These documents serve as the canonical ground-truth description of the project. We intend to use them to both describe the current state of the project and how it can be used, as well as to outline our larger vision for the work and what we hope to accomplish. Writing outside of these documents should be assumed to be helpful context, but may be out of date or deprecated. These docs are the single source of ground-truth about the state of the project that can be assumed to be up-to-date and presently relevant.
What is Underlay?
At its simplest, Underlay is public infrastruture that makes it easier and more valuable to publish open datasets. It provides a neutral space for people and organizations to publish datasets such that they are actually used. More about this value proposition is discussed here.
At its most grandiose, Underlay is public infrastructure that establishes a network of curated datasets that undergird a radically more effective, equitable, and sustainable web of public data.
Our first step in building towards that vision is a central underlay.org platform. We intend to use this platform to establish the features and social practices that we intend to scale to federated and local-first tooling.
While there are significant technical elements to the project, we are heavily focused on the social and cultural requirements that must be addressed in order for public, collaborative data to flourish. As such, we strive to prioritize simple and accessible design patterns that can be understood and used by many, rather than complex technical patterns that may provide higher customization or efficiency but require deep expertise.
Why is this work important?
Knowledge is often exchanged in formats optimized for computers, and then used to render webpages, maps, diagrams, tables and text for human consumption. It is also used directly by machines to navigate vehicles, trade stocks, control appliances, design structures, formulate scientific hypotheses, order search results, and much more. But today, most of these machine-readable data sources are privately held and controlled, and the ones that do exist publicly are fragmented and don’t work well with each other. Indeed, at the moment it seems the only way to leverage the power of a large dataset is to control it privately and implement business operations around staffing its maintenance and usage for the purpose of private benefit. The goal of the Underlay is to improve the way that public data is created, curated, and used such that it can be shared and used for public benefit.