The Crowd is the Territory: Assessing Quality in Peer-Produced Spatial Data During Disasters

Anderson, Tony; Soden, Robert; Keegan, Brian; Palen, Leysia; Anderson, Kenneth M.

doi:10.1080/10447318.2018.1427828

Cited by 28 publications

(29 citation statements)

References 40 publications

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“…Finally, some recent papers ( [24,25]) studied content bias in crowd-sourced geographic information in OpenStreetMap, depending on the country and the culture. Another work presented a similar study during disasters ( [26]). It is difficult to know if there are deviations of this nature in the data we obtained from Instagram.…”

Section: Limitationsmentioning

confidence: 86%

Using Entropy of Social Media Location Data for the Detection of Crowd Dynamics Anomalies

et al. 2018

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Evidence of something unusual happening in urban areas can be collected from different data sources, such as police officers, cameras, or specialized physical infrastructures. In this paper, we propose using geotagged posts on location-based social networks (LBSNs) to detect crowd dynamics anomalies automatically as evidence of a potential unusual event. To this end, we use the Instagram API media/search endpoint to collect the location of the pictures posted by Instagram users in a given area periodically. The collected locations are summarized by their centroid. The novelty of our work relies on using the entropy of the sequence of centroid locations in order to detect abnormal patterns in the city. The proposal is tested on a data set collected from Instagram during seven months in New York City and validated with another data set from Manchester. The results have also been compared with an alternative approach, a training phase plus a ranking of outliers. The main conclusion is that the entropy algorithm succeeds inn finding abnormal events without the need for a training phase, being able to dynamically adapt to changes in crowd behavior.

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Section: Limitationsmentioning

confidence: 86%

Using Entropy of Social Media Location Data for the Detection of Crowd Dynamics Anomalies

et al. 2018

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“…Objects are edited at all frequencies, but quarterly snapshots give a finer resolution of the evolution of the map while still making global-scale analysis computationally efficient. We use the open-source Javascript framework tile-reduce (github.com/Mapbox/tile-reduce) to efficiently process these historical vector tilesets, following the same methodology as previous work by Anderson et al [15].…”

Section: Methodsmentioning

confidence: 99%

“…In addition to systemic barriers, researchers have also highlighted that the global political landscape has significant impact on contributors and consequently, on the data produced [31][32][33][34][35][36]. The response of the OSM community has been notable in the wake humanitarian crises [15,16]. In particular, HOT mobilizes and coordinates global mapping events in response to disasters, including Typhoon Yolanda (2013), The Ebola Crisis (2014), and the Nepal Earthquake (2015), to name just a few.…”

Section: Introductionmentioning

confidence: 99%

Corporate Editors in the Evolving Landscape of OpenStreetMap

Anderson

Sarkar

Palen

2019

IJGI

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OpenStreetMap (OSM), the largest Volunteered Geographic Information project in the world, is characterized both by its map as well as the active community of the millions of mappers who produce it. The discourse about participation in the OSM community largely focuses on the motivations for why members contribute map data and the resulting data quality. Recently, large corporations including Apple, Microsoft, and Facebook have been hiring editors to contribute to the OSM database. In this article, we explore the influence these corporate editors are having on the map by first considering the history of corporate involvement in the community and then analyzing historical quarterly-snapshot OSM-QA-Tiles to show where and what these corporate editors are mapping. Cumulatively, millions of corporate edits have a global footprint, but corporations vary in geographic reach, edit types, and quantity. While corporations currently have a major impact on road networks, non-corporate mappers edit more buildings and points-of-interest: representing the majority of all edits, on average. Since corporate editing represents the latest stage in the evolution of corporate involvement, we raise questions about how the OSM community—and researchers—might proceed as corporate editing grows and evolves as a mechanism for expanding the map for multiple uses.

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“…Williams, et al [81] found that the engagement strategies developed around the open data collection process became just as important as the resulting data it produced. Engagement strategies involving voting [82], quality assessments against other features in the dataset [83] and identifying "good" contributors [84] have been proposed as measures for improving OSM data quality. Without active contributors, a geospatial dataset will quickly degenerate.…”

Section: Collaboratively Contributed Open Geospatial Datamentioning

confidence: 99%

Open Geospatial Software and Data: A Review of the Current State and A Perspective into the Future

Coetzee

Ivánová

Mitášová

et al. 2020

IJGI

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All over the world, organizations are increasingly considering the adoption of open source software and open data. In the geospatial domain, this is no different, and the last few decades have seen significant advances in this regard. We review the current state of open source geospatial software, focusing on the Open Source Geospatial Foundation (OSGeo) software ecosystem and its communities, as well as three kinds of open geospatial data (collaboratively contributed, authoritative and scientific). The current state confirms that openness has changed the way in which geospatial data are collected, processed, analyzed, and visualized. A perspective on future developments, informed by responses from professionals in key organizations in the global geospatial community, suggests that open source geospatial software and open geospatial data are likely to have an even more profound impact in the future.

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The Crowd is the Territory: Assessing Quality in Peer-Produced Spatial Data During Disasters

Cited by 28 publications

References 40 publications

Using Entropy of Social Media Location Data for the Detection of Crowd Dynamics Anomalies

Using Entropy of Social Media Location Data for the Detection of Crowd Dynamics Anomalies

Corporate Editors in the Evolving Landscape of OpenStreetMap

Open Geospatial Software and Data: A Review of the Current State and A Perspective into the Future

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