Chaos Computer Club - archive feed

This study adopts a statistical approach based on Exploratory Spatial Data Analysis to identify underlying contribution patterns of OpenStreetMap (OSM). Univariate and multivariate analyses on a number of variables computed from OSM history on a regular hexagonal grid in Milan (Italy) allow to detect a number of both local clusters and local outliers, which shed light on the complexity of OSM temporal evolution driven by active local contributors and communities, data imports and mapping parties. Compared to traditional geospatial data sources, a major advantage of OpenStreetMap (OSM) is the availability of its full history. In literature, OSM history has been exploited for a number of purposes. The most frequent is intrinsic quality assessment, which - in contrast to extrinsic assessment, where OSM quality is evaluated through comparison against a reference dataset - estimates OSM quality by only looking at its temporal evolution. OSM history has been also explored to gain insights into the project's contribution patterns, e.g. history and profiling of contributors; origin, amount, nature and frequency of edits; spatio-temporal evolution of the whole OSM database - or parts thereof, such as road networks and buildings - in specific areas, or after specific events like natural disasters; and spatial analysis of contributor and contribution patterns. This work fits into the context of OSM intrinsic assessment by proposing a statistical approach based on Exploratory Spatial Data Analysis, and in particular spatial association, aimed at uncovering underlying history-based patterns of OSM data. More in detail, spatial association is investigated in both the univariate and multivariate contexts, i.e. in the cases - respectively - when one variable and multiple variables (together) are examined. The univariate analysis is performed using the Local Moran’s I indicator, which provides a robust classification method to detect statistically significant patterns (compared to the hypothesis of randomness) and define the spatial association type at each location in the dataset. The association type reflects the local characteristics of the variable at each location and its surroundings. Hence it allows detecting clusters, i.e. local patterns of similar (either high or low) values, as well as outliers, i.e. local patterns of dissimilar values (either low values surrounded by high values or viceversa). Instead, the multivariate Geary’s c indicator is employed to detect local association patterns resulting from the joint spatial interaction of two or more variables. A multivariate pattern classification comparable to the one of the univariate case is achieved through a novel classification method developed by the authors. This consists of a comparison of local and global centrality measures (means and medians) for the computed distribution of the multivariate Geary’s c, to produce classification maps of clusters and outliers. The analysis is performed on Milan Province (Northern Italy), counting a population of more than 3 million inhabitants on a surface of about 1.500 km². This area is sampled using a regular hexagonal grid with side of the hexagon equal to 1000 m, producing a total of 684 cells. The analysis is focused on the history of OSM nodes only, with the following hypotheses: only nodes with at least one tag are considered; a new version of a node is counted only when there is a change in tags (not in geometry); only the nodes which currently exist in the OSM database are considered. With this in mind, for each grid cell a number of history-based variables are computed: total number of different contributors who have edited OSM nodes; average number of different contributors who have edited each OSM node; average date of creation of the OSM nodes; average date of last edit of the OSM nodes; average number of versions of the OSM nodes; average frequency of update of the OSM nodes. These values are derived from the processing of the OSM Full History Planet file (downloaded in May 2019) and its conversion into a SpatiaLite database after an intersection with the study area, followed by the computation of the variables for each grid cell. The univariate analysis, performed using the QGIS Hotspot Analysis plugin developed by the authors, highlights different spatial associations for the different variables. While some of them (such as total and average number of contributors and average version) clearly show clusters of high values in correspondence of the most urbanized areas and clusters of low values in the non-urban peripheral areas, spatial association patterns are more heterogeneous for other variables such as the average update frequency. Multivariate analyses are then performed to detect the spatial patterns derived from the joint interaction between two and more of the variables considered. Despite each variable has its own spatial pattern when taken alone, their combination (especially when adding more a

Lightning Talks ## Human in the Loop: Verifying Machine-Generated Data for Better Maps <em>Said Turksever</em> <p>Machine-generated map data has the potential to considerably accelerate mapping at scale. Combining it with human review helps ensure high data quality. We’ll show how a simple game-based tool helps verify the map data generated by Mapillary’s AI, and how that data helps enhance OpenStreetMap.</p> ## Share the word <em>Ilya Zverev</em> <p>WeeklyOSM is great, but is it the only channel for following news in OpenStreetMap? For most countries, yes. And that is sad. You can change it for the better: start a blog, record a podcast, tweet something. Here I will share my experience at keeping OSM community informed.</p> ## Enhancing OSM with missing roads <em>Beata Tautan-Jancso</em> <p>ImproveOSM is a powerful tool that detects and highlights areas in OSM where roads, one-way attributes, and turn restrictions are missing from the map. The first version of the JOSM plugin was released in 2015. Since then, the community has improved almost 200.000 areas with missing roads.</p> ## Community led mapping helping in policy changes <em>Sibabrata Choudhury</em> <p>Beginning of 2015 a process of community consultation and community led advocacy in the eastern state of India has resulted in several communities developing maps of their plots which has been a breakthrough experience.</p> ## How to create a data annotation process used for navigation <em>Alina Negreanu</em> <p>In this talk, the Telenav OpenTerra team will present how they built their data annotation team and the processes they developed in order to assure high-quality annotations, on which their AI algorithms heavily rely on. They will talk about good practices to use when building manual datasets and the hurdles they had to overcome in order to reach their quality requirements, having so far reached more than 600 000 annotations. </p> about this event: https://pretalx.com/sotm2019/talk/EGMAVR/

Ein paar Denkanstösse über den Umgang mit persönlichen Daten Eine kleine Einführung in die Problematik des Datenschutzes. Wie Daten gesammelt und analysiert werden, wielche Schlüsse sich daraus ziehen lassen am Beispiel der Rasterfahndung., Terrorismusbekämpfungsgesetz, Datenfallen im Netz, Verteidigungsstrategien about this event: https://datenspuren.de/2019/fahrplan/events/10190.html

OpenStreetMap's processes are carefully designed to minimize the privacy footprint of the mappers. Nonetheless, the principle that any edit shall be attributable means that some data is still recorded. An overview is given which data is recorded at all and which of it gets available to whom. OpenStreetMap surveys data about places, not about persons. Thus privacy sensitive data in the geodata is very rare and always unwanted. Likewise, the principle of distributing the data allows data consumers of the geodata to stay as anonymous as they want. Mappers can contribute with pseudonyms, although not completely anonymous. However, for both the social features of OpenStreetMap and the purpose of attribution for the edited data it is necessary to collect some privacy related data. A useful starting point to see your own data footprint is the tool HDYC. All the edits you make are grouped into changesets, and the editing software will urge you to add a comment per changeset. As both the edits and the changesets carry dates it is possible to track your activity times. The nature of some edits may suggest local knowledge thus that you actually have been at the mapped places. The kind of edited objects and the mapping standards can be checked by every other contributor as well. Most often, this is simply a reason to be proud of the achievements, but you should know and check before it might get a matter of concern. Using separated accounts for different mapping tasks is often an appropriate solution and well-accepted in the community. OpenStreetMap offers additional ways to interact: you can leave comments on changesets and notes on the map, you can discuss on mailing lists or the forum, or you can answer questions on help. You can write documentation on the wiki. All of these channels have their own rules with regard to how long the data is stored, how it is searchable, and whether you can hide or delete your contributions. The talk presents the data traces of each channel and discusses strategies to get the desired degree of privacy. about this event: https://pretalx.com/sotm2019/talk/XRL7VK/

We propose a model that uses only open data for estimating the minimal energy use of individual buildings for heating and cooling at scale. The workflow is divided in two main blocks: (i) predicting at scale a 3D building stock using OpenStreetMap data, and (ii) estimating the energy use of buildings individually with a back-end model. For mitigating climate change, it is crucial to minimize energy use in buildings while maintaining decent wellbeing (1). Buildings contribute more than a quarter of the global energy-related emissions (2). On the one hand, buildings are among the lowest-hanging fruit for mitigation—with technological solutions available for energy-neutral or even energy-positive buildings. On the other hand, deep decarbonization is challenging because of the heterogeneity in the building stock (2). Moreover, achieving decent well-being conditions for everyone could increase the energy consumption of buildings. For instance, in countries like India where global warming is likely is intensify the deadly effects of heatwaves, air-conditioning is considered an important adaptation strategy. Currently, building energy demand, e.g. for heating and cooling, is mostly estimated for individual buildings with data-intensive models, or with fudge factors in highly aggregated models globally. For rapid, wide-spread mitigation, such methods are not sufficient either to develop solutions that can be transferred across urban areas, nor to develop tailored solutions based on local data everywhere (3). This situation confines impactful climate action to a limited group of cities. There are entire regions with pressing mitigation and development issues that are left behind, in particular rapidly-urbanizing urban areas in the global South (4). The rise of big data and artificial intelligence offer new opportunities to model building energy demand for urban areas, and can even take into account geographical diversity (3). Such data could inform municipal policymakers on spatially stratified but city-wide strategies for climate change mitigation in buildings. However, large-scale spatially-explicit models that compute the minimum energy demand satisfying essential thermal comfort in buildings are still missing. Here, we propose a model that uses only open data for estimating the minimal energy use of individual buildings for heating and cooling at scale. The workflow is divided in two main blocks: (i) predicting at scale a 3D building stock, and (ii) estimating the energy use of buildings individually with a back-end model. In a first step, we use a machine learning model to learn and predict buildings heights from OpenStreetMap and ground truth LiDAR data. The latent energy use of a building can be approximated by its shape and its height (5). However, the height attribute is sparsely populated in OSM. Previous research (6) has demonstrated that building heights can be predicted from features describing buildings and their surroundings. We compare several machine learning architectures and input features spaces. In particular, we are developing a hybrid convolutional neural network based on OSM raster data and scalar features (7). Such architecture enables to take full advantage of both the spatial and the higher-level information available in OSM. We will test how well the model transfers to new cities, and how to improve generalization. In a second step, a back-end model computes the latent, minimal energy demand of each building for heating and cooling. The model accounts for simplified building characteristics, local climatological conditions and ancillary factors. Climatological conditions strongly influence building energy use. The latent energy demand is a simple metric that does not account for occupancy patterns or appliance use. However, this metric provides a lower bound for the energy necessary for thermal well-being, and it is simple enough so that it can be computed for any building. Preliminary results indicate that on average the energy demand in the studied areas can be reduced by a large amount while maintaining decent thermal comfort. However, strategies for energy demand reduction depend on building stock vintage, cultural standards, and the local climate. Our framework provides new insights from OpenStreetMap for more detailed and globally consistent analyses of mitigation strategies in cities. 1. N. D. Rao, P. Baer, “Decent Living” Emissions: A Conceptual Framework. Sustainability (2012) 2. O. Lucon et al., in Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)] (2014) 3. F. Creutzig et al., Upscaling urban data science for global climate solutions. Global Sustainabil

