Some months ago, I and some of my colleagues at the LII began to release a series of white papers that were written as part of the construction of a (mostly) comprehensive metadata model for Federal legislation. They are appearing as a series of blog posts in this blog. One which seemed more appropriate for VoxPopuLII — it had to do with metadata quality concerns that are not limited to legislation — was posted there yesterday. We’ll continue to adapt the white papers as blog posts and release them as Metasausage posts, but we thought that it was high time that we released full documentation of the model. Many of you have known of its existence for a while; we’ve been slow to release it because, well, we’re just overwhelmed with work.
The model is Linked-Data-friendly and designed to be highly extensible. We think it could serve as a reference model (by which I think I really mean “extensible scaffolding”) for a much more comprehensive metadata model for Federal legislation. As you’ll see when you read the documentation, we made no attempt to model things where we lacked domain expertise (appropriations and reconciliation being two), nor did we try to deal with the finer points of House and Senate rules when modeling process.
We’ll be interested in your reactions to it, and very, very interested in taking it further. Over the next month or so, we’ll actually build out what we’ve already put in the Open Metadata Registry into a full Linked Data representation online. Our hope is that this is a very big stone that can be used to make some Stone Soup.
The model was primarily done by myself, Diane Hillmann, John Joergensen, and Jon Phipps; other contributors included Sara Frug, Wayne Weibel, Dave Shetland, and Rob Richards. We had a lot of help from many of you, as well.
I suspect that there may be some glitsches in the documentation itself, because as most of you probably know e-book compilation software is twitchy and it wouldn’t surprise me if different versions have a range of ugly formatting problems. Let me know and we’ll clean ’em up. Most of all, we’re interested in knowing what you think of the model.