244 research outputs found
Analyzing the Tagging Quality of the Spanish OpenStreetMap
In this paper, a framework for the assessment of the quality of OpenStreetMap is presented, comprising a batch of methods to analyze the quality of entity tagging. The approach uses Taginfo as a reference base and analyses quality measures such as completeness, compliance, consistence, granularity, richness and trust . The framework has been used to analyze the quality of OpenStreetMap in Spain, comparing the main cities of Spain. Also a comparison between Spain and some major European cities has been carried out. Additionally, a Web tool has been also developed in order to facilitate the same kind of analysis in any area of the world
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Automatic Improvement of Point-of-Interest Tags For OpenStreetMap Data
The user experience of any OpenStreetMap (OSM) based service heavily depends on the quality of the underlying data. If the service deals with points-of-interest (POIs), consistent and comprehensive tagging of the respective map elements is a necessary condition for a satisfying service. In this paper, we develop methods that can automatically infer tags characterizing POIs solely based on the POI names. The idea being that many POI names already contain sufficient information for tagging. For example, \u27Pizzeria Bella Italia\u27 most certainly indicates an Italian restaurant. As the OSM data contains hundred of thousands POIs for Germany alone, we aim for a tool that can accomplish tag extrapolation in an automated way. In a first step, we automatically extract typical words and phrases that occur in names associated with a certain tag. For example, learning indicators for ‘shop=hairdresser’ on German OSM tags led to high scores for ‘fris’, ‘cut’, hair’ and ‘haar’. Having available such indicator phrases, we use standard machine learning techniques to derive the probability for a POI to exhibit a certain tag. If this probability exceeds a certain threshold, we assign the tag to the POI in an automated fashion. We used our extrapolation framework to create new amenity, shop, tourism, and leisure tags. The accuracy of our approach was over 85% for all considered tags. Moreover, for POIs tagged with amenity=restaurant, we aimed for extrapolating the respective cuisine tag. For more than 19 thousand out of 28 thousand restaurants in Germany lacking the cuisine-tag, our approach assigned a cuisine. In a random sample of those assignments 98% of these appeared to be true
On the Representativeness of OpenStreetMap for the Evaluation of Country Tourism Competitiveness
[EN] Since 2007, the World Economic Forum (WEF) has issued data on the factors and policies that contribute to the development of tourism and competitiveness across countries worldwide. While WEF compiles the yearly report out of data from governmental and private stakeholders, we seek to analyze the representativeness of the open and collaborative platform OpenStreetMap (OSM) to the international tourism scene. For this study, we selected eight parameters indicative of the tourism development of each country, such as the number of beds or cultural sites, and we extracted the OSM objects representative of these indicators. Then, we performed a statistical and regression analysis of the OSM data to compare and model the data emitted by WEF with data from OSM. Our aim is to analyze the tourist representativeness of the OSM data with respect to official reports to better understand when OSM data can be used to complement the official information and, in some cases, when official information is scarce or non-existent, to assess whether the OSM information can be a substitute. Results show that OSM data provide a fairly accurate picture of official tourism statistics for most variables. We also discuss the reasons why OSM data is not so representative for some variables in some specific countries. All in all, this work represents a step towards the exploitation of open and collaborative data for tourism.This work has been supported by COLCIENCIAS through a PhD scholarship.Bustamante, A.; Sebastiá TarÃn, L.; Onaindia De La Rivaherrera, E. (2021). On the Representativeness of OpenStreetMap for the Evaluation of Country Tourism Competitiveness. ISPRS International Journal of Geo-Information. 10(5):1-22. https://doi.org/10.3390/ijgi10050301S12210
Towards detecting, characterizing and rating of road class errors in crowd-sourced road network databases
OpenStreetMap (OSM), with its global coverage and Open Database License, has recently gained popularity. Its quality is adequate for many applications, but since it is crowd-sourced, errors remain an issue. Errors in associated tags of the road network, for example, are impacting routing applications. Particularly road classification errors often lead to false assumptions about capacity, maximum speed, or road quality which could then result in detours for routing applications. This study aims at finding potential classification errors automatically, which can then be checked and corrected by a human expert. We develop a novel approach to detect road classification errors in OSM by searching for disconnected parts and gaps in different levels of a hierarchical road network. Different parameters are identified that indicate gaps in road networks. These parameters are then combined in a rating system to obtain an error probability in order to suggest possible misclassifications to a human user. The methodology is applied exemplarily for the state of New South Wales in Australia. The results demonstrate that (1) more classification errors are found at gaps than at disconnected parts and (2) the gap search enables the user to find classification errors quickly using the developed rating system that indicates an error probability. In future work, the methodology can be extended to include available tags in OSM for the rating system. The source code of the implementation is available via GitHub
Metamorphic testing of OpenStreetMap
Context: OpenStreetMap represents a collaborative effort of many different and unrelated users to create a free map of the world. Although contributors follow some general guidelines, unsupervised additions are prone to include erroneous information. Unfortunately, it is impossible to automatically detect most of these issues because there does not exist an oracle to evaluate whether the information is correct or not. Metamorphic testing has shown to be very useful in assessing the correctness of very heterogeneous artifacts when oracles are not available.