Lightning Talks Lightning Talks about this event: https://pretalx.com/sotm2019/talk/RLZJG9/

The Tasking Manager is OpenStreetMap’s most used software tool to organize mapathons, community mapping initiatives and professional mapping teams. Over the last year it has been developed further significantly. This talk will give an update on the newest developments and the emerging community around the application. The Tasking Manager is OpenStreetMap’s most used software tool to organize mapathons, community mapping initiatives and professional mapping teams. Over the last year it has been further developed significantly. This talk will give an update on the newest developments and the emerging community around the application. Based on tales of data storytelling representatives of the development team of the Tasking Manager are going to discover remarkable curiosities and insights out of a wider application and user analysis, of course backed by hard stats. From this starting point we explain the solutions we implemented in Tasking Manager in the last year to improve the user experience and increase the data quality by mappers using the tool. Three stories will be told, about group of users that are coming to the Tasking Manager frequently and how the changes affected their flow. New mappers, validators and project creators are the main actors of the exciting adventures of combating a low beginners retention rate, lifting data relicts, guiding a mapper through the labyrinth of OSM contribution and learning about the magic of people’s using technology to achieve what they want. We will talk about the new ingredients of the Tasking Manager, from the redesign of the users interface and the interaction among them, to how it now fits into a wider spectrum with much more applications of the OpenStreetMap ecosystem in order to improve direct access to more efficient mapping and data validation. about this event: https://pretalx.com/sotm2019/talk/7Q97AH/

The talk describes the use of OSM as part of an asset management process using a crowd of National Trust staff, volunteers and the public to maintain an network inventory of an estimated 20,000 km of paths (both Public Rights of Way and permissive paths). The process pro-actively notifies local staff of changes to enable on-ground validation. The process required the definition, and consistent application of, a UK standard for path tagging. The National Trust (NT) is a charity set up to look after special places in England, Wales and Northern Ireland. Now the largest land owner in the UK, NT cares for more than 250,000 hectares of land including 775 miles of coastline, 100,000 hectares of statutory wildlife sites, 28,000 buildings and structures, 300 historic mansions and gardens. The NT operates a membership business model which provides members with complimentary access to our pay-for-entry visitor attractions, but also seeks to provide extensive free access to the countryside. The pay-for-entry visitor attractions welcomed 2.5 million visitors in 2018, and an estimated 300 million visits to countryside sites. Recent internal analysis estimates that NT look after a network of 20,000km of footpaths which comprises both legally designated ‘Public Rights of Way’ (25%) and permissive paths (75%). Permissive paths are those where access to members and/or the public is provided, and the condition of the path is monitored. Currently there is no single digital inventory of Public Rights of Way or permissive paths in the UK. The Paths Project is capturing a digital inventory of paths on National Trust in order to: • Demonstrate how NT are fulfilling our core purpose of providing access to special places. • Improve asset management including maintenance and enhancement of the path network, • Provide a digital base for trail curation and enhanced visitor experiences. A review of options concluded that the OpenStreetMap would be the best system for management of the National Trust Paths Inventory. This enables the capture of a digital path data to a defined standard to be carried out by the Trust’s extensive local staff, volunteer network and also any citizens with an interest in paths. The data is then available royalty-free to anybody for the development of products to encourage appropriate access to our special places. This approach is not without challenges. The constancy of path tagging in OSM is not currently suitable for describing the access to the path network. In order to ensure the paths data met the NT needs we worked with OSM UK, and other partners to apply consistent data standards for tagging paths in OSM. This standard is specific to the UK context and enables to differentiation between legal rights of way and permissive paths. In working with local staff to review the current representation a number of challenges were identified relating to the official register of paths and the reality on the ground. This is an evolving area and as the project progresses it is expected that other challenges will emerge. The project set-up an automated process for notifying local staff to changes in their area of knowledge so that changes could can be validated against the reality on the ground. This work provided an interesting technical and organisational challenge and is a somewhat novel approach for large asset owning organisations seeking to utilise OSM and the power of the crowd to manage asset data. The initial focus of the project is on the existence of paths and the legal basis for access. Once this is captured additional attributes relating to accessibility, condition will be considered. Whilst this project is still to be completed, other potential asset types that could be managed in OSM in this way have been identified. The true value of a UK wide paths inventory will only be realised by having a comprehensive, authoritative and trusted dataset. This cannot be achieved by NT alone. When the project is suitable mature NT will make available any parts of the process to other organisations to encourage adopt a similar approach. about this event: https://pretalx.com/sotm2019/talk/VDUV9A/

This presentation describes the nature and life-cycle of carto-vandalism through a data-driven analysis of harmful edits originated from Pokémon Go players. It also assesses how the OSM community reacts to vandalism. The utilization of OpenStreetMap (OSM) data by mainstream tech companies has been on the rise in recent years. Two prominent examples are Snapchat and Pokémon Go that became OSM data consumers in 2017. Snapchat [reports](https://bit.ly/2YAzv70) 190 million daily active users in 2019. Pokémon GO was used by 28.5 million users daily during its peak popularity in 2016 and it still managed to engage more than [10 million](https://bit.ly/2VJS3EO) users monthly in 2018. The large user base of these application puts OSM in an unprecedented spotlight which can be considered a huge success for the project. On the other hand, increased attention comes with side effects. Acts of [vandalism](https://bit.ly/2HBLE4R) manifested in the data no longer stay within the OSM community but will be visible to a worldwide audience. This increased visibility of errors caused by malicious actions (e.g. fake place names, fictive data) can potentially undermine the reputation of the OSM project. In August 2018, a case of [anti-semitic vandalism](https://bit.ly/2HHPRno) surfaced on Snapchat's online maps and also made it to various mainstream media outlets, such as the [BBC](https://bbc.in/2JLO4QY), [Time](https://bit.ly/2VJwpkd) or [The New York Times](https://nyti.ms/2onZJJS). Another type of vandalism can be observed in connection with Pokémon Go, where users modify the underlying OSM data by adding [fictional map features](https://bit.ly/2EjFSnD) (e.g. parks, footpaths and lakes) to gain benefits in the game. OSM’s vulnerability to vandalism is often considered one of its drawbacks directly related to data quality. Despite this and other negative effects on the OSM project, carto-vandalism [1] has only been addressed sporadically in the literature. One study identified motivations behind such actions [2], while some other studies characterized different types vandalism based on investigations of community forums and mailing lists [1] and documented cases of vandalism [3]. According to Linus’s law, the collaborative nature of OSM ensures that vandalism will be discovered and corrected [4]. However, it is unreasonable to expect that all harmful contributions will be found by community [5], therefore, automatic detection of vandalism with rule-based methods is of interest [3, 6]. The OSM community also developed a set of tools to battle vandalism. Using Pokémon Go as an example, this study focuses on the nature and life-cycle of harmful edits with an emphasis on the OSM community's response. Based on OSM changeset comments and discussions, the study first identifies Pokémon related vandalism together with changesets that fixed them or reverted them. This duality allows to study not only the act of vandalism itself, but also the community's response. By analyzing changesets committed by Pokémon Go players, the presentation describes in detail what kind of fictive information these players tend add. A better understanding of this will allow to develop more targeted rules for vandalism detection systems. However, it is important to note that not all Pokémon Go players vandalize OSM and some of them are probably valuable members of the OSM community. It is less obvious, though, if those who started their OSM careers as vandals can be converted to real contributors. As OSM relies heavily on its community, this study seeks empirical evidence of vandals converted to OSM contributors. This would help utilizing OSM's increased visibility to engage and retain more contributors. Vandalism directly affects data quality, therefore we provide a first description of the life-cycle of carto-vandalism analyzing a large pool of events and considering both spatial and temporal constraints. Our initial data analysis shows more than 1,000 revert changesets in response to Pokémon Go vandalism. Since OSMappers often revert more than one changeset at once (e.g. https://bit.ly/2YC7U5f), this number corresponds to more vandalism cases in reality. This provides sufficient amounts of data for our investigation. [1] Ballatore, A. (2014). Defacing the map: Cartographic vandalism in the digital commons. The Cartographic Journal, 51(3), 214-224. [2] Coleman, D., Georgiadou, Y., & Labonte, J. (2009). Volunteered geographic information: The nature and motivation of produsers. International Journal of Spatial Data Infrastructures Research, 4(1), 332-358. [3] Neis, P., Goetz, M., & Zipf, A. (2012). Towards automatic vandalism detection in OpenStreetMap. ISPRS International Journal of Geo-Information, 1(3), 315-332. [4] Haklay, M. (2010). How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environment and planning B: Planning and design, 37(4), 682-703. [5] Goodchild, M

