There’s been a lot of talk about the use of crowdsourcing to collect, filter and validate crisis information. As we continue to fine-tune methodologies to crowdsource crisis information, we should consider the next logical step: the crowdsourcing of crisis analysis, or collaborative analysis.
Crisis mapping platforms are typically designed with the end user in mind instead in mind instead of the “end network”. What’s been missing from the discourse is the need to embed social networking tools in crisis mapping platforms to encourage massive collaboration for real-time analysis by a network of end users. The field mathematics recently employed this approach to solve complex problems.
The Polymath Project “proved that many minds can work together to solve difficult mathematical problems” (Nature). Announced on a blog earlier this year, the defi was to prove the density Hales-Jewett theorem (DHJ) using “blogs and a wiki to mediate a fully open collaboration.” These Web 2.0 tools functioned as “a collective short-term working memory, a conversational commons for the rapid-fire exchange and improvement of ideas.”
Not surprisingly, the approach was “inspired by open-source enterprises such as Linux and Wikipedia,” which means, “anyone in the world could follow along and, if they wished, make a contribution.”
“The Polymath Project differed from traditional large-team collaborations in other parts of science and industry. In such collaborations, work is usually divided up in a static, hierarchical way. In the Polymath Project, everything was out in the open, so anybody could potentially contribute to any aspect. This allowed ideas to be explored from many different perspectives and allowed unanticipated connections to be made.”
The result? Within a few weeks, Polymath participants had collectively proven the DHJ theorem not once, but twice using different approaches. The user generated content on the project blogs and wiki reveal “how ideas grow, change, improve and are discarded, and how advances in understanding may come not in a single giant leap, but through the aggregation and refinement of many smaller insights.” On a side note, the question of authorship and credit was resolved by using the group pseudonym “DHJ Polymath” to represent all contributors.
One question that remains, however, “is whether the process can be scaled up to involve more contributors.” Participants believe this would require important changes to the collaborative process.
“One significant barrier to entry was the linear narrative style of the blog. This made it difficult for late entrants to identify problems to which their talents could be applied. There was also a natural fear that they might have missed an earlier discussion and that any contribution they made would be redundant.
In open-source software development, this difficulty is addressed in part by using issue-tracking software to organize development around ‘issues’ — typically, bug reports or feature requests — giving late entrants a natural starting point, limiting the background material that must be mastered, and breaking the discussion down into modules.”
Scientists engaged in the Polymath Project believe that the widespread adoption of these methods will lead to mass collaboration in many fields of science and thereby “will extend the limits of human problem-solving ability.”
This is precisely why Crisis Mappers should design platforms that encourage mass collaborative analysis to identify patterns in humanitarian crises. The next logical step will be to develop a taxonomy or library of crisis patterns based on the findings.