If you’ve seen my talks about information overload and discovery then you may recognize the image above.¹ It’s borrowed from the Eigenfactor Mapping Science research done by Carl Bergstrom, Jevin West and Martin Rosvall. We’ve done some work with the Eignenfactor at SSRN and understand the benefits of applying eigenvectors to a large corpus of content and mapping the relationships between those pieces of content. In my talk, I share that one of the solutions to the information overabundance is a good map and a trusted recommendation.

There are a lot of maps out there and many more being created every day. Unfortunately, we are beginning to see an overabundance of maps. When I spoke with Jennifer Lin last week about the map in her talk at CrossRef’s 2015 Annual Meeting, I was a little skeptical. She outlined CrossRef’s efforts to collect data and create an “open map” of scholarly communication that would be navigable by both humans and machines. In the related blog post, Jennifer elaborates on the map, providing a better picture of the “infrastructure” that needs to be built and its benefits, including a very valid point about discovery being related to connectedness. 

I agree that connections are important and aggregating the data in a usable format (creating the map) will enhance the normal evolution of discovery. But, I believe there is a more Kuhnesque set of opportunities. The scholarly community and its associated data are not a 2D, or even 3D, map; we need to think multidimensionally to fully capture the complexity. Connecting the pins is important, but there are incredible (possibly revolutionary) opportunities for different disciplines to create different planes at their granular, community levels and then intersect those planes using Jennifer’s infrastructure. The infrastructure could change the way most people think about discovery. It may, by helping people navigate the enormous amount of connected material, also mitigate what Dan Kahan calls the scientific communication paradox – “persistence of divisive conflict in the face of compelling scientific evidence.”

SSRN supports openness (access, data, science). It is a critical element in this infrastructure. But openness is not the first, or only piece of the puzzle. In order for an open infrastructure of scholarship to be created, a critical mass of scholarly data must be made available. One of the points in my post on the STM’s Consultation on Article Sharing was the need for clear guidelines and consistency across publishers. If we are going to connect the pins, we need to be confident about what can be shared and that the points we are connecting aren’t going to disappear in the future. Significant contributions will be needed from large publishers to get to critical mass, and enough small publishers will need to contribute to add texture to the landscape.

I can imagine how an infrastructure of this magnitude might flourish, but I know a thousand minds will create a million possibilities. Jennifer’s blog post references metastructure, one of the revolutionary possibilities. Just as Uber is changing transportation and evolving the networks for a future of autonomous cars, through the creation of a transportation metastructure, a similar “phase transition, like the first signs of order forming around a seed of crystal” maybe, possibly, could be applied to scholarly communications. Now, THAT would be one heck of a map for us to build on!

¹ This image was originally published in D. Butler, Nature (2011) 476:18