In this talk we try give an overview on how to use GraphHopper to provide a more flexible routing (based on weather information, road class, road width, ...) and how this could be also used for visualization purposes or data analysis. In its first version 0.1 the open source GraphHopper routing engine was able to store just the distance and the car speed and access for every road. Since then many things have changed and improved in version 0.12 and beyond more data can be stored even without knowing Java or GraphHopper internals, but still the storage of those properties is done efficiently. A world wide graph with some basic useful road properties like highway, toll, tunnel, bridge, ferry, width, height, surface, maxspeed and access fits into a routable graph of under 25GB, i.e. just 60% of the planet PBF. GraphHopper allows you to keep this either in memory if you need high speed or serve the graph from the hard drive (incl. cache) to keep the costs low or use your development laptop. Developers and data analysts are enabled to store more features while preserving fast data access. The advantage of the graph-based storage of GraphHopper over a usual database is that the road connectivity can be directly exploited. This is a work in progress and we'll show what is already possible to provide a more flexible routing, data analysis and in-browser visualization with Leaflet. E.g. for routing purposes so called "what if" scenarios can be done to show the impact of a bridge construction via isochrones or reachable areas and also potential problems for HGV vehicles can be outlined. about this event: https://pretalx.com/sotm2019/talk/P8AG7K/

This talk will share lessons that OSM and OSMF members can learn about the multi-years collective dynamics around OpenStreetMap which unfold in French-speaking southern countries of Africa and the Caribbean with the view of identifying paths for local OSM grassroots groups evolution towards a formal OSMF local chapters. It has been some years that OSM and OMSF members have been discussing the topic of OSMF local chapters over emails, wiki, physically through BoF sessions at SotM events. In 2019 the Ugandan NGO MapUganda applied to be the OSMF local chapter in this country. This talk will share lessons that OSM and OSMF members can learn about the multi-years collective dynamics around OpenStreetMap which unfold in French-speaking southern countries of Africa and the Caribbean. In these countries, since the start local OSM actions (outreach, communication, mapping and training) have been organized collectively. These actions lead to the de facto building of first informal collective of mappers which organized internally over the years and for some incorporated as local associations mandated to the promotion and support of the OSM project playing the role of a de facto OSM Chapter. The talk will look at the collective practices of these de facto OSMF local chapters in the light of the OSMF requirements but also look at the OSMF local chapters requirements in the light of this multi-years OSM associative experience with the view to identify itineraries to the building of OSMF local chapters. Like in Milano's BoF sessions, this talk will be collectively built with African mappers involved for many years in these activities and ideally co-facilitated by those from Western Africa successful in getting visas and traveling to Heidelberg. This talk is meant to introduce a BoF session opened to anyone active or interested in supporting the growth of OSMF local chapters connected to the pioneering grassroot collective in the hard environment of the countries of the Global South and especially southern countries of Africa. about this event: https://pretalx.com/sotm2019/talk/VWBV88/

<p>... ein gesellschaftliches und solidarisches Patch <br> <strong>TL;DR</strong><br> Was können wir in einer Umgebung der Anpassung tun, um kritisches Bewusstsein zu fördern und die Abhängigkeit von Expert*innen zu mindern?</p> <p><strong>Ausgangslage:</strong><br> Staatliche und Konzerninteressen prägen längst die Art, wie wir Technik nutzen und Medien konsumieren. Es wird uns leicht gemacht, uns mit den vorherrschenden Verhältnissen zu arrangieren. Spaß am Gerät und Medien, reichen heute nicht mehr aus, um auch kritisches Bewusstsein zu fördern und aus der Konsumentenrolle auszubrechen!</p> <p><strong>Inhalt des Vortrags:</strong></p> <ul> <li>Warum finden sich so viele Menschen mit der <s>unterdrückten</s> angepassten USER-Rolle ab?</li> <li>Was können wir gegen die vorherrschende Passivität und Resignation machen?</li> <li>Wie können wir die Abhängigkeit von Expert*innen mindern?</li> <li>Wie können wir gezielt ein <strong>kritisches Bewusstsein</strong> fördern, das auch zu einer <strong>kritischen und solidarischen Praxis</strong> führt?</li> <li>Warum sind wir in der Gefahr, <strong>selbst zu Unterdrücker*innen</strong> zu werden?</li> </ul> </br></br> <p><strong>Anschließend Meetup für Fragen/Diskussion:</strong><br>14:15 im Seminarraum</p> about this event: https://datenspuren.de/2019/fahrplan/events/10450.html

Hacker tüfteln mit verspielter Hingabe. Hacker machen Angst, indem sie ihr Wissen für Machtspielchen oder zur Machtdemonstration nutzen. Hacker mit entsprechenden ethisch moralischen Grundmoralvorstellungen klären auf, damit kein Raum für Machtspielchen bleibt. Mit diesem Vortrag möchten wir speziell bei funkbasierten Zutrittssystem aufklären. Wir zeigen anhand eines Beispiels im 900MHz-Band Signalanalysen und was man bei der Funkkommunikation beachten sollte. Dazu verwenden wir Software Defined Radio (SDR). Darin werden komplexe Verarbeitungsschritte in der Signalverarbeitung mittels Software gelöst. Das ist zwar langsam, bietet hingegen unglaubliche Flexibilität. ? about this event: https://datenspuren.de/2019/fahrplan/events/10441.html

Who benefits from the mapathons: between (over)communication and (over)attribution, critical feedback on the inflation of a form of action oversold in the field of humanitarian action and development aid. Really for the benefit of OSM? It would be possible to multiply the subtitles for this "Mapathon, mapathon, mapathon!" talk which questions the almost mandatory use taken by this form of collective OSM contribution for humanitarian and development aid stakeholders in the southern territories. "Mapathons in the "south" for what?", "A mapathon does not make a summer", or "Who benefits from mapathons?"... This presentation will aim to open a discussion about the inflation of one specific OSM contribution, to identify the diversity of its practices, the logics of communication, attribution, the quality issues of the data produced, and list the necessary conditions for a mapathon to actually benefit the OSM project in the southern countries and not harming its database. Like in Milano's Bird of Feather sessions last year, this talk will be collectively built with African mappers involved for many years in these activities and ideally co-facilitated by those from Western Africa successful in getting visas and traveling to Heidelberg. This talk is meant to introduce a Bird of Feather session opened to anyone active or interested in this topic and how it impacts the OSM dynamics in the hard environment of the countries of the Global South and especially southern countries of Africa. about this event: https://pretalx.com/sotm2019/talk/GQ3AAF/

Services that provide money advice, access to food provision, digital access and community support are key to supporting those facing poverty. “Our Falkirk” is a simple mapping platform for service discovery that allows enriched OSM data to be easily described, mapped and shared through the concept of data ‘themes’. Falkirk Council is one of 32 Local Authorities in Scotland. Located in the centre of Scotland with a population of around 155,000 people, 1 in 5 people and 1 in 4 children in the Falkirk Council area are estimated to be living in poverty. Fairer Falkirk is Falkirk Council’s strategic response to the rising poverty in the Falkirk Council area. It brings community planning partners together and sets out in detail a series of practical, deliverable, and achievable programmes aimed towards mitigating the impact of poverty on individuals and families. Services that provide money advice, access to food provision, digital access and community support are key to supporting those facing poverty, but ensuring that local people and front-line staff have access to up-to-date information relating to these services is challenging. With funding from the Open Data Institute (ODI)’s Local Government Geospatial Data Stimulus Fund, Fairer Falkirk and their technology partner thinkWhere have harnessed the richness and flexibility of OpenStreetMap to create “Our Falkirk”: an online, map-based tool to allow local people to easily access information on services in the area. The presentation will look at how we’ve created a simple mapping platform for service discovery that allows enriched OSM data to be easily described, mapped and shared through the concept of data ‘themes’. We’ll look at some of the key challenges and opportunities identified through this process, and show how taking an Open Data approach has allowed Falkirk Council to democratise access to vital information through the streamlining of data creation of publication. We’ll look at potential next steps and sign-post the resources now available as a result of this fully open–sourced project. about this event: https://pretalx.com/sotm2019/talk/YENWFX/

This talk discusses different ways how to improve the search experience for domain-specific maps. No map comes without a facility to search for places. As a result quite a few open-source geocoders using OpenStreetMap data have been developed and have matured in the last years. Nominatim, Pelias, Photon, Carmen, there are many to choose from. They all have in common that they offer a general purpose search for addresses, places and, to a more limited extent, places of interest. OpenStreetMap has inspired the creation of many domain-specific maps. Be it maps for specific features like brew pubs, camping or power infrastructure or for activities like cycling, hiking or child entertainment. A general purpose search on these maps is often not satisfying. The special features might simply not be available in the generic geocoders. And when they exist, they do not get the prominence appropriate for the map. This talk explores ways to improve the search experience for such special-interest maps. We start with simple approaches to boost results using existing web APIs and then look into different ways for creating a small custom domain-specific search engine. We discuss advantages and disadvantages of the different approaches and show common pitfalls for implementations. Although some knowledge in system administration and programming is expected, the focus is on solutions for small and medium projects that are realized with limited resources. about this event: https://pretalx.com/sotm2019/talk/PJE8GK/

