mean, applying the mean method, and trying to learn here, how did we measure our action, our impact? We have done in seven countries some activity and found communities there trying to evangelize about the use of open data tools. Also, we run hackathons, we were summoned in 2013 by NASA for the space-up challenge, and there, we were with five local chapters of the NASA spaceship program. It was important for us and we learned about mapping and stuff like that, and we have begun to evolve into the statistical mapping environment. With all of this, we support the 69 mapping project, a term related to statistics in and around the field, basically. So, how do we do this collaboration? Because we spoke about collaboration at the venue, and then specifically about these standards, and how it is done. Basically, it is about discovering first the data. This could be from the national statistics office, but you can also try to find your own data, and try to confront it with real other data. It is important to validate. Usually the officers of governments would like to have a certain, you know, standardization, and also certain characteristics of the data and so on. So this is really important in the whole process. And finally, the uploading, that could be circular and related to the discovery. This is basically how we work, and we tried to fund it, or to base it, on basically this circle of trust, like asking governments for some data that maybe is not open. They usually say they have open data, but that is not always the case. And we do apply a certain open-data analysis. There are several models that do this, but it is five stages. The most open is on CSV5, and you could do it in various different ways. And then, we produce a report among peers, like not only us, but also including the government officers, and finally getting this to a third-party data participant. This is important, because the third-party gives a certain credibility, yeah, credibility would be the word, like you would have the data in the hands of someone else. And so this work is peer-controlled. So finally, what we learned, this is really important. I mean, we haven’t noticed yet how many governments have been using OpenStreetMap. I mean, not in a systematic way. So what we learned a lot was how to adapt with these people, because they don’t have the skills to understand. It is hard, but also challenging, to be transparent in knowledge and share what we do, and also learning from them how they work and how they do maps, because anyway, we are in the same world, you know? Because that is one of our take-aways. And also, the initiative to be associated with governments is really important to set a proper environment to continue the collaboration. So basically, I wanted to show and also exchange and get the feedback from you about two different projects. The first one, Crowded, was a process that worked the other way around that I have been telling you. The National Statistical Office in Canada proposed by itself to use this method, although it was supported by certain technological companies. They proposed themselves on their own, they took the platform, the OpenStreetMap platform, and they produced a narrator, and they tried to demonstrate it is possible to run this kind of survey on the ground, and probably you could use the platform properly. We will see that just now. And the other one is this task for the development project. This is much more a project based on Latin America, and it refers to a certain volunteer idea from the organization from the United Nations and the economic commission for Latin America. They do have a kind of network of all national statistical offices in the region, and they exchange experiences. So, what we did is to take the same idea from the government side, but transparent to the civil society side. So you can dialogue inside the country with some kind of civil society that may understand statistics, but could sit at the table with the government to negotiate and to build up needs based on census data and statistical data, of course, using cartographic tools. So the cloud is a two-year pilot, it has not ended yet, and they wanted to engage people using the mobile devices, and having their own iterator. And it is a lot of building that they map, I don’t have the data exactly, but I think it is around 2 million buildings. So with this – sorry. Within Mobile Editor, what they did is to teach people how they can use it, and also it was a self-contained model that they could find on the web, and that they could download data and take the data of their own neighborhoods, but also downtown, or anywhere that could be done. The deal was to show it to the public so people could fulfill data – very few outfits were considered, but it was still worthwhile to take it into account. They took the building footprints, the addresses, the kind of uses. And finally, they run policy assessment exercises, where they were asking really what a typical government would ask about that, because we really care about quality within the OpenStreetMap community, because we really don’t know which of those quality assessments are the ones that third parties will be interested in. In this case, these are the ones that are interested in government, and these are completeness in coverage, looking at data, semantic occurency, and positional occurency. And most of the data was around 80 and 90 percent, generally speaking, on the data that has been already surveyed, because we have some time until the pilot is ending. So it was great news that the OpenStreetMap platform could be used in the government and also statistical environments. And that brings us, let’s say, encourages us, to do this in other – probably in other countries. I’m not saying that you can apply this kind of access to any country, probably not those that have the sufficient scale would not apply, but those that are similar to Canada, or a contingency like in Brazil, Argentina, or Columbia, could use this exercise as a lesson and it will benefit all platforms at the same time. In Mexico, there will be a meeting of all national statistical offices within this economic commission from the U.N. that will be meeting and speaking about the next steps to run a census. So it is a great time to go there, so what we did is to find the proper location, really lose to The National Statistics Office in Mexico, and we will have our OSM awareness week there, so the message is, in the official setting, why don’t you see what we do, and then we can work together. That is basically our strategy. And, finally, this is – one minute? Okay. Finally, this is the stats for the development project, and basically to establish a network of NGOs. We have already 50 organizations on board. People are mostly from Latin America and the Caribbean, most of the participation is from South America. But we really trust that we can collaborate with these governments, with the National Statistics Office. And then we provide recommendations in this network about how to produce minimal, viable products, because you need to test them on the ground and then you need governments to have the buy-out of governments. So that’s it. I’m really happy to be here, thank you very much for all of your attention. I hope that we can also have feedback afterwards. Can you talk about how you verify the data? Once it is captured by a group, what is your steps in place to – Yeah, basically, we are guided by the rules that OpenStreetMap has about checking the data. But we also do have a structure, like, a parameter structure where you have a head of, let’s say, an area and then you will cover between 200 buildings and 400 buildings, depending on the density of the area. We do cross-checking, and peer review is very important. Most of the methodologies is about five people involved, one of them will be the general manager of the process, two of them will be out of the surveying process. That way, they can gain objectivity about it, and two will be surveyors, probably the head of the group.
Host: Any other questions? Thank you. (Applause). Live captioning by Lindsay @stoker_lindsay at White Coat Captioning @whitecoatcapx.