 Chen, thank you all so much for coming. You're here today for a Q&A about the Collections as Data part to whole cohort to CFP, Funding Opportunity and Cohort Development Opportunity. I'm Thomas Padilla. My colleague, Lori Allen, is with us here today. Prior to this project, Lori was the co-principal investigator on a project called Always Already Computational Collections as Data. She's a team member on this project. And I believe she is now headed to the Library of Congress to join the awesome folks at LC Labs. So thank you, Lori, for being here today to answer questions as well. So a couple of weeks ago, Hannah Skates-Kettler and I delivered a webinar in which we introduced this project. And then we answered some questions there. And Krista and the fine folks at Clear also suggested that we should have just like an additional paired Q&A webinar. So this is the hour that is dedicated to just you asking us. Lori and I have many questions as you want to ask. And I guess to kick things off, yeah, instructions. OK, so it looks like Krista is saying, if you have any questions, go ahead and put them into the chat. And then we'll be responding to those there. So I think that's probably enough to get us started. I don't know, Lori, do you think, am I missing anything? No, I think that you said the things. Let's just see where the questions take us. Thank you. Cool. There is actually already a question. Is there? Yes. Where is it? It's in the Q&A thing. Oh, and now Krista's put it in here. We're forming our team here and are excited about the potential opportunity. In your experience, what are some important things to consider in order to form the best or most productive cross-disciplinaria or cross-institutional team? I'm thinking more voices could be helpful, but also not helpful in other ways. Do you want to take it or do it me too? That seems like a nice, easy one. I think you should take that one. Thank you, Thomas, easing me back in. So a couple of things about the team that come to mind. One is that in terms of the project funding, the project supports three people to come to the cohort development meetings. That is the project lead, the disciplinary scholar, and the administrator, basically the institutional administrator. Those three roles are funded to come. As far as we know, almost all the teams are way bigger than that. And if folks want to use their own funding to come, they can. But the project funds for those three. So I think it's really important to make sure that those three roles are filled and filled productively in ways with people who really want to be involved in the project, since they'll be the folks who are really getting the most out of this cohort opportunity. I think if you saw the last webinar, they certainly said this a lot of times. And if you read the CFP, you can see it again. We're really interested in developing capacity in institutions for the ongoing support of the use of collections as data. So we're really, when forming a collaborative group, whether it's interinstitutional or interdepartmental or interdisciplinary, I think all of those are necessary. But I think focusing on how will this expand capacity? Will people learn in ways that they will then be supported in continuing to take what they learn from this project into their job, into the work that they do? Is it will it become part of what the institution now supports? And those so I think building the team, I think thinking about the goals for the institution is sort of like and making sure that the team includes people whose continued participation will expand the capacity of the institution. Thomas, how's that? I think that was really good. I would just add, in terms of important things to consider, I think obviously one of the really important things to consider is just that the various people that are coming from different parts of the organization or as you mentioned here from a different discipline, that they're open to learning and that they're comfortable with a bit of uncertainty in their work together, and then in combination that you think sort of strategically about who that senior administrator is going to be that's on your team, right? Because we've all been involved in projects where, say, we're comfortable with uncertainty and we're really interested in doing a thing, but then we have no administrative power to actually do the things that we want to do beyond our unit or beyond our particular part of a library or an archive or a museum. So concretely, that bears on who's going to be your senior administrator in your project and can they help you sort of clear paths to doing the work that you propose to do? Yeah, and Thomas, the next question is to ask to talk a little bit more about the senior administrative person's responsibilities. Yeah, I mean, do you want to pick that up? Sure, I think I'm just going to echo what Thomas said. I think when we looked at proposals and we're absolutely open about who it is, but I would say the further up, because institutions are different sizes and different scales, but the further up the organizational chain you go, I think the stronger we felt it would be, in part because in the experience of the people on this, in our experience with the last project, learning about how organizations do collections of data across the board. We just kept seeing that people were empowered to take risks or move across organizations for a little project. And really one of the reasons to have a senior administrator on this project is so that someone is really deeply considering what are the ramifications of this kind of work over the long term for institutional resources. So a lot of the reason that we want a senior administrator there is partially to clear paths for