Modelling growth of urban crowd-sourced information

Quattrone, Giovanni; Mashhadi, Afra; Quercia, Daniele; Smith-Clarke, Chris; Capra, Licia

doi:10.1145/2556195.2556244

Cited by 14 publications

(8 citation statements)

References 35 publications

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“…This interest in unequal geographies inspired a broad range of research on OSM which cast light on inequalities in its production of geographic knowledge on the global (Glasze & Perkins, 2015;Graham & De Sabbata, 2015;Neis et al, 2013) and urban scale (Ballatore & De Sabbata, 2020;Bittner, 2014Bittner, , 2017Quattrone et al, 2014). Scholars also subjected the notion of participation and the concept of ''the crowd'' in OSM (Bittner et al, 2016;Neis & Zipf, 2012;Turk, 2020), alongside the gendered division of participation and representation therein (Gardner et al, 2019;Stephens, 2013), to critical examination.…”

Section: Unequal Geographies Of Knowledge Productionmentioning

confidence: 99%

De/colonizing OpenStreetMap? Local mappers, humanitarian and commercial actors and the changing modes of collaborative mapping

et al. 2021

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In its early days, the geodata and mapping project OpenStreetMap (OSM) was widely celebrated for opening up and “democratizing” the production of geographic knowledge. However, critical research highlights that the new socio-technical practices of collaborative mapping often also produce or reproduce patterns of exclusion, not least in the area of relative data density between the Global South and North. These findings notwithstanding, we consider it important to acknowledge the increasing number of contributions of geodata from regions outside the old European core of OSM. This expansion of geodata production in OSM is related to a diversification of OSM actors and socio-technical practices. While OSM has often been described as a crowd-based project bringing together thousands of individual craft mappers, our analysis of OSM metadata indicates new institutional actors are gaining relevance. These developments have not only resulted in new collaborations but also conflicts between local mapping communities and institutional actors. We interpret these processes in two ways. First, the expansion of mapping activities can be viewed as a decolonizing process, whereby quantitative differences in data density between the Global North and South are partly reduced and new groups of local mappers are empowered to produce geographic knowledge. Second, these new developments can also be understood as colonizing processes. The engagement of large commercial actors in OSM raises concerns that the project (and its local mappers) could be used as a new means of data extraction and that in particular new and diverse voices in the OSM community are marginalized by a fixation on economically exploitable, modernistic and universalistic epistemologies. However, this supposedly clear distinction should not obscure the fact that colonizing and decolonizing processes intertwine in complex ways.

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Section: Unequal Geographies Of Knowledge Productionmentioning

confidence: 99%

De/colonizing OpenStreetMap? Local mappers, humanitarian and commercial actors and the changing modes of collaborative mapping

et al. 2021

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“…Harvey argues that there is a significant difference in contributions provided in an automated versus manual way. Quattrone et al [15] present a model that attempts to leverage the characterists of urban-based crowdsourcing in order to describe its digital evolution over time. The authors conclude that "digital mapping of spatial urban information is governed by complex dynamics".…”

Section: Related Work and Applicationsmentioning

confidence: 99%

Exploring Data Model Relations in OpenStreetMap

Pruvost

Mooney

2017

Future Internet

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Abstract:The OpenStreetMap (OSM) geographic data model has three principal object types: nodes (points), ways (polygons and polylines), and relations (logical grouping of all three object types to express real-world geographical relationships). While there has been very significant analysis of OSM over the past decade or so, very little research attention has been given to OSM relations. In this paper, we provide an exploratory overview of relations in OSM for four European cities. In this exploration, we undertake analysis of relations to assess their complexity, composition and flexibility within the OSM data model. We show that some of the patterns discovered by researchers related to OSM nodes and ways also exist in relations. We find some other interesting aspects of relations which we believe can act as a catalyst for a more sustained future research effort on relations in OSM. These aspects include: the potential influence of bulk imports of geographical data to OSM, tagging of relations, and contribution patterns of edits to OSM relations.

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“…Quality control mechanism similar to those employed in crowdsourcing (i.e., majority consensus is used to maintain Wikimapia data [70]) as well as use of heuristics (e.g., POI data entry of a café in the middle of a historic park tend to be erroneous [70]) should not be present is also used to assure its data accuracy However, its coverage still falls behind that of other official dataset, especially in rural areas and in countries where OpenStreetMap is less popular [133]. This geographic data coverage bias is common in VGI [74,124,145]. In chapter 6, we investigate the quality and quantity of data collected via our remote data collection methods to see if our volunteer-based methods are viable for collecting geographical information about street-level accessibility.…”

Section: Volunteered Geographic Informationmentioning

confidence: 99%

Scalable methods to collect and visualize sidewalk accessibility data for people with mobility impairments

Hara

2015

SIGACCESS Access. Comput.

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Poorly maintained sidewalks pose considerable accessibility challenges for people with mobility impairments. Despite comprehensive civil rights legislation of Americans with Disabilities Act, many city streets and sidewalks in the U.S. remain inaccessible.The problem is not just that sidewalk accessibility fundamentally affects where and how people travel in cities, but also that there are few, if any, mechanisms to determine accessible areas of a city a priori.To address this problem, my Ph.D. dissertation introduces and evaluates new scalable methods for collecting data about street-level accessibility using a combination of crowdsourcing, automated methods, and Google Street View (GSV). My dissertation has four research threads. First, we conduct a formative interview study to establish a better understanding of how people with mobility impairments currently assess accessibility in the built environment and the role of emerging location-based technologies therein. The study uncovers the existing methods for assessing accessibility of physical environment and identify useful features of future assistive technologies. Second, we develop and evaluate scalable crowdsourced accessibility data collection methods. We show that paid crowd workers recruited from an online labor marketplace can find and label accessibility attributes in GSV with accuracy of 81%. This accuracy improves to 93% with quality control mechanisms such as majority vote. Third, we design a system that combines crowdsourcing and automated methods to increase data collection efficiency. Our work shows that by combining crowdsourcing and automated methods, we can increase data collection efficiency by 13% without sacrificing accuracy. Fourth, we develop and deploy a web tool that lets volunteers to help us collect the street-level accessibility data from Washington, D.C.As of writing this dissertation, we have collected the accessibility data from 20% of the streets in D.C. We conduct a preliminary evaluation on how the said web tool is used.Finally, we implement proof-of-concept accessibility-aware applications with accessibility data collected with the help of volunteers.My dissertation contributes to the accessibility, computer science, and HCI communities by: (i) extending the knowledge of how people with mobility impairments interact with technology to navigate in cities; (ii) introducing the first work that demonstrates that GSV is a viable source for learning about the accessibility of the physical world; (iii) introducing the first method that combines crowdsourcing and automated methods to remotely collect accessibility information; (iv) deploying interactive web tools that allow volunteers to help populate the largest dataset about street-level accessibility of the world; and (v) demonstrating accessibility-aware applications that empower people with mobility impairments.

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Modelling growth of urban crowd-sourced information

Cited by 14 publications

References 35 publications

De/colonizing OpenStreetMap? Local mappers, humanitarian and commercial actors and the changing modes of collaborative mapping

De/colonizing OpenStreetMap? Local mappers, humanitarian and commercial actors and the changing modes of collaborative mapping

Exploring Data Model Relations in OpenStreetMap

Scalable methods to collect and visualize sidewalk accessibility data for people with mobility impairments

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