We’ve been experimenting with methods for visualizing some of the relationships embedded within the data we’ve collected for our 2024 State of Open Infrastructure report. Katherine Skinner, IOI’s Director of Programs and author of the section on governance, explored governance models and terminology, along with participation and overlap in representation in governance groups. She wondered, initially, if a noticeable number of individuals would hold multiple seats on governance groups, but in the end found fairly high diversity, with most individuals (90%) holding just one seat, and about 10% holding two or more seats.
A reader could inspect the dataset to see which individuals hold more than one seat, and with what open infrastructure governance groups, but we wanted to create a visual representation of that information. We did so by creating a two-mode network using gephi, a free and open source tool for creating network visualizations. Two-mode networks allow you to classify the entities represented in a network into categories – in this particular case, people and governance groups (blue and green nodes, respectively, in the network below). If you look closely, you’ll see nodes are proportional to the number of connections they have, and it’s pretty easy to see that arXiv, for example, has a lot of governance seats (29) relative to most other infrastructure communities in the graph (average of 10.5, minimum of 2). The variation in connectivity among the people in the graph is a little harder to see since we’re looking at a smaller range in the number of connections (just one to five), but see if you can spot some of the individuals who hold multiple governance seats, and the infrastructure communities with which they’re affiliated.
We will also be interested in applying this approach to looking at grant funding data, to visualize where funders have common interests, as we grow our dataset in 2025. Stay tuned!
NOTE: the app that generates the web version gives us no control over appearance, so what you see is pretty much what we get.