Sensor journalism

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Sensor journalism [1] refers to the use of sensors to generate or collect data, then analyzing, visualizing, or using the data to support journalistic inquiry. This is related to but distinct from data journalism. Whereas data journalism relies on using historical or existing data, sensor journalism involves the creation of data with sensor tools. This also includes drone journalism. [2] [3]

Contents

Background

Examples of sensor-based journalism (below) date back to the early 2000s [4] and usually involve the use of sensor tools to generate or collect data to be reported on. The way in which the sensors are deployed varies. In some cases, a journalist will learn how to operate and deploy a sensor (see Houston Chronicle) while in others (see WNYC Cicada Tracker), the sensors are built and deployed by the general public. Journalists can also request data from existing sensor networks (see Sun Sentinel example) and remote sensors (see ProPublica example). [5]

Sensors used for reporting can be closed source with expressly stated terms of use or open source, which allows for modification of the sensor downstream of development. [6]

Sensor journalism modules have been taught at Emerson College [7] (around water quality/contamination) and Florida International University (around sea level rise). [8] [9] [10] [11] An air quality sensor journalism module is slated for spring of 2015 at San Diego State University [12]

Examples

A study about toxic chemicals in the air in public parks.
A series that looked at lead-contaminated soil in neighborhoods around previous U.S. lead factories.
A series about the tendencies of cops to speed.
A project that revolved around the emergence of Magicicada.
A project with 300 acoustic sensors across 20 square miles in D.C.
A project that followed the production of a shirt from beginning to end.
A study of sea-level rise in Louisiana.

Tools and platforms

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References

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