We blended a number of different techniques to facilitate our exploration of the data story behind Food for Free’s mission. In contrast to the paradigm of “start with the data, finish with a story” that is described by the Data Journalism Handbook, we started the design process for our data mural by listening to Sasha Purpura, Executive Director of Food for Free, talk about the ethos and mission behind Food for Free, and the impact that the organization has had thus far in the local community. By listening to her first-hand account of the story behind “Food for Free”, we seeded our data exploration with a big picture idea of how Food for Free operates and its role in addressing a well-defined and critical piece of the broader issue of Food Security.
After that, we jumped into a few collaborative design exercises to openly explore the available data and hone the data story that we are directly expressing through our data mural. First, we employed a framework to develop data stories through identifying interesting factoids/outliers within the data, examining surprising correlations and interactions between different data points, analyzing how the data changes over time, revealing comparisons within the data, and also leveraging what we know about our local community to infuse the data story with personal experiences. These techniques are very similar to those described in the Data Journalism Handbook for developing context for data stories.
As a class, we discussed the individual data stories that emerged from our exploration, and developed visual designs through a group drawing exercise. Similar to some of the design strategies highlighted by Segel & Heer in their framework for narrative data visualization, we eventually developed a cohesive design to visually structure the data story, and highlighting specific motifs and patterns within the data itself. Since our data mural fits within the author-driven genre of narrative visualization, it provides a visual metaphor telling a focused story about Food for Free. It differs from many of the the case studies presented by Segel & Heer since it lacks the aspects of interactivity and transition that are typically present in data visualizations presented with a more reader-driven perspective.