OpenStreetMap provides a lot of valuable information about urban green spaces, but the numerous and conceptually overlapping OSM tags that describe such features lead to spatially heterogenous representations in OSM. We developed an exploratory data analysis methodology to identify locally relevant OSM tags for mapping green spaces in a specific area and compared the extracted OSM features to administrative data to evaluate the level of completeness in regard to urban green spaces. Urban green spaces provide a variety of important ecosystem services such as micro-climate regulation, increase of biodiversity and the provision of recreational and cultural services for citizens. Thus, they are an important factor for the quality of life in cities (Bolund and Hunhammar, 1999). However, in order to take advantage of these services citizens need to have sufficient information about the location and qualities of nearby green spaces. Within the project “meinGrün” we are addressing this issue by developing a web-based recommendation service which helps citizens find suitable green spaces that satisfy their personal needs. OpenStreetMap (OSM) plays an important role in this project, since it provides a lot of valuable information about urban green spaces such as their location and the amenities they provide (playgrounds, benches, toilets etc.) However, its spatially heterogeneous data quality, especially in regard to the level of completeness, provides challenges for its usage in a recommendation system. Therefore, the integration of OSM data for our purposes requires a prior assessment of the completeness of urban green spaces. The completeness of certain geographic objects is one of the main fields of investigation in regard to OSM data quality. In recent years several studies investigated the completeness of OSM data with respect to the road network (Barrington-Leigh and Millard-Ball, 2017), buildings (Hecht et al., 2013) or land use features (Jokar Arsanjani et al., 2015). Urban green spaces, on the other hand, were rarely the focus of completeness studies. Ali et al. (2016) developed a method to quantify the plausibility of vegetation-related tags being assigned to specific OSM features and Lopes et al. (2017) evaluated the potential of OSM for extracting information about natural local climate zones. Since both of these studies do not explicitly address the completeness of urban green spaces, we developed a new methodology for this purpose. In contrast to buildings and highways, this poses unique challenges due to the variety of vegetation-related OSM tags and the many different forms of urban vegetation ranging from large parks over private gardens to roadside greenery. OSM tags that describe natural objects are numerous and sometimes conceptually overlapping e.g. some features could be tagged as leisure=park or leisure=garden. This leads to different representations of urban green spaces in OSM across different geographical regions. Defining one set of relevant OSM tags to measure the completeness of urban green spaces that can be applied everywhere is therefore not possible. To solve this issue, we developed an explorative data analysis methodology based on OSM and satellite imagery to identify locally relevant OSM tags that indicate urban green spaces. The analysis is based on statistical and graphical methods to evaluate the association between a certain OSM tag and the presence of vegetation. After the relevant tags have been identified, features representing green spaces are extracted from OSM and compared to an administrative data set to assess the level of completeness. As a basis for this comparison, the study area is divided into patches of homogenous land use based on natural and human-made barriers such as the road network, rivers or objects that mark changes in land use (fences, walls, etc.). On this basis, features from both data sets are joined and the level of completeness is assessed using different extrinsic data quality measures. In our talk we will present our methodology along with the results of the completeness assessment for the City of Dresden, which is a pilot city of “meinGrün”, a project funded by the Federal Ministry of Transport and Digital Infrastructure (BMVI). References: Ali, A., Sirilertworakul, N., Zipf, A., Mobasheri, A., 2016. Guided classification system for conceptual overlapping classes in OpenStreetMap. ISPRS Int. J. Geo-Inf. 5, 87. Barrington-Leigh, C., Millard-Ball, A., 2017. The world’s user-generated road map is more than 80% complete. PLOS ONE 12, e0180698. https://doi.org/10.1371/journal.pone.0180698 Bolund, P., Hunhammar, S., 1999. Ecosystem services in urban areas. Ecol. Econ. 29, 293–301. https://doi.org/10.1016/S0921-8009(99)00013-0 Hecht, R., Kunze, C., Hahmann, S., 2013. Measuring completeness of building footprints in OpenStreetMap over space and time. ISPRS Int. J. Geo-Inf. 2, 1066–1091. Jokar Arsanjani, J., Mooney, P., Zipf, A., Schauss, A., 2015. Qualit

The PostgreSQL database with the PostGIS extension is an important instrument in the toolbox of anybody working with OSM data. This talks explains the basics of working with the SQL database and how it handles geographic data. We'll look at getting OSM data in and out of such a database and what we can do with the data once it is in there. The PostgreSQL database with the PostGIS extension has always played an important role in the OpenStreetMap project. The main OSM database is a PostgreSQL database, tile rendering is most often done from a PostgreSQL database, data analysis and data transformations using current or historical OSM data can be done with PostgreSQL. But understanding what the database can and can not do isn't always easy. And there are a ton of tools, from osm2pgsql to Imposm to Osmosis to Osmium and beyond that "do things" with OSM and PostgreSQL databases. It can be daunting to understand what they all do and where their place in the larger OSM ecosystem is. This talk is an introduction into some of the concepts of SQL and geographical data in an SQL database as well as a whirlwind tour about uses of PostgreSQL in the OSM context. We'll talk about use cases from rendering, to data analysis to routing. We'll talk about the data models that enable those use cases and the software that implements them. And we'll also talk about where the limits are and what things can better be done outside the database. The audience will walk a way with an idea of how things fit together and how to approach their own projects using PostgreSQL. about this event: https://pretalx.com/sotm2019/talk/K8N3XY/

The project created from the cooperation between GeoLab (Universidad de Antioquia), and SiCLas (group of cyclists), both present in Aburrá Valley (Colombia), proposes a collaborative mapping by bicycle users as an urban transport mode. The data generation from existing cycling infrastructure will allow an improvement of OSM database, and an optimization in route calculation. In addition, the incorporation of surveys will allow the generation of thematic maps, such as the association of gender with mobility. The cities of the Aburrá Valley, with Medellín as a core city, present a network of bike paths, and the theme of sustainable and non-motorized mobility is gaining increasing importance in public policies in the region. Meanwhile, everyday cyclists, who use the bicycle on a daily basis as a mode of transport, know that this cycling infrastructure has lacks in several aspects, such as a fragmented presence in the territory, non-direct routes, among others. In addition, the cycling infrastructure in OpenStreetMap is not completely mapped or has erroneous information, this represents a problem for cyclists who wish to transport themselves through the city and identify the most appropriate route to their destination. It does not have accurate and relevant information for users such as the location of bicycle parking, bike-share stations and multimodal stations, among others. These reasons represent a disincentive for more people to choose the bicycle as a mode of transport. For these reasons, this project aims to map the existing formal cycling infrastructure, urban transport routes used by cyclists, to optimize route calculation, and aims to create a platform that allows the visualization of safety data, infrastructure, environmental problems (air quality) and gender mobility, among others, in which the information of shared eventualities can be collected and uploaded by the users. From the cooperation created between the GeoLab research group of the University of Antioquia – YouthMappers chapter, and the SiClas group of cyclists, both entities present in the Aburrá Valley, a considerable number of cycling activists will be mapping the cities of the valley with the OSM platform and tools open. The discussion of the existing tags in OSM for the mapping of cycling infrastructures is a topic of interest in the project, and can contribute to a discussion of the creation of new tags in OSM. The status of current information will be verified and corrected and the missing routes mapped. The tools to generate the thematic maps will be KoBo Collect, Mappillary, among others. about this event: https://pretalx.com/sotm2019/talk/KATR7E/

More than 17 million edits globally have been made by paid contributors in the last five years. We look at the long history of corporate involvement in OSM and then dig into the data to quantify the impact this latest evolution of corporate involvement is having on the map and explore the interactions between paid and volunteer mappers. OpenStreetMap (OSM) is both a map and the active community of over a million mappers that create and maintain it. Participation in OSM has largely been studied in terms of motivation and the resulting data quality. Today, the community is comprised by many different interest groups including craft/hobby mappers, humanitarian mappers, professional mappers, and more. The last few years have seen a dramatic growth in a specific group of mappers: corporate editors. These are mappers hired by corporations and edit the map as part of their employment. In November 2018, the OSM Foundation published the _organized editing guidelines_ that outline a number of steps all groups engaged in organized editing activities (including corporate data teams), should take to promote transparency, openness, and engagement with other mappers—especially local community. This work identifies ten corporations that are complying with these guidelines and explores their mapping activities. We found these corporations have cumulatively edited over 17M objects globally in the last five years, of which 9M were edited in 2018 [1]. First, we traced the history of corporate involvement in OSM to show that while this growing phenomena of corporate editing is new, it represents just the latest stage in a long history of corporations both contributing to and benefitting from OpenStreetMap. Next, we used historical quarterly-snapshot OSM-QA-Tiles to quantify where the ten corporations are active on the map and what types of edits they are performing. We find these edits are global in geographical scope, yet vary per corporation in location and edit type: Corporations heavily impact road networks, yet non-corporate mappers maintain the majority of all edits by mapping more buildings and points-of-interest [1]. To date, this research has quantified and contextualized the growing phenomena of corporate editing in OSM and identified the need for more in-depth analysis to more descriptively explain the impact to the map and volunteer mappers in these regions where corporate-editors are active. To further explore these impacts, we need to dig deeper into the editing record to describe the evolution of the map. For this, we are building upon open-source OSM data-processing tools to construct new vector tiles with with full OSM editing histories [4]. These new historical analysis tiles allow us to efficiently explore the evolution of the map in these regions. This allows us to better contextualize and visualize the interactions between corporate editors and volunteer mappers at scale. Previous research has shown that the road network typically gets mapped first and the map builds up from there [2]. To this extent, we will explore the notion of _map seeding_ whereby paid editors create the first version of the road network, seeding the map for others to maintain and grow. Supporting such an idea is the concept of _densification_ of the map, where some mappers prefer to edit where there is existing—though incomplete or sparse—map data, instead of a beginning with a blank section of map [3]. The concept of such editing patterns highlights the nuances in effectively measuring the impact of paid editing on the map. In other words, this question is more complicated than “are corporate editors taking over?” The first part of the research presented here was recently published [1]. The deeper exploration of the data to identify and explain the impact to the map and local communities is current, ongoing research. At State of the Map, I will briefly summarize the completed work to better set the context, and then present the results of our ongoing investigation on the impact to the map and community. 1. Anderson, J., Sarkar, D., & Palen, L. (2019). Corporate Editors in the Evolving Landscape of OpenStreetMap. ISPRS Int. J. Geo-Inf. 8, 232. 2. Ciepłuch, B., Mooney, P., & Winstanley, A. C. (2011). Building Generic Quality Indicators for OpenStreetMap. 19th Annual GIS Research UK (GISRUK), 5. Retrieved from http://eprints.maynoothuniversity.ie/2483/ 3. Corcoran, P., Mooney, P., & Bertolotto, M. (2013). Analysing the growth of OpenStreetMap networks. Spatial Statistics, 3, 21–32. https://doi.org/10.1016/j.spasta.2013.01.002 4. OSM-Wayback Utility available at https://github.com/osmlab/osm-wayback about this event: https://pretalx.com/sotm2019-at/talk/W8BA9K/