this project, but the money is also there to clear paths for this project. It's really to think about what are we learning in this project about the way that our institution allocates resources and supports staff development, such that going forward, we can take those lessons into further kinds of jobs. And so I think the senior administrator's role is absolutely to support the work of the project team and to participate in that work, but it's also really to take seriously the learning opportunity for what does this mean about when library staff or a museum or archival cultural heritage organization staff work across departments, what's heard about that. So we don't want, in some cases it's a department head, but ideally we want someone who's gonna be able to see across departments or divisional silos and see who maybe doesn't, yeah, that. So what their role is kind of depends, but the reason we feel like that's really important is because it seems like it's often much easier to do a collections as data project than it is to change the work of the institution so that it supports this as something that the institution always does. And we want someone in the room who's in a position and whose job it is to think about that. There are other questions. I feel like this is for, you know, I think specific questions are fine, presumably you guys, yeah. Like, or general, or big, small, medium size. Hi, this is Krista. We have a new question in the Q&A pod and I'll type that over into the chat just so everybody can see it. Oh, great. Yeah, Thomas, why don't you take that one, if you're willing. As it is not nice and easy. Okay, yeah, so it is in the, it's in the chat now. So let me just take a sec to read it. So I guess my first reaction is that I don't know. I always tend to work on projects with a lot of cooks. So I guess I come out on the end, but it's mostly a good thing. So I would say that that's good. I don't see it as detracting from the project to have two disciplinary scholars, one immediate studies and one in data science without knowing more about the project or the proposed work. I, you know, arguably it could be essential to have a combination of something like data science and something else, you know, especially given that in the projects that we're seeking to support, there is a really heavy emphasis on supporting work that is ethically grounded and that speaks to underrepresented histories. So I think you would need, or it would be advantageous to have a domain perspective as well. Oh, Lori, what would you say? That sounded great. Okay. Oh, we will read the question for the benefit of the recording. Oh, okay. Yeah, thank you. I think Thomas kind of, he spoke to the content of it in the answer. I mean, I think I'm just sort of to reiterate while we wait for the next question. I think we are, I think maybe too many cooks, maybe not depends on the cooks, but as Thomas said, arguably that's all necessary. I think what, you know, we absolutely want to see the development of collections as data. And so sometimes it's hard to get things done when there's a million people making decisions altogether. But even, you know, as important as producing collections as data is producing knowledge, like shareable, reusable knowledge about how these kinds of collaborations work or don't work or can be made to work for providing services around new uses of collections as data for roles that develop for how technically libraries or archives or museums make collections as data available and maintain their availability. So those processes and collaborations are every bit as important. So if you can make a case, I think that having more people will build stronger knowledge of the good practices, even if it might slow the process down of creating collections as data, it certainly is something we would be open to. So we have a suggestion to talk about other questions that we've been getting while we're waiting for new questions. And I have one fresh on my mind and it relates to sort of like a component of the CFP where we set up expectations for making the collections as data that you work with accessible or openly accessible. So I guess from like, and so we received a question of like, what if we have like sensitive data or what if we have data for which it may not be appropriate to release the product beyond certain communities, say in the case of like indigenous data? Of course we're gonna make, of course we're gonna make an exception for that. You know, we're open, very open to any and all arguments in that space. It's not like a de facto make it all open. We don't wanna be those people. And then the second component is, what if our data has, like it's in copyright or it has particular legal restrictions around it. And to that end, yeah, I mean, I think that there are cases to be made and techniques to be pursued to work in that particular space. And I'm thinking of things like, what's it called, like JSTOR, Data for Research or various kinds of like socio-technical workarounds that various entities have come up with to, if the data is in copyright, they can still come up with ways to share viable data out of the data that can't be used for research. So I think that there's like additional work to happen in that space with additional kinds of content. And it would be great to say things like that. Laurie, what about you? Do you have any? I'm just thinking of things about like, media types, multimodal, multimedia collections as data as a question that's come up. And it's absolutely yes, we're all about it. I think the first cohort has fewer, while there's different approaches taken to the collections as data, in most cases the collections are primarily text. And so it would be great to see some proposals