Questioning Big Data: Crowdsourcing crisis data towards an inclusive humanitarian response

Big Data and Society 3 (2) (2016)
  Copy   BIBTEX

Abstract

The aim of this paper is to critically explore whether crowdsourced Big Data enables an inclusive humanitarian response at times of crisis. We argue that all data, including Big Data, are socially constructed artefacts that reflect the contexts and processes of their creation. To support our argument, we qualitatively analysed the process of ‘Big Data making’ that occurred by way of crowdsourcing through open data platforms, in the context of two specific humanitarian crises, namely the 2010 earthquake in Haiti and the 2015 earthquake in Nepal. We show that the process of creating Big Data from local and global sources of knowledge entails the transformation of information as it moves from one distinct group of contributors to the next. The implication of this transformation is that locally based, affected people and often the original ‘crowd’ are excluded from the information flow, and from the interpretation process of crowdsourced crisis knowledge, as used by formal responding organizations, and are marginalized in their ability to benefit from Big Data in support of their own means. Our paper contributes a critical perspective to the debate on participatory Big Data, by explaining the process of in and exclusion during data making, towards more responsive humanitarian relief.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,672

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Data fusion with probabilistic conditional logic.Jens Fisseler & Imre Fehér - 2010 - Logic Journal of the IGPL 18 (4):488-507.
Data models and the acquisition and manipulation of data.Todd Harris - 2003 - Philosophy of Science 70 (5):1508-1517.
The ethics of medical data donation.Jenny Krutzinna & Luciano Floridi (eds.) - 2019 - Springer International Publishing.
Data politics.Didier Bigo, Engin Isin & Evelyn Ruppert - 2017 - Big Data and Society 4 (2).
Mental Models in Data Interpretation.Clark A. Chinn & William F. Brewer - 1996 - Philosophy of Science 63 (5):S211-S219.
Mental models in data interpretation.Clark A. Chinn & William F. Brewer - 1996 - Philosophy of Science 63 (3):219.

Analytics

Added to PP
2020-11-24

Downloads
13 (#1,031,809)

6 months
8 (#352,539)

Historical graph of downloads
How can I increase my downloads?