OSM Teams is a software framework for building team-based applications on top of OpenStreetMap. We will present how the software is built, why we think it's a good tool for communities, and how you can integrate your application with the framework. OpenStreetMap is first and foremost a community platform. A lot of OSM mapping emerges from grassroots collaborations, from local neighborhood communities to large-scale mapping initiatives. These collectives need tools to communicate, collaborate and sustain their combined motivation around mapping, and to that end we present OSM Teams. OSM Teams is a software framework for building team-based applications on top of OpenStreetMap. Development Seed built Teams internally to coordinate mapping projects, and to share tasks and statistics across mapping applications built on top of OSM. By building an authentication and authorization framework on top of the OSM login, we enable a second identity layer for teams that can be shared throughout apps. If adopted by the wider community, OSM Teams would bring structure to organizational editing. Teams would also support individual mappers by empowering them to discover new communities and causes, and to better understand who else is editing the map. With this presentation, I would like to start a technical and community focused conversation about running organizations, teams, and communities using this framework. Specifically the questions I would like to bring to the community are: how does this fit with existing community patterns? How do we reduce complexity for new mappers? What new application possibilities does this open up? about this event: https://pretalx.com/sotm2019/talk/XHGBU7/

There are 250 million refugees and IDPs in informal settlements that are routinely excluded from population and settlement datasets as well as Sustainable Development Goals (SDGs) assessments. Here, we share results from ongoing research to map and assess SDG indicators at global informal settlements using OSM data and satellite imagery. We present a new OSM-driven schema for monitoring SDG progress that counters the exclusion of informal settlements from other assessments. In 2015, the United Nations introduced 17 Sustainable Development Goals (SDGs) and 169 associated targets to be met as part of its 2030 Agenda. One hundred and ninety three countries declared their commitment to “leave no one behind” in the shared pursuit of SDGs, yet 250 million people around the globe are estimated to be missing from SDGs progress assessments. This presentation focuses on one category of the “Missing Millions”: refugees and internally displaced people (IDPs) living in informal settlements in over 60 countries. In part due to the lack of reliable information on the locations of informal settlements, refugee and IDP populations are systematically excluded from national censuses, representative surveys, global settlement and population data sets, and settlement-level SDG progress assessments. If implementation and monitoring of SDG goals are to be truly inclusive of these highly vulnerable populations, a globally systematic, accurate, and open database of informal settlement locations is required. In order to locate and characterize informal settlements across the globe, we have used multi-sensor satellite (i.e. Landsat, Sentinel-2, and Planet Dove) imagery, machine learning pattern recognition, and crowd-sourced data collection through visual interpretation of high resolution satellite imagery. With informal settlements identified and using Uganda as a relatively data-rich case study, we developed a spatially discrete and temporally informed settlement-level schema for monitoring SDG initiatives and evaluating progress since 2015. To do so, we examined the distribution of OSM tags relevant for SDG goal indicators, built a database of unique OSM flags for specific SDG indicators, identified relevant OSM features within and nearby informal settlements in Uganda, measured when each feature was first added to the OSM database, and assessed the variability in SDGs progress across a global sample of informal settlements. The presence of SDG-relevant OSM features at some informal settlements may reflect past humanitarian or development mapping, while other informal settlements with less attention in OSM may lack any SDG-relevant OSM features. Since we also sought to assess SDG indicators purely through satellite image analysis, we measured the agreement and complementarity of various remotely sensed measurements of SDG indicators and OSM features. Amenities or public services represented in OSM data such as the designation of a building as a school or health center, and sites of portable drinking water have been essential to formalizing the relationship between satellite-derived estimates of SDG proxy indicators and SDG-relevant features in OSM since these features are not readily identified with satellite imagery and thus are complementary to satellite image-derived indicators. Finally, with an eye on scaling up our assessment to the global-level, we evaluated the relevance of the Uganda-based SDG schema for other geographic regions and specific informal settlements. The results of this research highlight the value of fusing place-specific OSM data with spatially expansive satellite imagery for assessing progress toward specific SDGs. Further, the analytical framework developed for this project may inform future OSM volunteer campaigns to map and evaluate settlement attributes of vulnerable populations or help guide development practitioners and programming. Many challenges associated with the considerable variability in OSM tags within and between informal settlements remain for developing a settlement-level schema for assessing SDG progress using OSM data. Further, the absence of SDG-relevant OSM features across so many informal settlements highlights the need for a rigorous assessment of potential bias in settlement-level OSM data availability. Future work thus includes a cross-validation between remote sensing and OSM-derived SDG indicators at informal settlements as well as field-based assessment of the settlement schema. Results from this effort will inform how on-the-ground contributors and global end users of OSM data can adopt the proposed settlement SDG schema to better align data collection for SDGs assessment. about this event: https://pretalx.com/sotm2019-at/talk/LKLEWQ/

Providing more validation checks with MapRules and MapCSS Tag Checks in iD and JOSM to direct mappers to issues as they map. As well as using Overpass queries to retrieve features with data quality issues. There is a need for validation in crowdsourced mapping to ensure that the quality of created data meets the community’s agreed upon standards and best practices. The OpenStreetMap community has created many Quality Control (QC) tools (Osmose, KeepRight, OSMLint, etc.) to identify existing errors within OpenStreetMap data, but there has not been as much emphasis on Quality Assurance (QA) tools to prevent issues from being created during the editing process. We are developing methods to introduce these data quality checks in both the iD and JOSM editors to educate mappers and provide immediate feedback while they are mapping. In order to introduce these new tools, we first need to recognize the methods a user typically uses to learn how to contribute to the map properly: - Peruse the many pages on OSM Wiki; - Reach out to community members on mailing lists, forums, or Slack groups; or, - Follow detailed instructions and receive feedback (sometimes untimely) on tasks completed in a focused project (via Tasking Manager or MapRoulette) This process is accepted and works for those who are resourceful and careful, but we wanted to reduce the barrier to entry for new mappers by creating MapRules. MapRules is an interface to create instructions which generate custom presets and validation rules that are then integrated into the existing validation frameworks in JOSM and iD. Contributors are directed on how to map features according to the generated rules and are provided instant feedback if their changeset does not meet the set specification. In addition to using MapRules to create specifications for collecting features, we are creating validation checks specifically for JOSM using MapCSS based on rules found in QC tools like Osmose, KeepRight, and OSMLint. This approach follows the paradigm of checking data before it is committed to the map. This approach is truly for all contributors and users of OSM. It clearly shows its worth to the mappers who are creating new edits, but it also aids validators to quickly identify problems where they may have had to visually and manually inspect each feature or rely on numerous QC tools outside of the editing environment. To further assist in validation and clean up, we have created a series of corresponding Overpass queries that download only the features with identified data issues. Within JOSM, these issues can potentially be resolved by applying automatic fixes on a feature or in bulk. By bringing more validation into the regular mapping workflow, we can help create a better map. about this event: https://pretalx.com/sotm2019/talk/9SSZQH/

We've learnt about many projects and clever systems that run OpenStreetMap possible, but it's the individuals that are most valuable in what we do. Settle down in your seats as Gregory introduces you to a selection of OSMers and informally chats to them about their involvement. When, how, and why did they join OSM? What do they do in the project? Has that changed? What's their favourite map tag? All these questions and more will potentially be asked. We've learnt about many projects and clever systems that run OpenStreetMap possible, but it's the individuals that are most valuable in what we do. Settle down in your seats as Gregory introduces you to a selection of OSMers and informally chats to them about their involvement. When, how, and why did they join OSM? What do they do in the project? Has that changed? What's their favourite map tag? All these questions and more will potentially be asked. Come to the talk to find out which OpenStreetMappers we will be having a conversation with. Gregory held back from joining until he met some OSM guys in the UK in 2006. You may have seen him shout "Maps" on the stage, but he really enjoys chatting to people in the breaks. If it's your first time or you've got every SotM t-shirt that exists, do find him and say hello. about this event: https://pretalx.com/sotm2019/talk/VANVBY/