that include non-textual or audio, visual, video or other kinds of data. We haven't, we didn't, so yes to that, that's one that came up that we can just easy answer. Yes, please. And again, with a copyright, like yeah, which given that that content often has richer copyright restrictions, we're totally, I mean, very open to seeing what proposals come forward. I think we'd be really interested in some that have creative ways of obeying the law and still making materials and still making good scholarship available, data available. What are other questions we've gotten? We've had questions about whether or not there can be team members from multiple institutions. And the answer to that is yes. I know, I feel like that's an easy answer. Yep, yep. Like if we would accept a proposal from multiple institutions or joining together, like yes, yes we would. Maybe some things I think I would wanna know. Last time around we got, I think we think we got 20 proposals, all of them were great in a way that was like pretty difficult. And I think we certainly are getting more interest earlier this time. We were looking for a cohort that made, where we felt like the people in the cohort could learn from one another in addition to all of the things in the CFP. So we did revise the CFP this time based on what we saw last time. And so I think it's more reflective of what we felt like we were looking for. And almost most of the people, I would say last time, most of the people who, not most, like half the people who applied had done a phone call with one or more members of the team to talk through their proposal before they submitted it. And we were open to that. I mean, I think one of the reasons for these is to get some of those questions answered. What other Q and A's? The gray line, what should be, ah, talk about please that gray line between what should be done and presented in the proposal versus what should be completed as part of a successful project. Great question. What should be? So, okay. I'm gonna give it a shot, Thomas. Okay. I remember having a conversation with someone who worked at a granting agency about before we went to Mellon for this. And they talked about how amazing it was, the idea of re-granting and how amazing it was to see that in some cases, the act of writing a proposal, even when it didn't get funded, was enough to get an institution to have all the kinds of conversations that they needed to have. And then in some cases, they could self fund a project and the thing that they needed was actually just to get the right people sitting in a room making a plan together. And I think that's really appealing. Like, you know, that was one of the things that's exciting about this is that we are getting all these institutions to think through what would it mean for our institution to try to tackle this project. The money part needs to be helpful. Like, so we did see proposals where we were like, this is amazing. We really, really, really hope that they can do this. And it's not clear that they can't just do this. Like, if, you know, that this institution can't just make this thing happen. So the gray area, I think, where you need the money for, like, we really want to learn how to do two weeks of intensive work on this thing that we just don't have, our staff simply don't have time for unless we, you know, like, bring in an expert to whatever or unless we send them to some learning experience or yeah, I mean, I guess the proposal should be a commitment to actually growing over the year or the 18 months of being part of the cohort. I don't know if that really answers that. Thomas, can you better? I don't know about better. Maybe just like, maybe like a little, like an addition. So I don't know. I mean, this has kind of taken me back to like some workshops that I took when I was at Michigan State about, like how to get external funding. And I think there was a part of it. It was really simple. And it was Bill Hart Davidson who at Michigan State using the writing and rhetoric department, which, you know, who would know that someone who is a professor of rhetoric could help you construct a compelling argument. But one of the things that he said was that, you know, one of the most important parts of the application is to, you know, just try and evidence that you have the right people in the room to do the thing, that you have some grounding in the work that you propose to do, and that it appears that you can do that thing. So I think that's actually pretty, it's pretty straightforward. It's like, you know, here's my team, here's our context, here's the thing that we wanna do. This is why it's needed, and this is how we propose to do it. Yeah, Erin, maybe if you wanna say more about the question, I feel like what Thomas just said is like totally right on, like, I will say that, you know, we had, I've had a related question recently come in about this CFP where it was kind of similar to your question, but like flipped a little bit. It was like, can we seek funding for an ongoing project? So like the project was, the project they were proposing to seek funding for was kind of established, and then they wanted to know if they could seek funding to continue to build upon an established project. And the answer to that is yes. At the same time, it's like, we also wanna help people start things. So I don't think it's necessarily required that you have like, you know, two, three, five years of development on a project. So she says, in particular, I was interested in the model development, which we would like to do in part as part of the project where I should say they said, I mean, we are super interested in the model development as an outcome of the project. It's truly like we, everywhere we talk about the