Constructing global data: Automated techniques in ecological monitoring, precaution and reification of risk
Automatic aggregation of large-scale data is increasingly conceived as central in the production of ecological knowledge. This article examines the implications of the employment of automation techniques and ‘data-driven analysis’ in long-term biodiversity monitoring. What are the pathways and parad...
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Online Access: | https://doi.org/10.1177/2053951718779407 |
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doaj-dd69fe89c96e44398f6b732dd4963e902020-11-25T03:55:52ZengSAGE PublishingBig Data & Society2053-95172018-05-01510.1177/2053951718779407Constructing global data: Automated techniques in ecological monitoring, precaution and reification of riskNaveen ThayyilAutomatic aggregation of large-scale data is increasingly conceived as central in the production of ecological knowledge. This article examines the implications of the employment of automation techniques and ‘data-driven analysis’ in long-term biodiversity monitoring. What are the pathways and paradoxes in the possible public acceptance of automated data-sets as a trustworthy source for use in global protection and regulation of biodiversity? This article suggests that the precautionary discourse aid topdown measures for the public acceptability of the use of such techniques. Automated biodiversity monitoring offers distinctive advantages to further precautionary goals in terms of a faster, cost-effective and less messy way of collecting data, at a large scale over long periods of time. However, it contradicts other values implied through precaution – for instance the opacity and reification of the construction of risk. How do the specific forms of data-making relate with specific forms of risk governance, and what implications does this have for helping us to understand appropriate ways of political representation in governance? Can paradoxes attendant to introducing a form of construction of data help understand the nature of the exercise of governmental power? This article is a part of special theme on Data Associations. To see a full list of all articles in this special theme, please click here: http://journals.sagepub.com/page/bds/collections/data-associations .https://doi.org/10.1177/2053951718779407 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Naveen Thayyil |
spellingShingle |
Naveen Thayyil Constructing global data: Automated techniques in ecological monitoring, precaution and reification of risk Big Data & Society |
author_facet |
Naveen Thayyil |
author_sort |
Naveen Thayyil |
title |
Constructing global data: Automated techniques in ecological monitoring, precaution and reification of risk |
title_short |
Constructing global data: Automated techniques in ecological monitoring, precaution and reification of risk |
title_full |
Constructing global data: Automated techniques in ecological monitoring, precaution and reification of risk |
title_fullStr |
Constructing global data: Automated techniques in ecological monitoring, precaution and reification of risk |
title_full_unstemmed |
Constructing global data: Automated techniques in ecological monitoring, precaution and reification of risk |
title_sort |
constructing global data: automated techniques in ecological monitoring, precaution and reification of risk |
publisher |
SAGE Publishing |
series |
Big Data & Society |
issn |
2053-9517 |
publishDate |
2018-05-01 |
description |
Automatic aggregation of large-scale data is increasingly conceived as central in the production of ecological knowledge. This article examines the implications of the employment of automation techniques and ‘data-driven analysis’ in long-term biodiversity monitoring. What are the pathways and paradoxes in the possible public acceptance of automated data-sets as a trustworthy source for use in global protection and regulation of biodiversity? This article suggests that the precautionary discourse aid topdown measures for the public acceptability of the use of such techniques. Automated biodiversity monitoring offers distinctive advantages to further precautionary goals in terms of a faster, cost-effective and less messy way of collecting data, at a large scale over long periods of time. However, it contradicts other values implied through precaution – for instance the opacity and reification of the construction of risk. How do the specific forms of data-making relate with specific forms of risk governance, and what implications does this have for helping us to understand appropriate ways of political representation in governance? Can paradoxes attendant to introducing a form of construction of data help understand the nature of the exercise of governmental power? This article is a part of special theme on Data Associations. To see a full list of all articles in this special theme, please click here: http://journals.sagepub.com/page/bds/collections/data-associations . |
url |
https://doi.org/10.1177/2053951718779407 |
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