Den "Turingtest" zu erwähnen kann ebenso vielsagend wie irreführend sein - allzu verbreitet ist die Einschätzung, da "wisse man schon worum's geht". Der Aufsatz hinter dem populären Turingtest ist hingegen gemeinhin viel weniger vertraut. Schade eigentlich, denn die dezent-provokante Schreibe macht nicht nur Spaß beim Lesen, sondern wirft auch spannende Fragen auf. Dieser explorative Input schnappt sich eine populäre Verhandlung des Turing-Tests - Alan Garlands Film Ex Machina - und setzt diese in Bezug zur Debatte um künstliche Intelligenz sowie zu Turings Aufsatz - und damit automatisch auch zu unserem gesellschaftlichen System und dessen Denktraditionen. Von dort aus lässt sich prima drüber sinnieren, wie wir selbst eigentlich programmiert wurden, als wir meinten einfach nur so "aufgewachsen" zu sein - und ob und wo wir den Code für die Zukunft vielleicht umschreiben wollen. about this event: https://datenspuren.de/2019/fahrplan/events/10484.html

OpenStreetMap enables people to use third-party apps that seem to be more suitable for privacy-conscientious users, but are we as users really private when using OSM-based apps? In mobile applications users generally don’t have control over what gets transmitted over the network. This means that people even in the age of the GDPR are not aware what they expose about themselves when using Android or iOS apps. This talks goes through a few popular open and closed source OSM apps and shows what gets transmitted about you and to whom. Additionally, it shows whether removing ads through in-app purchase gives users of those apps more privacy. Furthermore it will be demonstrated which tracking services are most often used and which risks of de-anonymization could arise from this. Also a brief discussion whether and how software developers can make their software more privacy-friendly will take place. Are users aware which data gets sent to third parties and are they consenting? Do they have a choice? And is this tracking generally bad or can it improve user experience in return? Are there apps which are suitable for people who want to stay private? Is it possible to prevent tracking and how? This talk is going to compare several OSM apps in regards to their privacy levels, but also show how closed data, commercial competitors are performing. about this event: https://pretalx.com/sotm2019/talk/7LMH8R/

This talk presents an initial inquiry into the relations between the Academic and Mapping communities in OpenStreetMap, based on a review of recent publications, interviews of colleagues, and self-reflection of the authors. By this, we aim to understand how and when research-community interactions come to be, what is their nature, and how can these be improved and made more productive for both sides. OpenStreetMap (OSM) can be conceptualized in a multitude of ways: it may be seen as a database, as a platform, as a concept, as a community (or collection of communities), as a social practice, etc. The academic research on OpenStreetMap adopts and utilizes these different conceptualizations, creating various forms of inquiry. For example, quality-related inquiries can be linked to the data/platform perspectives, contributor behaviors are analyzed quantitatively and qualitatively from a more behavioral perspective, and social understandings of OSM are utilized in inquiries into the institutional and community dimensions of the project. Indicative of a more general issue in the relations between geo-information and socio-cultural contexts, these readings of OSM do not represent absolute truths, but rather they emerge from the specific personal, professional, and socio-cultural backgrounds of OSM researchers (OSM-R). Furthermore, they hold the potential to create an effect on the world and specifically on OSM and its communities. However, the extent and nature of these relations in OSM-R, and specifically relations between research and the OSM community (OSM-C) have not received much academic attention yet. This is despite such interactions existing, e.g. when research outputs are presented to the community, when OSM contributors (OSMappers) become researchers themselves and vice versa, or on other occasions. Efforts to establish and strengthen the interaction between OSM-R and OSM-C have already resulted into significant outputs, e.g. the creation of a dedicated ‘OSM science’ mailing list and the stable inclusion of an Academic Track into the annual State of the Map conference. In this talk, we make a step further in the exploration of this issue, with the objective of not only better understanding these interactions but also formalizing an agenda for future OSM-R endeavors. Specifically, we look at the interactions between OSMappers and research communities, analyzing how the two affect each other, what are the implications of these interactions for both the researchers and the community, and how could these be changed to enhance relations and make them more productive ones. While this issue can be studied from the perspectives of both OSM-R and OSM-C, we focus on an initial exploration of the former. For this purpose, we employ two techniques. First, we review OSM-R publications from recent years (2016-2019) and, in addition to classifying them according to the researchers’ background discipline and the topic, consider what type of conceptualizations of OSM are employed there, and whether and how interactions with the OSM-C are considered explicitly. We use this analysis to make an initial assessment of the state of the issue in the field and identify how specific topics/backgrounds affect the ways in which OSM is conceptualized in research. Second, we collect detailed records of experiences of OSM-R/OSM-C interactions via the self-reflections of the authors and interviews with colleagues. While far from representative of the entire field, these allow a deeper observation of the causal processes that lead to the adoption of certain perspectives and to the development (or lack) of OSM-R/OSM-C interactions. In such a way, we gain insights into how researchers that are also mappers manage their different community roles and sets of objectives, when interactions (if any) happen, what their nature is, who initiates them, who dominates them, and why these came to be that way. Furthermore, these reflections allow speculation on how things could have been done differently, which opportunities were missed, and what possibilities exist. Thus, the combination of a view of current research status with an understanding of processes and forward-looking thinking allow us to point towards possible steps and procedures OSM-R could consider in order to create an impact on OSM-C and to enhance research via an understanding of OSM as a community. about this event: https://pretalx.com/sotm2019-at/talk/RZXQP3/

Indexing OSM data in your PostGIS database for fast spatial queires is not as straight foreward as one migth hope. And with each release of PostgreSQL / PostGIS there are more options to try out. This talk will explain different spatial indexing concepts and best practices in PostGIS and present some benchmarking results. When working with OpenStreetMap data in a database you learn pretty soon that you need to index the columns (and rows) which you use for filtering in order to have fast running queries. PostgreSQL offers a variety of these [table access methods](https://youtu.be/W6B8-srOsrs) but when it comes to its spatial extension PostGIS, developers could only use one for the geometry fields for years: The GiST index - an implementation of the [R-tree](https://en.wikipedia.org/wiki/R-tree) search tree concept. But during the last releases new methods were made available, namely BRIN and sp-GiST. Not many resources are yet available to figure out which index strategy to apply for which data processing or analytical workflows. Therefore, I created a simple [benchmark](https://github.com/FxKu/postgis_indexing) to find it out. So far, only for artifical data, but for this years StoM it is planned to extend the experiments to OSM datasets. This talk will explain the different characteristics of each spatial index and present some performance comparisons in terms of query speed, overhead on writes, index building time and index size. It will also cover general indexing best practices such as subdividing geometries, [partial indexing](https://wiki.openstreetmap.org/wiki/User:Species/PostGIS_Tuning#Indices) and introduce new concepts such as [covering indexes](https://info.crunchydata.com/blog/why-covering-indexes-are-incredibly-helpful). about this event: https://pretalx.com/sotm2019/talk/CAD93S/

An analysis of Notes, based on local experience of managing notes. Over 1 735 319 notes have been added to OSM, currently 416 224 notes are still open. Even looking at a small area such as Edinburgh, the city I live in, we have around 10 new notes added every day. It's interesting to note the motivation of people adding notes, many are added by regular experienced mappers for changes that need to happen in the future, some are added by local businesses or anonymous users altering us to problems on the map and some by non technical users for changes that are required. These note encapsulate a few different categories: Things that can be fixed quickly and the note closed straightaway. We then have short to medium term notes, such as shops closing or road closures that may be for issues for between days and months. Then finally then some of the very long term items, such as the construction of the Forth Crossing, New Hospitals or Housing Estates that may be tracking developments for years. But with so many notes remaining open, issues can very easily be missed. I will briefly review some of the tools available for tracking notes, and talk about how we deal with notes including some of our local tests with using github issues to track some of the longer term issues. Finally as well as hopefully look at some ways of managing notes. Hopefully with some prototypes for ways that notes might be improved either directly on the OSM site or via an external site. about this event: https://pretalx.com/sotm2019/talk/SKVRRL/

Our data model is impractical. You know that. Even OGC Simple Features are better. Changesets and versions promised easier reverting — is it simple yet? We have added a lot of features to API 0.6 over the past ten years, but should we have? Let's see what went wrong and what we can improve. People often come to me saying, changesets with huge bounding boxes are impossible to validate. Come on. You know changesets were not meant to group edits by any criteria. Developers look at the data model and derive user experience from it — and it obviously does not work. Every instance of OSM data needs to be preprocessed, converted, filtered, layered, postprocessed and thrown away. We need to stop looking at OSM as a database and start treating it like a map. In this talk I will highlight what's wrong with the current state of API, including both the actual REST API and the server side. Things like topology, notes, GPX traces and stuff: they were coded when the project was small, but the model starts to show its age — and few people know what to do, besides adding more mappers. How come Overpass API became the better API, and what can we learn from it? Changesets should be abandoned by user-facing tools: let's imagine how the mapping, the validation, the undoing of changes would work if we didn't rely on changesets or actually anything API provides. Can we do something to improve data quality right now? Or can we work towards API 0.7, that would help keep the map not only the most complete, but also the most recent? Let's take a step back and imagine how OpenStreetMap should have been working, to make it more fun to work with, while keeping its versatility and simplicity. I have been involved in a couple API 0.7 discussions, made a few tagging proposals and wrote an editor and a change rollback script. That doesn't make me an expert — there are no experts in OpenStreetMap — but it gave me some ideas on how things could be better. Maybe together we will have a clearer path towards the better OpenStreetMap. about this event: https://pretalx.com/sotm2019/talk/V7NUWP/

