follow-up: Impact Data Lab in Amman

Having recently returned from a four-day workshop with Visualizing Impact and Columbia's Studio-X Amman, what follows are only a couple takeaways from a remarkable event and several remarkable individuals. I had the distinct pleasure of spending much of the workshop serving as a mentor and advisor to the five interdisciplinary design teams, working through a concentrated charrette to produce proofs of concept and prototype visualizations each pertaining to topics on human rights in Palestine. Although the topics ranged from education and gender to digital rights and historical mapping, the process and products (all of which were astounding and encouraging) raised a handful of questions worthy of reflection beyond the particularities of specific subject matter.

  Amman, from the  Darat Al Funun  gallery. 

Amman, from the Darat Al Funun gallery. 

On the many deployments of DataViz: Within academic research, the uses of data visualization are rather clearly delineated and our approaches to developing those visualizations are designed to fit each use. We visualize as a mode of analysis or as a means of communicating results. There are, of course, instances when those two uses are intertwined and cases when visualizations are applied to other ends after-the-fact, but rarely are the conflicts between intended uses so pronounced and the lines between them so blurred that we grapple with what (and how) the image—static, interactive, plugin, or platform—must do. During the last week, I was delighted (and challenged) to revisit these concerns which ranged from leveraging or questioning the seeming veracity of quantitative information and identifying the boundary between editorializing and storytelling. Almost every team seemed simultaneously tasked with developing outputs that "report" in a journalistic tone, act as tools for advocacy, educate or support education, operate as objects around which existing but disparate communities can gather or coalesce, actively intervene in discourses of conflict, and even create resources for capital-R Research. These are incredibly different aims implying almost impossibly different methodologies, some of which stand in direct conflict with the others, raising ethical concerns from multiple disciplines that often go without discussion or acknowledgement in DataViz circles. And this discussion—between what is possible, meaningful, strategic, responsible, and ethical; between which audiences, readers, users, and constituents are served by each—was difficult, necessary, and beautiful.

On the lack of data and its opportunities: Given the dearth of high-quality, publicly available information on some of our most challenging topics, the questions of how to "make do" with the information we have was a frequent point of discussion, even through the project presentations that concluded the workshop. Despite our grandest ambitions, sometimes it is worthwhile to remember a few preliminary points: (1) In working with data-poor regions and/or data-controlled topics, often simply creating and sharing a reliable and rigorously sourced data set constitutes a major contribution to both scholarly and activist work. (2) Don't apologize for what available data isn't. At a certain point, the interpretative caveats about a dataset outweigh whatever story one is trying to derive from it. Consider the data you have for what it is, and tell that story. (3) Sometimes, there is a meaningful story behind why data doesn't exist. And, we can be sure there's a powerful story to be told when it does exist but is either inaccessible or substantially unreliable.