Knowing salmon involves knowing data about salmon and its environment. These data are collected by management agencies, commercial fisheries, community data collectors, processors, and of course—university research programs—and, come in many forms such as brood tables (age composition data), escapement numbers, world trade prices, temperature profiles, etc… And, these data catalogue the salmon as measurable, countable, and capable of being managed. Data register not only “local changes in technology, personnel, and organization but also broader cultural rhythms and events” (Loukissas, 2016). Moreover, there is a temporal aspect to data: to the sustaining, transforming, and fitting data to current uses. Understanding ecological systems “requires an extended temporal perspective, and long-term data collection is a cornerstone of ecological knowledge” (Burton and Jackson 2012). This concern with a long-term perspective illustrates how phenomena might be hidden in the past and “reside in the invisible present” (Magnuson 1990. As such, data do not “speak for themselves”, but are made to speak by human and technological actors working together.
This work is an attempt to visualize the data transformations that occur in making data interoperable, reproducible, and commensurable.