Travelers have high expectations of their route planners. We explore how preprocessing techniques applied to Linked Open Data derived from OSM (Routable Tiles) can provide a satisfying performance for client-side route planning. Travelers have higher expectations than current route planning providers can fulfill, yet new solutions struggle to break through. Matching user experience from existing applications is already challenging without the large-scale infrastructure most of them have at their disposal; additionally integrating datasets such as the road network, public transportation schedules, or even real time air quality data is an even more laborious endeavour. W3C and OGC mention the usage of Linked Open Data as a best practice for publishing interoperable geospatial datasets. Instead of relying on proprietary data formats or monolithic CSV files, Linked Open Data uses the RDF data model as a framework for existing domain models. Every data element, and even the relations between them, receives a Uniform Resource Identifier (URI). Data publishers can reuse these identifiers to unambiguously refer to resources on the Web, thus making individual data sets more interoperable. The ultimate goal being automated integration, giving even clients the power to execute the queries. Client-side querying differs from traditional approaches but provides some advantages: (i) it takes the load off the service provider, (ii) the data can be cached for subsequent queries, and (iii) the user leaks less personal data. The OSM road network has recently been published as routable Linked Open Data, following a similar approach to vector tiles (http://pieter.pm/demo-paper-routable-tiles/). However, executing route planning queries on the client is still an unsolved problem. Long-distance queries require large amounts of data and downloading all the data takes a long time. It also makes caching less effective because caches have a fixed capacity, and writing to a full cache will evict other data. Moreover, even when all the data ingredients are there, processing them may still take a long time. State-of-the-art route planning algorithms achieve better query execution times by using auxiliary data that has been computed in a preprocessing phase. The biggest bottleneck in client-side querying is bandwidth; downloading more data to improve query times will ultimately make querying even slower. Client-side route planning requires a different approach to match the quality of service of existing services. We explore several ways of preprocessing the tiles to improve the user-perceived performance of query evaluation. As a first step, we compute how to efficiently traverse pedestrian areas. Only the boundary edges of these areas are defined in OSM which means that most routing engines route along these edges, yielding suboptimal paths. Secondly, we identify which nodes and ways are actually needed to cross an individual tile, filtering out the elements that are only used for local traffic. Queries only need the full tiles around the departure and arrival locations. Finally, a hierarchical network graph is computed using an adaptation of the contraction hierarchies algorithm. Each step yields a different view of the tile data and the results are published as Linked Open Data, in accordance with the W3C and OGC best practices. We integrated the results into a route planner for public transportation. The road network is used to route to and from public transport stops. We found that short-distance one-to-many queries such as getting to the closest nearby station that initially took around 400 ms to complete only take around 260 ms now, and the first results are presented after 140 ms. The difference becomes bigger over long distances; queries that used to take minutes to complete can now be answered in seconds. More importantly, downloading and querying the road network is no longer the main bottleneck. The majority of the querying time is currently spent on parsing the data files, which seems like a tooling issue that should resolve itself as the linked data ecosystem matures. about this event: https://pretalx.com/sotm2019-at/talk/GRJC7W/

Von Firewalls und VPNs hat wohl jeder schon gehört - jedoch sind die technischen Details häufig hinter GUIs versteckt, so dass man von den eigentlichen Abläufen dahinter nur wenig sieht. In diesem Vortrag wollen wir auf zwei neue Technologien in Linux näher eingehen: dem iptables-Nachfolger nftables und dem modernen WireGuard VPN-Tunnel. Wir greifen verschiedene Implementierungsdetails auf und zeigen, was die Unterschiede und Vorteile gegenüber Alternativen sind. Gerichtet ist der Vortrag an alle Interessierte, wobei Linux-Admins besonders für die Anwendung in der Praxis profitieren können. Der Vortrag wird in Kombination mit einem darauf folgenden Workshop angeboten. about this event: https://datenspuren.de/2019/fahrplan/events/10399.html

Nachdem der Verlag Heise in der C'T schon GnuPG für tot und unbrauchbar erklärt hat, wird nun der Abschied vom Passwort gefordert und FIDO2 als Nachfolger präsentiert. FIDO2 bietet endlich Schutz vor Phishing und identitätsdiebstahl. Was ist davon zu halten? Es gibt bereits seit vielen Jahren nutzbare und wirklich sichere Alternativen zu unsicheren Passworten; allerdings lässt die Nutzung und Verbreitung dieser Alternativen zu wünschen übrig. In meinem Vortrag werde ich im Detail einige dieser Alternativen, dazu gehört auch der "Neue Personalausweis" (nPA), aufzeigen und auch auf Hindernisse und Hürden dieser Alternativen verweisen. Im Kern sollten die Endnutzer über soviel Fachwissen verfügen, dass sie die vielen Alternativen einschätzen können und sich für die in ihrem jeweiligen Fall angemessen Lösung entscheiden können. Daraus ergibt sich für die Community die Forderung, IT Security Awareness Schulungen durchzuführen. Anhand diverser Beispiele wird das bisher gesagte vertieft. In dem Vortrag wird auf die Verwendung von Zertifikaten eingegangen. Beispiele, die in dem Vortrag genannt werden: 1. Tracking Cookies und die DSGVO. Letztere verlangt die explizite Zustimmung und Einwilligung. Der Endanwender wird aber nur sehr selten über den Verarbeitungszweck ausführlich informiert. 2. Banken und ihre Art der Identifizierung ihrer Kunden. Identitätsdiebstahl hat für die Betroffenen teils schwerwiegende Folgen. Oftmals sind hier zivilrechtliche Ansprüche zu prüfen und die Beweislage ist für die Betroffenen äußerst ungünstig. Was tun? 3. Hatespeech im Namen anderer zu versenden ist schon schlimm. Wenn aber der Empfänger solcher Nachrichten den vermeintlichen Absender öffentlich attackiert, wird es für die Betroffenen hart. Es wird bis zum Tag der Datenspuren bestimmt mehr aktuelle Beispiele geben. da bin ich mir sicher. about this event: https://datenspuren.de/2019/fahrplan/events/10455.html

Abschlussveranstaltung der Datenspuren 2019 about this event: https://datenspuren.de/2019/fahrplan/events/10469.html

Lightning Talks Lightning Talks about this event: https://pretalx.com/sotm2019/talk/KMP9X7/

<h3>Workforce Development and YouthMappers: Understanding perceptions of students in humanitarian mapping.</h3> <em>Patricia Solís and Sushil Rajagopalan</em> The study tried to understand how and to what extent particular extracurricular (informal) activities through YouthMappers could impact workforce preparation and perceptions among students globally engaged in humanitarian mapping. <h3>Contextualizing OpenStreetMap in Mapping Favelas in Brazil</h3> <em>Everton Bortolini and Silvana Philippi<em> Favelas in Brazil are spaces with unique characteristics and need to be mapped. Can OpenStreetMap be an alternative tool for this? <h3>How Knowing the Purpose of Mapping Changes the Map and the Mappers Themselves</h3> <em>Patricia Solís<em> YouthMappers engages university students in humanitarian mapping which provides a potentially valuable learning experience beyond creating the open map. It may also pique new mappers’ interest, satisfaction, and confidence in spatial technologies as well as interest in the people and places that are served by humanitarian mapping projects. This presentation shares findings of a recently published study assessing how contextual information about the purpose of the humanitarian mapping task affects mapping and mappers themselves. about this event: https://pretalx.com/sotm2019-at/talk/L3CQMM/

JOSM is almost as old as OSM but few people really know what it takes to maintain your preferred editor. We'll present the development model of JOSM and who's part of its active community: developers, translators, testers, plugin authors, end users, sponsors, etc. We'll talk about the project difficulties, the major achievements made in the past years, what work is currently in progress and what will happen in the near future! JOSM is almost as old as OSM but few people really know what it takes to maintain your preferred editor. We'll present the development model of JOSM and who's part of its active community: developers, translators, testers, plugin authors, end users, sponsors, etc. We'll talk about the project difficulties, the major achievements made in the past years, what work is currently in progress and what will happen in the near future! about this event: https://pretalx.com/sotm2019/talk/88ZHKQ/

