01.2016 Using DG and social media to tell complex stories.

January 30, 2016. Using DebateGraph and social media to tell complex stories.

One of the challenges of telling a complex story, with many parts, like a natural or man-made disaster (or a really big, complex story, the story of the Anthropocene) is context. How can I provide detail and, at the same time, provide context over time, not just on the day that I file my report? The answer has been, until now, that this has not been possible. Each report on a particular story sits on a pile of other stories to which it cross-links and we have multiple piles sitting in the room.

Enter the map. What does the map do that the pile of stories does not? First, what is a map in this context. It is a way of representing knowledge in space, a knowledge map. So, what can it do? To say it uses space as its foundation for presenting knowledge and not time but time can be a component is true, but not perhaps helpful. So let's start with an example.

21st Century Challenges  is a map and this link: http://dgraph.org/aaov displays it in Outline View. Clearly there are a number of topics available, from air pollution to wildfires. Knowledge piles up on the map. So far so good. But what if we reverse the process? What if we wrote our article on air pollution in England *on the map* and then tweeted it using the Share menu? What would that accomplish? The key is in the word "it" in the previous sentence. What are we tweeting? We are tweeting a location. If I find the article at a newspaper website, I am tweeting: "Here is an article I found at this newspapers' website." Clicking through gives me no sense of context. Tweeting an article already on a map says: "Here is an article I found on Anthropocene Impacts > Population Growth > Planet Earth > Pollution > Air Pollution (England) and cross-linked to Planet Earth > People > Public Health."  This is implicit in the tweet, of course, not explicit and it's something we find only after clicking through. But once we have we can instantly see the landscape of the knowledge environment in which the tweet/article lies.

It is just a few clicks up to Population Growth and then down the Climate Change branch. In this way we have provided an entry-point with our tweet to an ordered collection of stories which are interesting and useful in themselves but also for the patterns they reveal and for the speed with which they can be investigated. Speed is important because with speed comes faster processing; in fact what we are doing with a DebateGraph map is putting the maps we try to build in our heads on the computer screen, freeing up our own thinking for a higher order of thinking; systems thinking. 

The fact that the maps themselves can be linked together provides for even more dizzying levels of mapmaking, ordermaking and sensemaking around these collected stories.

Going the other way, one exciting component of this approach is that the articles can be broken down and expanded almost infinitum. A story which mentions in passing a new chemical process can link to an article about that chemical process, this sub-article now available to other articles through cross-linking and so on.

Shortlink: dgraph.org/DGcomplexstories

edited, May, 2016.

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