The Bowe article we read this week discussed widespread excitement over the “Wash Your Lyrics” PSA project, suggesting that it “matched the virus in its virality, creating a world-wide network of conscientious hand-washers, singing in solidarity” (Bowe 8). The wonderful thing about many of the data visualizations available in the Bowe piece is that they gave their viewers a measure of control over the data or the circumstances of its presentation. Anyone could use the “Wash Your Lyrics” tool in order to create their own PSA. But the indication of this type of data visualization generated a network is particularly intriguing. As a type of data visualization, it is also a piece of media, and thus it has the capacity to inspire new trends and communities. This type of phenomenon has already been brought up by both Zack and Rei who discussed memes. Memes in general and specific types of memes are capable of generating communities of people who produce and consume them and are happy to be “in on the joke”. 

In a previous post-production post, I brought up the suggestion that all media might be community-produced. Inspired by both the “Wash Your Lyrics” case and the Miller piece on Social Networking Sites, which argues suggests that people are themselves social networking sites, I began to consider that all data is community-produced. At the very least, all data interpretation is community-produced. When we kept data journals about ourselves, we were inevitably tapping into networks and communities in order to access our data. At the most local and personal level, the grocery store spreadsheet keeping track of my household’s weekly expenses is affected by and affects my household of four people. Manipulation of these data points is actually a reflection of changes in a single person’s diet and decision-making. But the formation of the data and its interpretation must be understood as a communal task. As for the other data that people looked at–through Google, social networking sites, apps that recorded sleep, etc.–these trackers were community-produced, and thus inevitably the data is community-produced or can only be understood in the context of a community. A person can independently, with pen and paper and nothing else, choose to keep track of their sleeping schedule. However, the numbers they generate mean nothing without a community of other numbers to compare them to. Although it may have been obvious, the indication that both media and data are community-produced shows how deeply intertwined these sectors are with culture.