three things that we want to come out of each of these and two of them are models, and one of them is a collection as data and that is on purpose. And the inflection of all of those with reimagining the ways that libraries and archives and museums can be ethical participants in the world, like that's the thing, that's the project. So yes, we are super interested in model development. How can this be made to work as every bit as important as producing a collection as data? And that's why this project exists. It's yes, collections as data, but we already know collections as data is possible. The question is how can institutions organize themselves to support the use? And we don't, and we think it's hard. And so we're providing funding for lots of institutions to try it in lots of ways. So if your proposal is all about that with yes, here's a collections as data that we're gonna do. And the part that's important is the reason that there's that collections as data has to be there is actually because we really want to see institutional practices connected to real questions, real that are coming that are connected to communities, scholars, scholarship so that they're made for use basically for real uses. Okay, so the next question is maybe you could talk a bit about what you hope the cohort will learn from one another and whether there are any applicants, any ways applicants have successfully signaled their willingness to actively engage with the cohort in the way they build their proposals. So I'll take a first shot at this. I'm sure Lori has a lot of thoughts too, but yeah, I mean, we're, so okay, I'm gonna try and make this like not too long, too long-winded of an answer, but I will say that there was a point in proposal development for us as a project team in which there was a question about whether or not in terms of seeking funding, we should seek funding to support in a significant way one institution advancing collections as data work. And the feeling among the project team based on what we learned in the IMLS project was that we could really use increased diversification of exploration in this space and further development in this space that reflected the range of realities that we all work in, the different kinds of organizational sizes, the different communities that we're trying to serve, the different kinds of content. And so we very intentionally chose to pursue a re-granting program in order to support a bunch of different kinds of institutions in the creation of models that other institutions could learn from and potentially adapt to their particular context. So it's a favoring of particular solutions over universal solutions, right? And so when we think about the cohort, like that's a really important part of it, right? Because we don't see there as being like one answer of how to do this thing. We wanna bring together groups of people with lots of different answers in the hopes that they can learn different things from each other based upon the context that they're working in. So perhaps a large institution couldn't, you know, totally emulate some of the cool things that a smaller institution does, but perhaps nonetheless there's something that they can learn from that smaller institution and sort of like vice versa. I don't think to the second part of the question, I don't know that in any of our proposals that the applicants signal their intention to participate in the cohort, although anecdotally we do gather that people in the current cohort are enjoying it very much and find it to be valuable. We intentionally have, so basically it's like funds are made available in January of the new year and then within a couple of months we bring you all together as a cohort for professional development activity intentionally toward the beginning of your project so that knowledge exchange happens toward the beginning rather at the middle or toward the end so that there is the opportunity to learn from that interaction with the rest of the cohort. Laurie, what would you add? Oh, just about the cohort part. So I don't think we, I don't know what to say about how to signal or how people have signaled that they're interested. I mean, we did a lot of trying to figure out, trying to build the first cohort such that we would be sure that everybody would be able to learn something from someone and be able to teach something to someone. So maybe someone was there because that was something we looked for and will I think I hope continue to look for among really just a bunch of extraordinarily strong proposals. I think in terms of the timing we know that you have to get so specific in the development of the proposal so having the first cohort meet, as Thomas said, a little early but not so early that you haven't actually started working. Like the idea is like you should have, you had this plan, you made it, you put it in the summer or the early fall and then in January the money comes and you're supposed to start doing it and so we wanted that cohort time to be a time when you've started working on it so you've begun to hit reality and that's the time to come together and say okay, where we had our proposal, everybody signed up for this thing, now we're starting to do it, what can we learn from each other now? And then, so I don't know, I think, yeah, maybe I guess just being reflective about what are you a model of? Are you a model of a large institution working in a particular discipline? Are you a model of a small museum working in, it's just a different, it's just understanding, helping us understand who will best learn from you and how you think you'll learn from others would probably help. I think it's a really great point, just like encouraging you to be, because the intention is to support