Software projects, whether open source, proprietary, or a combination thereof, rarely exist in isolation. Rather, most projects build on a network of people and ideas from dozens, hundreds, or even thousands of other projects. Using the GitHub APIs it is possible to extract these relationships for millions of users and projects. In this paper we present a dataset of a large network of open source projects centered around Ruby on Rails. This dataset provides insight into the relationships between Ruby on Rails and an ecosystem involving 1116 projects. To facilitate understanding of this data in the context of relationships between projects, users, and their activities, it is provided as a graph database suitable for assessing network properties of the community and individuals within those communities and can be found at https://github.com/pridkett/gitminer-data-rails.

Past research established that individuals joining an Open Source community typically follow a socialization process called "the onion model": newcomers join a project by first contributing at the periphery through mailing list discussions and bug trackers and as they develop skill and reputation within the community they advance to central roles of contributing code and making design decisions. However, the modern Open Source landscape has fewer projects that operate independently and many projects under the umbrella of software ecosystems that bring together projects with common underlying components, technology, and social norms. Participants in such an ecosystems may be able to utilize a significant amount of transferrable knowledge when moving between projects in the ecosystem and, thereby, skip steps in the onion model. In this paper, we examine whether the onion model of joining and progressing in a standalone Open Source project still holds true in large project ecosystems and how the model might change in such settings.