¶ 1 Leave a comment on paragraph 1 0 There is an art to perfecting a visualization. No formula will tell you what to do in every situation, but by following these steps (1. Pick your data, 2. Pick your visualization type, 3. Pick your graphic variables, 4. Follow basic design principles), the visualizations you create will be effective and informative. Combining this with the lessons elsewhere in this book regarding text, network, and other analyses should form the groundwork for producing effective digital history projects.
¶ 2 Leave a comment on paragraph 2 0 As with every lesson in this book, this is chapter is only a starting point. There is a rich and growing literature on information visualization. Colin Ware’s Information Visualization (2012) is a phenomenal textbook for beginning to think about visualization in terms of cognitive science and human perception. Edward Tufte’s oeuvre is useful for his insights into effective, efficient, and aesthetically sensible approaches to visualizing data, especially his books The Visual Display of Quantitative Information (1983) and Envisioning Information (1990). Katy Börner’s recent book Visual Insights (2014) provides a good point of entry into the practice of making visualizations yourself. Elijah Meeks, one of the prime movers behind the Stanford ORBIS project, has written a handbook to creating visualizations using the d3.js framework. D3.js is beyond the remit of our book, but if you are looking to create ‘data driven documents’ that can be integrated into interactive websites, D3.js in Action (2014) is well worth considering.
¶ 3 Leave a comment on paragraph 3 0 Recently, visualization as an interpretive, historical, and humanistic practice has enjoyed some scrutiny and prominence. Daston and Galison’s recent tome, Objectivity (2010), explores the history of objectivity as a concept in the sciences, paying special attention to the role of visualizations in constructing scientific objects. Johanna Drucker’s work focuses both on the creation of humanities-inflected visualizations and on the theory of visualizations as interpretive objects, especially in her recent book Graphesis (2014). Of particular importance to digital historians is the visualization of missing and uncertain data: a hot topic at recent digital humanities conferences.
¶ 4 Leave a comment on paragraph 4 0 In recent years, one particular kind of visualization – the network diagram – has risen to prominence. Partly this is a function of the metaphors of the ‘internet’ and ‘world wide web’ rising to such dominance, but it is also a function of a great deal of research into the statistical properties of networks. Allied with this research was the need to develop ways to present this research. Over the last decade, the technical difficulties of representing networks with more than a few hundred nodes have dropped as computing power and memory have ramped up; but crucially, the software used to measure and visualize networks has become more user friendly. The downside to this is that there have been many analyses and visualizations that have used the tools and metaphors of network analysis without any real appreciation of the dangers and limitations.
¶ 5 Leave a comment on paragraph 5 0 The network, as metaphor, is ubiquitous in historical research. The formal analysis and use of network methods will be an incredible boon to historians, adding nuance and precision to an already important metaphor. We turn to network analysis and visualization in our final two chapters, in the hopes that we can foster better network analyses and visualizations in the humanities.