the development of these models, that you're pretty self-reflexive in thinking about what is particular about your organization and then that that shows in your documentation of your model, so that you're actually creating sort of clear pathways into your work and how other people could learn from it. So the next question from Liz Neely, I missed the first webinar, so I'm sorry if this is duplicative, do you define disciplinary scholar broadly? I guess I'm asking how specific of a discipline? I see a range and cohort one, some setting, something specific, others more about research practice. Yeah, so we do define it pretty broadly. Pretty broadly. And we're open to arguments in that space and we'll respond accordingly. Part of the intention of having the disciplinary scholar in that team of three is to speak to the disciplinary value or the research or pedagogical value of the data that are produced in the course of your project. And also to some extent about the resonance of the particular services that you're aiming to develop in terms of how they will support the use of the data. Laurie, what do you think? Nope, same thing. I think what Thomas said, yes. Someone needs to, someone who knows in a different way about the topic, needs to want the data for something real. And other than that, I don't think we're super, the disciplinary scholar as a term might be a little misleading, but yes, we want someone who, and this is the Mellon Foundation and they're, but yeah, we want it to be for use. We want someone who really cares about this topic to continue to stay involved and care about how it's contained. Yeah, are these services going to work for the people who want this collections as data? That's it. What other questions have we run into, Laurie? That one about, I feel like a bunch of people asked us, like where should the administrator be? But we've answered that. Interdisciplinary, I think we did a better job. I'm thinking last time, because I remember hearing more questions last time. And last time we got the question over and over again, it really seems like your proposal is about libraries. And that has to do with our own accidental, we all work in libraries, but we mean archives and museums too. But I think the fact that the cohort that we funded for round one sort of helps clear that up a little bit. We have gotten in various forums questions that touch upon the contingent labor issue. So do you want to speak to that? Sure. So yes, we've said that we don't want to fund contingent labor. We don't want to fund a term position. And the tricky part is trying not to fund graduate students to do the work. We love graduate students. We want graduate students to get funding. Absolutely. I will just speak for myself in saying, I don't think that, I think having graduate students do new, cool projects and not having institutional staff who are there over the long term, get a chance to learn those skills, get a chance to where all they're doing is managing a graduate student in the doing of this cool thing. I don't think that's a way that libraries grow or institutions grow. And so we really, we are open to the occasional graduate funding opportunity, but we want the projects to help the institution change and putting institutional change in on the backs of contingent staff is unfair and ineffective. And it's unfair to the contingent staff and it's unfair to the long-term staff who are not given an opportunity to do cool things. So we really are interested in creative ways of using money that isn't about hiring someone to do the cool thing while we keep doing the things that we think are really important. Because if you, because we want to see collections as data, I'm just speaking for myself. This is just my, I'm, I bet Thomas was like, Lori, do the thing. But yeah, I think we want to see how can institutions change people's full-time jobs to do the work that they believe is important as an institution. How can they learn to do new things that are hard to learn, that take time, that take different kinds of collaborations, that take people from different parts of the institution working together in new ways. And can we provide funding that makes space for those kinds of collaborations to grow and the new roles to emerge in a way that isn't just about bring on someone to make something cool and then we'll have it. So the contingent staff is something that people ask about a lot. It's such an obvious way to spend grant money. And it's harder to think of ways to spend grant money that aren't about hiring students. And again, it doesn't mean that we won't support the hiring of students, but we would be super interested in a proposal that hired students to do some of the work so that a staff member could go get trained for a while or work a little slower. We don't wanna exploit graduate students or undergraduates at all. We also want projects that are gonna build capacity inside the organization. Yeah, so just to add to that a little bit, you'll notice that in the CFP around each of the deliverables, the ending parenthetical is basically make this thing sustainable, right? And just exactly what to Lori said, we're really interested in seeing models and approaches to this work that are sustainable past the life of the grant funding. Like external funding is not an ever-flowing tap as we all know, right? For most institutions, maybe for some of us, we have a different situation, but we really wanna see how can you use this project as an opportunity to make it possible for more of you to do the work that you wanna do? So in case it's helpful, do you get many other questions about budgets? What's good to include? What's definitely not to include, et cetera? Mellon doesn't pay for digitization. Yeah. That's