Data Collection through Local Involvement in the Development Context

DEBUNKING MYTHS

HoseaAlfayo.jpg

The initial hype surrounding crowd-sensing, citizen science or more generally, data collection through local involvement seems to have somewhat ebbed recently. While today's technology advances provide plenty of novel opportunities to develop and integrate non-traditional data into decision-making, the main reason for this is that crowd-sensing campaigns are often chronically riddled with a number of significant problems. These can ultimately prevent achieving the planned goals in a targeted, cost-effective and sustainable manner over the long-run.     

With it's global footprint, the iMoMo Project has accumulated a large expertise for crowd-sensing water-related data in the development context. Here, we present key learnings from the multi-year project. The focus is on institutional and cultural aspects and not on technology. Understanding properly these boundary conditions can help guiding interested stakeholders in the design and implementation of future field campaigns.

THE LIMITS OF ALTRUISM

Self-Reported Data versus Purposeful Data Collection Through Local Involvement

INSTITUTIONS MATTER

Weak versus Strong Actors

THERE IS NO FREE LUNCH

Accounting for the Costs of Non-traditional Data Collection

THE VALORIZATION OF DATA

Key Prerequisite for Continued Data Collection