Sensors are devices that are proliferating in environments; and their purpose is to generate reams of data about environmental conditions. From air quality sensors, to light, temperature and humidity sensors, technologies are now available for monitoring environmental fluctuations and for producing data that might inform environmental action. Yet the basic diagram of technical sensors monitoring environments and producing data that has subsequent effects turns out to be less singular when operating in concrete conditions. The data generated through air quality sensors might then be referred to as “creatures,” in the sense specified by Alfred North Whitehead, where “concrete facts” assume distinct forms. For Whitehead, creatures are the actual entities and occasions that participate in the world in particular ways, but which also signal toward abstract processes whereby creatures come into being.
Air quality data may appear to be stable facts in the moment of collection. Yet these facts-as-creatures in their particular forms also have the potential to animate new relations and practices. An air quality sensor such as the Grove Dust Sensor from Seeedstudio uses the Shinyei Model PPD42NS Particle Sensor to measure and disclose particulate-matter levels by counting concentrations or densities of dust within an established unit of time. Yet how does the signal of particulate-matter concentrations to electrical currents to digital data, as an initial “disclosure” of particulate matter, transform into analysis and eventual reintegration toward having effects on the world?
What becomes apparent when working with environmental sensors such as air quality sensors in situ is that the data generated do not circulate as absolute and immediate indicators of the “fact” of air quality, but instead always require further analysis, as well as consideration of the environments of relevance in which these citizen-collected data might have particular effects. This is one of the trajectories informing the Citizen Sense project (www.citizensense.net), which undertakes a study of environmental sensors and citizen-sensing projects to understand how the data gathered from DIY sensors might concretely facilitate, change, or re-route practices of environmental citizenship.
This is another way of saying that data, whether institutionally or individually gathered, require extensive infrastructures for making sense of and acting on data. A single particulate-matter reading, or a line graph analyzing particulate-matter changes over time, then, must be put to work in particular contexts in order to effect change. By attending to the creatures of data, the particular forms of concrete facts and their potential to generate new encounters become more apparent. Data-as-creatures, in this sense, might be seen to generate particular environmental practices and material-political worlds. Practices of gathering evidence related to air quality might then shift from an exclusive focus on “facts,” to the concrete creatures and worlds generated through environmental monitoring with sensors.