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Methodology for crowdsourcing water quality data
  • This report documents the theoretical background that is being used to pilot the concept of crowdsourcing water quality data. It explores the theory of change, citizen science and crowdsourcing, and provides a short overview of water quality indicator selection as well as an outline for conducting a crowdsourced water quality study.
  • The  methodology  proposed  herein  combines  empowerment  of  the  public  through  participation in  the  scientific  process  (citizen  science)  with  modern  technologies  to  collect,  gather,  and disseminate data (crowdsourcing).
Supported Use Cases

Collect in-Field Data

The full methodology on how to involve different actors when designing and integrating a crowdsourcing solution for collecting in-field data on water quality.

Very detailed document - straight forward to implementing it.

Related CM functions

Crowdsourcing

Motivate participation

What to consider when motivating citizens in science projects: a process model

Related CM functions

A process model of citizen volunteers’ and scientists’ motivations in citizen science projects

Crowdsourcing project design considerations

When pursuing a crowdsourcing project, it is advised to consider social design, technical design,
and program design from the outset (Hutchings et al. 2012). The text lists the important
components to consider, potential barriers restricting long-term sustainability of the project, and
actions to take for each design element.

Related CM functions

Addressed hazards
Innovation stage
Readiness
Crisis Cycle Phase
Crisis size
Illustrations
Handbook
Crowdsourcing - conceptual framework

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