just Mellon. Mellon doesn't pay for, what do they call them? You can't buy stuff. You can't buy equipment, really. Yeah. You can buy food, you can buy food. This was actually... What is it that university overhead Mellon doesn't pay for? Yeah, there's no overhead. Yeah, I mean, it's pretty straightforward in the CFP. I think everything that Lori just said, it's like, yeah, you can't use it on stuff, can't use money to buy equipment, no digitization. And very hopefully for some of us, no overhead, right? Yeah. I think a couple people did ask about, right, what about more people, different people using the funds for the cohort stuff? I think I answered that at the beginning. I mean, the first go round, honestly, we had a much larger range. The first cohort, we said 30 to 80,000, which was our mistake that everyone asked for the maximum amount of money and then we had to spend a lot of time reducing everyone's budgets. So this time we did it. So last time, I wish they'd asked more questions. This time, we just said 50,000 because that's actually, right? Yeah, I think, yeah, that's right. Just thinking about the budget thing, it would be, we did try to encourage for some proposals more funding allocated to professional development, right? So if it seemed like most of, I don't know, the development work was being kind of shifted off to one person that was sort of contingent, we might encourage, hey, maybe other people on the team, it would be a good use of the budget to create some development opportunities for them. You said everything I could imagine saying about this. Oh, thanks, Chad. Could you speak about what details you would like to see included for the use model and the implementation model? We haven't seen these yet, but like I would like to see job descriptions, like what jobs we're going to exist as a result of this project. There's gonna be like someone's job is going to change and that's one that I'm really hoping for is like new and also new teams, like we are going to have a workflow that where a request comes in here and it goes to write to the metadata specialists and then it goes to a developer and then to back to the, I'm just making up, but that sort of specificity eventually would be really cool. Like, oh, this question comes in, we need to subset this giant proprietary data, whatever, and this will be the workflow and it involves these technologies and these kinds of expertise. That I think are hard to come by in institutions currently. Thomas, what else? Yeah, I mean, I think this is kind of like one of those questions where we can kind of, where we tend to kind of turn it back to you, right? So if you're thinking self-reflexively about your organization and the work that you're proposing to do, what is the collection of things and documentation that would make it easy for another institution to understand what you did and then possibly for them to adopt some of what you've done in their context. So I think that, like Lori said, that could be like job descriptions. It could be within that like percentages of time. It could be combinations of different roles. It could be workflows on the implementation side. It could be code. It could be documentation by your infrastructure. It could be a bunch of different things. Yeah, I don't know. What were you saying, Lori? Oh, it's just like a thought. No, obviously it'd be nodding with my mouth. Yeah, so in a way it's kind of like whatever you think would be most clear and useful for your colleagues. Maybe it's like you have a charter within your library that explains how you work together on whatever, but it is definitely the model part is definitely tied to like, how does this become ongoing work and especially the support of linking but also of using for collections as data. Yeah. And like, yeah, figuring out what 12 models, implementation models and 12 use models look like is that's what we're about, which is to say we don't know. Cool, I'm glad that helped. No problem. What other questions? Thomas, should we end our call? Should we end our call? I don't know, I want more questions, but I don't want us to. Yeah, I'm just trying to think if there's like anything else. I think, so it's not a question as much as like, okay. Yes. So this is from maybe Liz Neely. Yeah. Are you open to ideas being run past you? Yes, throughout the process. So you can either use the form that's on the website, that'll reach all of us. My email is there, you can email me directly. So we're open, we're open at all times. I'm gonna mention because I probably have not changed it everywhere. I will put, yeah, my pen email address no longer works. So I'll have to change that on the form. Yeah. Yeah, we kind of think that. Liz serves, sorry. That's a reminder I should have sent to him differently. So would it be helpful to describe the other changes you made in the call based on your cohort one experience? Sure. So this is a nice segue, because this was just something that I was just gonna start saying, even though it wasn't a question. Yeah, so some things that we changed based on the cohort one experience. One of the things that we've tried to be clear about in the cohort two CFP is basically like what we expect around the collections is data use model, right? So based on kind of like reflecting on the experience of the cohort one CFP and the response to that, I think the way that we wrote the CFP kind of like aligned with some familiarity or comfort that some of our institutions have with the concept of collections as data. And the idea that we have these collections, we can make machine actionable collections for example. And so we got a lot of proposals that were like, this is how we propose to make collections as data. And we didn't see as much that