Objective: The main goal of our work is to provide a (fully implemented) framework, based on metamorphic testing, that will support the analysis of the information provided in OpenStreetMap with the goal of detecting faulty information.
Method: We defined a general metamorphic testing framework to deal with OpenStreetMap. We identified a set of good metamorphic relations. In order to have as much automation as possible, we paid special attention to the automatic selection of follow-up inputs because they are fundamental to diminish manual testing. In order to assess the usefulness of our framework, we applied it to analyze maps of four cities in different continents. The rationale is that we would be dealing with different problems created by different contributors.
Results: We obtained experimental evidence that shows the potential value of our framework. The application of our framework to the analysis of the chosen cities revealed errors in all of them and in all the considered categories.
Conclusion: The experiments showed the usefulness of our framework to identify potential issues in the information appearing in OpenStreetMap. Although our metamorphic relations are very helpful, future users of the framework might identify other relations to deal with specific situations not covered by our relations. Since we provide a general pattern to define metamorphic relations, it is relatively easy to extend the existing framework. In particular, since all our metamorphic relations are implemented and the code is freely available, users have a pattern to implement new relations
Cartographic Vandalism in the Era of Location-Based Games—The Case of OpenStreetMap and Pokémon GO
User-generated map data is increasingly used by the technology industry for background mapping, navigation and beyond. An example is the integration of OpenStreetMap (OSM) data in widely-used smartphone and web applications, such as Pokémon GO (PGO), a popular augmented reality smartphone game. As a result of OSM’s increased popularity, the worldwide audience that uses OSM through external applications is directly exposed to malicious edits which represent cartographic vandalism. Multiple reports of obscene and anti-semitic vandalism in OSM have surfaced in popular media over the years. These negative news related to cartographic vandalism undermine the credibility of collaboratively generated maps. Similarly, commercial map providers (e.g., Google Maps and Waze) are also prone to carto-vandalism through their crowdsourcing mechanism that they may use to keep their map products up-to-date. Using PGO as an example, this research analyzes harmful edits in OSM that originate from PGO players. More specifically, this paper analyzes the spatial, temporal and semantic characteristics of PGO carto-vandalism and discusses how the mapping community handles it. Our findings indicate that most harmful edits are quickly discovered and that the community becomes faster at detecting and fixing these harmful edits over time. Gaming related carto-vandalism in OSM was found to be a short-term, sporadic activity by individuals, whereas the task of fixing vandalism is persistently pursued by a dedicated user group within the OSM community. The characteristics of carto-vandalism identified in this research can be used to improve vandalism detection systems in the future
Collaboration or competition: The impact of incentive types on urban cycling
Bicycling is an important mode of transport for cities and many cities are interested in promoting its uptake by a larger portion of the population. Several cycling mobile applications primarily rely on competition as a motivation strategy for urban cyclists. Yet, collaboration may be equally useful to motivate and engage cyclists. The present research reports on an experiment comparing the impact of collaboration-based and competition-based rewards on users’ enjoyment, satisfaction, engagement with, and intention to cycle. It involved a total of 57 participants in three European cities: Münster (Germany), Castelló (Spain), and Valletta (Malta). Our results show participants from the study reporting higher enjoyment and engagement with cycling in the collaboration condition. However, we did not find a significant impact on the participants’ worldview when it comes to the intentions to start or increase cycling behavior. The results support the use of collaboration-based rewards in the design of game-based applications to promote urban cycling
Bridges and Barriers: An Exploration of Engagements of the Research Community with the OpenStreetMap Community
The academic community frequently engages with OpenStreetMap (OSM) as a data source and research subject, acknowledging its complex and contextual nature. However, existing literature rarely considers the position of academic research in relation to the OSM community. In this paper we explore the extent and nature of engagement between the academic research community and the larger communities in OSM. An analysis of OSM-related publications from 2016 to 2019 and seven interviews conducted with members of one research group engaged in OSM-related research are described. The literature analysis seeks to uncover general engagement patterns while the interviews are used to identify possible causal structures explaining how these patterns may emerge within the context of a specific research group. Results indicate that academic papers generally show few signs of engagement and adopt data-oriented perspectives on the OSM project and product. The interviews expose that more complex perspectives and deeper engagement exist within the research group to which the interviewees belong, e.g., engaging in OSM mapping and direct interactions based on specific points-of-contact in the OSM community. Several conclusions and recommendations emerge, most notably: that every engagement with OSM includes an interpretive act which must be acknowledged and that the academic community should act to triangulate its interpretation of the data and OSM community by diversifying their engagement. This could be achieved through channels such as more direct interactions and inviting members of the OSM community to participate in the design and evaluation of research projects and programmes
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