A Case Study of Crowdsourcing Imagery Coding in Natural Disasters Article Swipe
Crowdsourcing and open licensing allow more people to participate in research and humanitarian activities. Open data, such as geographic information shared through OpenStreetMap and image datasets from disasters, can be useful for disaster response and recovery work. This chapter shares a real-world case study of humanitarian-driven imagery analysis, using open-source crowdsourcing technology. Shared philosophies in open technologies and digital humanities, including remixing and the wisdom of the crowd, are reflected in this case study.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.31235/osf.io/bcgwf_v1
- https://osf.io/bcgwf_v1/download
- OA Status
- gold
- References
- 20
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4409670067Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.31235/osf.io/bcgwf_v1Digital Object Identifier
- Title
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A Case Study of Crowdsourcing Imagery Coding in Natural DisastersWork title
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preprintOpenAlex work type
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enPrimary language
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2017Year of publication
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2017-06-23Full publication date if available
- Authors
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Cobi CalyxList of authors in order
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https://doi.org/10.31235/osf.io/bcgwf_v1Publisher landing page
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https://osf.io/bcgwf_v1/downloadDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://osf.io/bcgwf_v1/downloadDirect OA link when available
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Crowdsourcing, Natural disaster, Natural (archaeology), Coding (social sciences), Computer science, Data science, Geography, Sociology, World Wide Web, Social science, Meteorology, ArchaeologyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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