other like 50% of it, other 40% of it, which is like, and now that we made them, what is our model for sustainably supporting the use of these data, right? So one of the things that we really tried to do in the cohort two CFP was make that a little bit more clear, right? So stepping before this project in the IMLS project, that was really focused on that like, how do you describe, produce and provide access to collections as data? A big part, a primary part of why this project exists is because we wanted to explore what happens when the other foot drops, right? So it's like, okay, we made the collections available and it's like, but now what? How can we support the use of these things? What opportunities do they create for collaboration with our colleagues in teaching and learning and special collections and archives in institutional repositories and to really prompt the community to think about that and now what, like how do we support the use of the stuff? So we've tried to be more clear about that. We've tried to be more clear about what we mean by models, mostly by including parentheticals with examples of things like job descriptions and things like that. It's still kind of in admittedly an ambiguous space. I don't know, Lori, what else? I mean, practically speaking, just like, disclosure-wise, we made the CFP much more obvious, like the parts of the proposals now line up to the ways we'll be evaluating proposals. So in the last one, there was like, we want a proposal with these sections and then it was like, and we'll be evaluating it according to these criteria and the sections and the criteria didn't line up so that for each criteria, there wasn't like an obvious section, which what that meant is that we had these 20 proposals where we would just be sitting in a room being like, where's the part where this place talked about how they're gonna meet this criteria? And it was the selecting the cohort felt like we were trying as hard as we possibly could to do it in the fairest possible way and it was really hard. So we've tightened now, like, here is what we want in the proposal and here are the criteria that we're using to evaluate and it will be easier for us to see, oh, we need to see it does this place do, do they meet this criteria for evaluation or how well do they, we know where to look in the proposal and that was, for me, it sounds so minor, but as like a learning thing, like, oh, wow, I see why they do that when they've got a lot of proposals. It's really, it just felt like we were drowning in these brilliant ideas and it was hard to suss out. It just required a huge amount of work. So that's one thing, just direct change we made is that the proposals are a lot more clear where the criteria line up with the proposal. The money changed because the range was way too big. Everybody asked for the maximum. Yep, doing a lot better job. Thanks, Chad. Doing a lot better job describing what the models are and what we mean by use. I don't, yeah. I think we tried to, in the revision, we also tried to emphasize more, oh, am I frozen? No, you're there. Okay, yeah. We tried to emphasize more, like the central importance of sort of like the ethical dimensions at the proposed work and that we are looking for you to evidence that and document it very well. And I said this during the Q and A in the last webinar, but if the ethical dimensions of your work are not addressed or they are not addressed in a proposal, it will make it probably not possible for us to fund, right? So it'll be really, it's essential. Gotta do it, have to address it. And also like the whole marginalized sort of, yes, it is. And I think, I'm sorry, Thomas, I totally cut you off, but with you, it was a thing in the first call, we ended up being drawn to proposals that were, and we had put it in the call, but it wasn't as clear. Like, no, this is super important to us. We really are gonna prioritize funding, collections as data that change the representation scales in libraries, archives and museums in ways that are just, I mean, we're not only gonna do that, but it matters. Yeah. Yeah, you know, it's like, I mean, from, you know, I think we want to support you know, the production of collections as data, the use of collections as data. And you know, within that sort of frame, you know, things like machine learning or AI or computer vision become exciting, but we want to be sure that the proposed work isn't sort of like emulating some of the very public, you know, harmful misuses of these technologies that we're seeing coming out of the private sector. Sorry, that's kind of like a bummer, like last comment. I'm glad you said it, I'm glad you brought it up. Yeah. It's important. Well, thank you. Well, thank you. We think so too. Oh, good. Great. So happy to hear that. People are liking it if you don't see the chats. Yeah, yeah, I can see it. No problem. Wonderful. I'm so glad. Okay, so it looks like we're set to wrap up then. Yeah. Okay, cool. Well, thanks everyone. Thank you so much. If you have any additional questions, like I said, on the collections as data part to whole website, there is a form where you can reach all of us at once. My direct email is there if you wanna email me. You can reach out to us throughout the process. Like Lori said, many of the people who proposed in the last cohort did seek us out directly and did have conversations with us. Of course, that's not us trying to set the expectation that you need to like talk with all of us. You know, I'm sure you're really busy. But just to say that we are available and we're happy to chat with you about your ideas as you consider development. So with that, I guess we'll close. All right, thanks Lori. Thanks everybody. Thanks Thomas. Thanks everybody. Bye. Bye.