Infrastructure in the Wild: What Mapping in Post-Earthquake Nepal Reveals about Infrastructural Emergence
Open accessAbstract
Disasters and their impacts have unavoidable spatial characteristics. As such, maps are necessary and omnipresent features of the information landscapes that surround and support disaster response. Professional and volunteer GIS services are increasingly in demand to support map-based information visualization during crises. This paper investigates the work of mapmakers working on the response to the 2015 Nepal earthquakes. In comparison to prior events, we found significantly more collaboration and spatial data sharing took place between map producers working across humanitarian organizations and parts of the Nepal government. Collaboration between mapping practitioners was supported by a complex and emergent information infrastructure composed of social and technical elements, some of which were brought through experience with prior disaster events, and some which were shaped anew by the availability and acceptance of open data sources. Our research investigates these elements of the spatial information infrastructure in post-earthquake Nepal to consider infrastructural emergence.
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Information gathered in SAR is communicated through shared maps, which serve as a foundation for collaboration and planning.
“Information collected is communicated through maps [6,12] that are shared, forming the basis of collaboration and planning “we consult the map given to us by Incident Base, which outlines the search plan” [P7].”
From Mapping in the Wild: Toward Designing to Train Search & Rescue Planning (2018) · cites this paper as [12]
The Analysis section says maps provide a common picture that enables coordination in disaster response. “Means of Distribution: The Value of Paper Maps” describes shared paper maps guiding relief-planning discussions. The study concerns post-earthquake humanitarian relief in Nepal, however, and does not establish the claim specifically for search and rescue (SAR). Page numbers were not supplied in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measuredIn SAR cooperative work, planning and spatiotemporal skills are critical for success.
“In this complex cooperative work, planning and spatiotemporal skills are crucial to success [12,13], thus, responders constantly train to retain and enhance their knowledge and competence.”
From Mapping in the Wild: Toward Designing to Train Search & Rescue Planning (2018) · cites this paper as [12]
The Introduction (page unavailable) says disaster responders rely on contingency plans, skills, and expertise to accomplish their goals. The Analysis and Dependence on Personal and Professional Networks sections describe spatial-data work and collaboration in the Nepal earthquake response. The paper does not establish that planning and spatiotemporal skills are crucial specifically to search-and-rescue success. (LLM, conf=0.77)
Experimental — accuracy not yet measured
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Percentages, sums and reported differences re-computed from the paper’s own numbers.
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- Authors
- Soden, R., & Palen, L.
- Affiliations
- University of Colorado Boulder (US)
- Venue
- Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2016-05-07
- Pages
- 2796-2807
- OpenAlex
- W2394927023
- Cited by
- 59
- References
- 47
- Citations by year
- 2026: 7 · 2025: 5 · 2024: 9 · 2023: 4 · 2022: 6 · 2021: 7 · 2020: 4 · 2019: 6 · 2018: 7 · 2017: 3 · 2016: 1
- FWCI
- 27.07
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion, other-oa)
- Funders
- National Science Foundation (1441263, 0910586, and 1524806)
- Topics
- Social Sciences › Geography, Planning and Development › Geographic Information Systems Studies
- Social Sciences › Sociology and Political Science › Disaster Management and Resilience
- Social Sciences › Transportation › Earthquake and Disaster Impact Studies
- Keywords
- 2015 Nepal earthquake, spatial data infrastructure, mapmakers, spatial data sharing, collaboration, open data, post-disaster reconstruction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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