 I'm S.J. Klein. I'm part of the Knowledge Futures Group, which is a new incubator for free knowledge and open publishing projects out of the MIT Media Lab and MIT Press. And we're interested in finding new ways that we can support other projects. But right now, we're five people who are mainly working on two products of our own. One is the underlay, which is a decentralized knowledge graph of things like authority files claims. And the other is pub pub, which some of you may have seen, which is a publishing platform for conversations around living documents. Pub pub is designed for publishing something that is intended to be in dialogue over a period of time. There are a few dozen journals and some long form books in the Constitution of Mexico City and a few other projects of that sort. And right now, it's being extended to something that can be embedded and used in a wider range of environments, especially books. Frankenbook was a book that it was a republishing of Frankenstein that came out last year. And then as a follow on a few months later, a number of professors who had been studying it over many iterations of the work shared conversations that they had with their students and some conversations of their own. And then our newest product is the underlay project, which is the idea of separating knowledge into knowledge graphs that distinguish underlays from overlays. You can have many different displays or ways of understanding and underlay, a collection of statements, and capturing detailed provenance for each of those statements. So if you have provenance 2.0 for sign apps in the near future, you can imagine all the ways you could expand provenance and take things like the prod standard and add more subtlety and nuance to it. And we're working with the whole-tail project, which is an effort to capture provenance that you would need to fully reproduce an experiment. And then the underlay project is the collection of public underlays. So with the protocols that allow anyone to make an underlay of their own, all the public overlays together form something like a knowledge graph, something like we used to have with Freebase. And we're designing some tools, templates, and a bot ecosystem, which will be some of the active substrate that people interact with when they contribute or announce statements. So let's say you wanted to build an authority file, and you have four or five different sources, like Orkin, who are building their own partial collections of author disambiguation. Instead of making yet another silo of author disambiguation, you can say, anyone who's interested, here are all the claims we know about. And here's where they came from. You can distinguish the ones that all came from the same source, but are showing up in different silos from ones that are new. We just had a workshop last week. So if you want to see some of the technical discussions from people who are there, we have a summary, and we have the full back and forth. But if you wanted to capture some author disambiguation, you start with Himmelsstein's paper, and maybe you really care about your following retraction watch, you realize that Daniel made some mistakes and his paper has been retracted. And most people don't know about it. First, you might look and see what all the components of the structure data that was in the article were. And then you might look at all the things that different bots had pulled out of the article. And some of them might have been looking for retraction claims on blocks. And they could say, well, there are some people who seem to say that this should be retracted. Here's the conversation. In the future, we're hoping that underlays will let us ask more interesting questions. These are kind of the questions we ask now of the bibliometrics we have. But at some point, you might want to ask, what are all the analogies to battle that anyone has ever made? And it's a hard question to answer completely, but you could ask everyone who studied this for some subset who came up with a partial collection. And you could have collections of battle analogs that you trusted more or less. And you could see, in as much detail as you wanted, all of the types of analogy that different researchers cared about.