The OpenStreetMap (OSM) community is a global community crossing cultures, languages, and geographical boundaries. Researchers have been working to develop automated approaches to understanding the composition of this community through their contributions to the OSM database. In this talk we propose a new and novel application of theories and models of species abundance from ecological science to understand contributor community structure and distributions in OSM. **Motivation: ** Community is a word that evokes different images for different people. Socially, we as humans require interaction with other people and society is built around people coming together into social groups we call ‘community’. Communities identify different groups and very often the bond within these communities in a set of shared goals and the division of sharing of labour and skills among other resources. Indeed some scholars believe that the feeling of contributing positively to our own communities is one of the most fundamental feelings of satisfaction in life (Proctor, 2013). In all of these ways the now millions of contributors to OSM form the OSM Community. Attempts to understand how the OSM community works have appeared in the academic literature. Amongst the research community there is a curiosity and fascination about the OSM community given: the global extent of OSM crossing cultures, geographical boundaries and languages; the altruistic nature of its members; and its obvious success as a primarily Internet-based community different to almost every non-crowdsourced community we know from our everyday lives. **State of the Art: ** In this talk we shall argue that the model of community required for OSM is more nuanced that many of the current quantitative approaches. Neis et al (2013) amongst others have used concepts of junior, senior, local, external mappers which does capture the distribution of contributors to OSM well. OSM has been shown to loosely adhere to the 90-9-1 rule of Neilsen (2012) which highlights that about 90% of the members of community-based projects are usually only consuming the collaboratively collected information, while 9% occasionally contributes to the project and only 1% demonstrate a very active pattern of contribution of activity. As Begin (2018; PhD Thesis) argues 'characterizing Volunteered Geographic Information (VGI) data requires understanding contributors’ behaviour and many typologies of contributors are proposed in an attempt to link VGI contributors with the nature of the data they provide'. In Begin et al (2018) the authors identifies the different phases of contributor life cycle from a temporal perspective as a contributor's lifespan is a 'university metric'. In a more computationally complex approach Truong et al (2018) develop a multigraph approach with data mining to characterise individuals and identify behavioural groups. The implementation of a multiplex network based on an OSM data sample and an initial analysis make it possible to identify useful behaviours. **Methodology**: We consider a very novel approach to community identification and understanding by borrowing concepts and methodologies from theories and models of species abundance to the individual contributors of the OSM community. This is a novel approach in VGI but a decades old and mature branch of Ecological Science. As Hughes (1986) points out "It is a common observation that in samples from animal and plant communities most of the individuals belong to a small number of abundant species, whereas most of the species are represented by a small number of individuals". In OSM we see that most individual contributors make a small number of edits. However, from the global OSM community, a small number of species (groupings) are represented by a small number of contributors. For example contributors who have contributed thousands of GPS traces or thousands of building objects. We use the OSM Planet History data for a number of selected regions to consider the contribution history of those OSM community members who have contributed in those regions. All software is developed in Python. We then develop and apply the Community Level Modesl (CLMs) from Maguire et al (2016) and others. We define different types of OSM community member species. Species characteristics are based on contribution history and patterns and can be easily changed. For example, we may create a species which are differentiated by the number of OSM Relations they have created/edited. We could decide on three species groups: 0 - 10 relations, 10 - 100 relations or greater than 100. More sophisticated species can be developed. CLMs allow the creation of a species co-occurrence matrix to environmental variables (such as quantity of edits, types of tagging used, etc) which allows prediction of the community structure and the distributions of individual species. Maguire et al (2016) argue that in ecological communities CLMS ha

Get to know the Board and the Working Groups. Together, we run the OSMF. Let's use the SotM to have a real face to face meeting. The public is invited to join the conversation too. SotM is about the community meeting the community. But we don't always seek out everyone we would like to talk to. So let's use this space to make sure as many members of the working groups and the board get to know each other as people and not just online text. All working group and board members are invited on the stage and can discuss anything. The public can also ask questions. Feel free to suggest some agenda items to joost -at- osmfoundation.org about this event: https://pretalx.com/sotm2019/talk/9MR9QK/

Wer sich gegen Überwachung von Kommunikation wehren will, kann sich entweder kryptographischer oder steganographischer Methoden bedienen. Der Vortrag diskutiert die Möglichkeiten und Grenzen der Enttarnung steganographischer Kommunikation im Medium natürlicher Sprachen. Steganographische Kommunikation ist die Kunst des Versendens von Nachrichten über einen offenen Kanal, so dass niemand außer den intendierten Empfänger/innen überhaupt von der Existenz der Nachricht weiß, geschweige denn ihren Inhalt dekodieren kann. Dies unterscheidet sie von der Kryptographie, bei der die Existenz der verborgenen Botschaft prinzipiell wahrnehmbar ist. Häufig werden Bilder als Trägermedien steganographischer Botschaften gewählt. Doch ebenso häufig ist das Verbergen von Nachrichten in unscheinbaren natürlichsprachlichen Nachrichten, etwa wenn Jihadisten Anleitungen zum Bombenbau als Kochrezepte tarnen. Nach einem Überblick über unterschiedliche Spielarten der klandestinen Kommunikation diskutiert der Vortrag die folgenden Fragen: - Was sind typische Merkmale steganographischer Kommunikation im Medium natürlicher Sprachen? - Welche Ansätze zu ihrer Enttarnung gibt es? - Lassen sich überhaupt zuverlässige maschinelle Methoden für die Enttarnung entwickeln? - Mit welchen Maßnahmen kann man eine Enttarnung schwieriger machen? about this event: https://datenspuren.de/2019/fahrplan/events/10373.html

Ever experienced a broken system by simply upgrading packages? No more! This talk introduces the purely functional package manager Nix and the advancements all software distributions can benefit from - with some of those already implemented in mainstream package managers like snap. about this event: https://cfp.all-systems-go.io/ASG2019/talk/AD8VYE/

A summary of the current state of Thunderbolt, kernel as well as user space, including the latest development where the the input–output memory management unit (IOMMU) is used to prevent Direct Memory Access (DMA) attacks. A brief explanation and discussion of such such an attack, the recent Thunderclap attacks, will be given including with a focus on how it is related to the IOMMU feature on Linux. about this event: https://cfp.all-systems-go.io/ASG2019/talk/HXLJNF/

It’s been more than a year since we at Grab incorporated OpenStreetMap into our ecosystem and we have come a long way since then. This talk will focus on our learning journey, our tools, the challenges and our experiences working in the South East Asia region and the vibrant OpenStreetMap communities here. In the past few years, Grab as the biggest ride-sharing provider in Southeast Asia, is one of the biggest users and contributors of OpenStreetMap (OSM) in this region. We have put a great amount of effort into building a healthy ecosystem around it. We now have a better understanding of OpenStreetMap, mapping within its infrastructure, and how communities form one of its strongest pillars. We are excited to share how Grab started from scratch and gradually built a unified framework to manage OSM data as well as, more importantly, the velocity and data richness Grab has contributed back to OSM. We have worked closely with the different corporates, partners and the communities in the South East Asia region to support, build, guide, and empower ourselves and the community in contributing to improving OpenStreetMap. It has been a great learning journey so far with its share of peaks and valleys. Through this talk, we’d want to share our challenges and learnings from these experiences with the global OpenStreetMap community: - Grab’s ecosystem of managing OSM is a crowdsourcing system powered by data analysis, AI techniques, and other organic components - These include manual moderation and on the ground feedback from our well-trained map operations officers who are in every country striving to make the map as accurate as possible with local knowledge - Our experience in collaborating with the vibrant South East Asian Communities and different community partners like HOTOSM, through different programs and initiatives leading to a stronger community in this region - Collaborating with imagery partners like OpenStreetCam and Mapillary by contributing and making imagery available for cities like Singapore and Chiang Mai - Working along with the other corporates in this region as well as representing SEA on the OpenStreetMap Foundation advisory board - We will also share interesting findings of OSM in Southeast Asia and also shed light on how Grab has driven OSM to evolve here. about this event: https://pretalx.com/sotm2019/talk/PAG8CN/

We'll be covering happenings, learnings and new challenges running and supporting systemd in production on the Facebook fleet throughout the past year. This talk is a followup to [State of systemd @ Facebook](https://cfp.all-systems-go.io/ASG2018/talk/192/) that was presented last year. We'll cover the latest developments, how we're leveraging new systemd features, the design of our CI/CD pipeline for systemd, and finally discuss a number of interesting case studies. about this event: https://cfp.all-systems-go.io/ASG2019/talk/983XHL/

OSGeo is all about Open Source Software, Open Data and Open Education. Learn about OSGeo and what builds up this great organization and find out how OpenStreetMap is used by OSGeo projects, how OpenStreetMap can use OSGeo projects and how the two OSGeo and OpenStreetMap are conneted. The Open Source Geospatial Foundation (OSGeo) is a not-for-profit organization whose mission is to foster global adoption of open geospatial technology by being an inclusive software foundation devoted to an open philosophy and participatory community driven development. The foundation provides financial, organizational and legal support to the broader open source geospatial community. OSGeo vision: Empower everyone with open source geospatial OSGeo was founded in 2006 and is well established as a global organization with Local Chapters all over the world. OSGeo represents and supports more than 25 software projects (https://www.osgeo.org/projects/) like QGIS, PostGIS or GDAL. OSGeo organizes many events global and regional all over the world (https://www.osgeo.org/events/). On every event OpenStreetMap is a topic in some of the talks or workshops. The initiative GeoForAll (https://www.osgeo.org/initiatives/geo-for-all/) is an OSGeo Committee and has an Educational outreach and has the mission for making geospatial education and opportunities accessible to all. There is also the OSGeoLive project that covers more than 50 software projects, Open Data and also documentation and tutorials. OSGeoLive is a self-contained bootable DVD, USB thumb drive or Virtual Machine based on Lubuntu, that allows you to try a wide variety of open source geospatial software without installing anything. OpenStreetMap data and software are also included on OSGeoLive. OpenStreetMap data is involved in many OSGeo projects f.e. as sample data, sample service. There is also functionality available to handle OSM data f.e the variety of OSM specific plugins for QGIS or support for OSM in GDAL (https://www.gdal.org/drv_osm.html) or routing on OSM data with pgRouting. Learn about OSGeo and how OSGeo and OSM are connected and join the OSGeo community. about this event: https://pretalx.com/sotm2019/talk/VZVFMS/

Eröffnung der Datenspuren 2019 about this event: https://datenspuren.de/2019/fahrplan/events/10468.html