Making Sense of a Complex World
Complexity is a word often used to describe many facets of our current state of affairs. Technological development has increased the available amount of transactions in the world, broadened the scope of applications, and made up-front-and-center to people enormous amounts and structures of information. At the epicenter of the fairly recent rapid rise in data transactions is no doubt: the web. The internet has unquestionably altered the way society receives and communicates information, engages in social dynamics, and how institutions interact, internally as well as with other organizations. This technology has opened everyone to a new, and ever-expanding environment; an environment that is saturated with complexity and information. But with the proper tools and a thoughtful approach this complexity can yield unparalleled assistance and reveal previously unknown insights. As businesses and institutions learn to cope with and mine vast databanks, many fail to effectively proceed to the next steps: inference and communication. As humans are primarily visual learners and adept at pattern recognition, data visualization techniques are an effective method for abstracting key insights in the sea of statistical data. The objective is to bring to the foreground the relevant information to a particular problem. For visual communication, this task is the combination of two primary variables: asking the right questions, and identifying the right information. Through this process, institutions can more effectively translate through visual diagrams the key insights that are important for their constituents to understand. With more clear and appropriate understanding, organizations can isolate areas of leverage, and engender action within their operation.
Before data can be managed, one needs to understand the scope of elements pertinent to a problem and how these elements interact. Within the ecosystem of everyday experiences, the scale of this information can often be far too large to appropriately analyze. Mindmapping is a technique to visually outline information(1) by diagramming different nodes of information, their structures, and relationships to other components. For very large problems, however, even these diagrams can be overwhelming. Nevertheless, Eric Berlow, an ecologist and network scientist, argues that by isolating on only one link of influence, it is actually less predictable than stepping back, embracing the entire system, and honing in the sphere of influence that matters most. In their research, he states, “that’s often very local to the node you care about within one or two degrees. So the more you step back, embrace complexity, the better chance you have of finding simple answers, and it’s often different than the simple answer you started with.” (2). By focusing on these two or three degrees of influence, one can construct a problem at manageable scale, and identify the data of greatest leverage to investigate.
From here, data visualization software can be used to generate informative graphics that illustrate information in patterns that can incorporate more complex structures, such as context. Data Journalist, David McCandless, points out that, “all of us now are being blasted by information design. It’s being poured into our eyes through the Web, and we’re all visualizers now; we’re all demanding a visual aspect to our information”(3). We can assume this pattern to continue as more of us are raised in a world of digital displays that are ever present in the environment. By utilizing the vast databanks of information made available by network technology, through thoughtful and appropriately scaled investigation, we can better analyze our current conditions, and translate these insights for effective action.
Software Sources for Mind-mapping and Data Visualizations: