 All right. Well, welcome back everyone. I hope you had a good break and I am delighted to introduce our last session for today. This is a look at the costs of making public access to research data, a reality, which is something that now is increasingly a requirement for various funders. We have a wonderful set of speakers and I'm going to turn this over to Cynthia Hudson Vitale from ARL, who has done just a wonderful job of sort of pulling this whole thing together and organizing it, and invite her to actually introduce everybody and take it away. All right. Thank you, Cliff. And thank you for inviting us here to talk about our work on institutional expenses for public access to research data. So my name is Cynthia Hudson Vitale, as Cliff said, and I am the director of scholars and scholarship within the Association of Research Libraries. Joining me today are Christie Keane, who is the assistant director of post-award support services at the University of Chicago. Melissa Corf, who is the director of grants and contracts with Harvard Medical School. And Wendy Kalsowski, who is the data curation specialist at Cornell University Library. Jim Luther, the interim research compliance officer at Yale University, and Shauna Taylor project manager for the realities of academic data sharing initiative with the Association of Research Libraries. So just to cover a quick overview of today's agenda, I'm going to quickly provide some background and contact setting that will hopefully ground these presentations that each organization is going to speak on. So they will report out on each of their organization's current and collaborative work and initiatives, followed by a brief poll about audience, audience interests and needs for research data, and we will wrap up with a facilitated discussion, hopefully we can fit all that in there in 60 minutes. Please feel free to pop your questions into the chat and we'll get to those at the end, or follow up after the presentation. To jumping right in, you know, public access to research data has existed in some form for quite a while now. This isn't obviously an exhaustive timeline, but more key dates that have had broad impact throughout higher education. One of the most critical points was in 2003 when NIH released their data sharing policy for grants and awards that were greater than $500,000. This was followed in 2011 by NSF releasing a directorate wide policy for the sharing of research data for all awards. And I'm going to go back to what I mean and what has become widely known as the Holder in Memo. OSTP asked all federal agencies with over 100 million in research and development expenditures to develop plans to support increased public access to results of funded research, inclusive of peer reviewed manuscripts and articles and research data. And the federal agencies subject to the Memo are in compliance, and even some below that that kind of threshold that was initially set on the horizon, and after many years of public feedback and engagement NIH is new data management, or data sharing policy will go into effect in January of 2023. I strongly believe that this new policy is prompting a renewed interest and costs of costs and expenses. So, to address these policies and points of compliance, many institutions have purchased or developed technology or built workflows and services. This obviously is drawn upon expertise distributed throughout the academic institution, including campus IT, university libraries, research offices, research computing, the individual faculty lab or office and elsewhere. Like other operations and academic institutions distributing services allows stakeholders to bring their skills and abilities, while also dispersing the labor of the research activities that go into making data publicly accessible. It is a fact, I feel that the distributed nature of these services kind of complicates understanding the full expenses that factor into doing this though right few of any institutions have investigated institution wide expenses for these services, given these complexities the distributed nature, along with the unique nature of research and its methods by discipline and sub discipline. It gets complicated quick. Often described as an unfunded mandate or policy, you know, many of these federal policies and even private private funding agency policies do allow costs for implementing the policy as allow as an allowed direct expense to funding. So, in recent little bit of research I completed with some colleagues we found that 62% of private and federal funding agencies allow these expenses to be included as direct cost. What activities were actually allowed very significantly among the data policies analyzed, and we're also fairly vague many using terms such as documenting or preparing or curating to describe what was allowable. This was so vague that many of the sub activities that would be engaged in that are inclusive of that were not didn't go into any of those terms so you know the data curation network has identified over 50 activities that could be considered curation related so it, it gets down into details quite quickly. The big takeaways from this kind of general analysis is that none of these funding agencies provided example costs or budgets, and none of the policies address covering expenses post award. While most of the policies stated that research data need to be retained for three to 10 years post grant close out. To pull this all together you know funding agencies are requiring the sharing of research data have been for almost two decades which is wild researchers and faculty can include these grants and their costs are in their grant proposals, whether or not they can fit it into their grant proposals hasn't really been tracked because we don't have a lot of information or data on the costs institutions have stood up services and enhance services to meet these new repositories. And we don't know the full costs so faculty can't include them, and we can't collectively advocate for new funding models if that's what's needed as well. So needless to say there's a lot of work to do here. And we have heard from NIH that they'll be releasing additional FAQs and guidance on what researchers should be considering or thinking about with regards to cost for data management and sharing. And we will soon see through the presentations that follow that many higher ed organizations are looking critically at how to account for the institutional costs for public access to research data. And with that I'm going to turn it over to our first set of speakers Christy keen and Melissa course to give us an update and what the federal demonstration partnership has underway. Thank you. So for those of you who may be wondering, what even is the FTP, we figured we'd start with the close notes version of what is the FTP. It's the federal demonstration partnership, which I think originally began, you know, several decades ago as the floor to demonstration partnership, where, you know, far fewer than now, we're currently up to 217 institutional members. There are institutions themselves that are members, as well as a variety of federal funding agency members come together to work towards reducing administrative burden associated with federally funded research. Next slide please. So the red language here at the bottom is sort of our tagline, researchers doing science, not administration. So, the FTP mission is federal agencies, academic and nonprofit research institutions and research policy organizations working together to streamline the administration of federally sponsored research and foster collaboration to enhance the national research enterprise while maintaining high standards of stewardship and accountability. It's in a space like this, we don't want to sacrifice good data management practices to get this burden. We want to maybe create consistency or make sure there are clear guidelines, clear best practices, rather than really trying to kind of compromise data management. So we want to maintain a high standard while trying to reduce burden. Next slide please. This gives you a little bit more of the type of folks that participate in FTP activities. The federal agency participation is really critical in pursuit of our mission. And we have, as I said federal federal agencies that are members but also many federal employees from those agencies that are critical to moving our work forward. So we also have a wide variety of engaged faculty representatives each institutional member is assigning a faculty representative representative that can help us make sure that our efforts are aligned with faculty goals and eats. And then we have a diverse group of technical and administrative representatives that that can bring those perspectives to our work as well. Next slide please. So our adventures in FTP, looking at some of these data management cost issues has been going on for a little while as we tried to sort of figure out where we wanted to fit into all of the groups that are working in this space right now. So we did what's called a thought exchange with first with our faculty representatives so that we could gauge what are the biggest areas of concern for our faculty where they most worried about be able to cover costs. And this is the cloud from that thought exchange can see that requirements factors really heavily really understanding requirements where they need to get the funding budgets are some major themes and some of their thoughts. And next slide please. And specifically, if they could indicate their top three areas, their top areas of concern over some of the thesis of the data management life cycle and and the top three. So pretty much the largest was what are they going to do close out and close close out. In part because once you hit close out the grant funds go away and so how will they support the cost of maintaining that that data for the longer term so that they can share or use it. So that comes with like considerations like HIPAA and protected health information or export controls or federal information security requirements. And then followed by that is data management plan monitoring compliance. And that again is that close out and close close out so once an award has actually ended, what is enforcement going to look like and making sure that they're continuing to comply with their data management plan, even, even after the awards ended. We also asked for what types of data sets were typically used by our faculty members, and the top three responses there were data that they acquired through their own activity so so data that the researcher generated themselves. And the data that was institutionally provided maybe that they got from their library or a collaborator and third was data acquired through purchase so perhaps a purchase of CMS data or commercially available data set. Next slide please. So those of you might not be familiar with thought exchange. The way it works is it's a little bit like Facebook or thoughts where you know you can go in and ask one sort of really broad question like, what are you worried about in terms of covering data management sharing across and each respondent can share as many thoughts as they like and then they can kind of up vote or down vote as the case may be the thoughts that others have added. And some of the main themes that came out of our faculty thought exchange is, as Cynthia mentioned that this feels like an unfunded mandate, they're worried about, you know where the funding is going to come from this new requirement. Because it doesn't seem like there's funding coming along with it. The desire for uniform cross agency requirements. So if every one of the federal funding agencies or every one of the research funding agencies has different requirements becomes really difficult and burdensome for them to apply. Who is going to pay where's the funding going to come from. And along with that long term funding for storage and curation. They really are hoping for clear guidance on how they might be able to budget for these costs so to the extent that they can ask for grant dollars. So how exactly should they budget for those water allowable costs. And, and that we are able to explicitly recognize activities associated data management like data collection transformation documentation as legitimate and appropriate allowable direct costs. They're hoping for clear regulations, and they're concerned about graduate students being required to do this, and not the PI anecdotally at my own institution we have lab data managers for each lab. And it's often like the first graduate student or the last graduate student or postdoc who joined the lab gets sort of fallen told that they're the lab data manager. And we want to sort of flip the script on that so that we're really putting resources into data management expertise. And then sort of lower down the line was what are we going to do about repositories how are we going to find them and seen them worried about the NIH deadline and worried about the culture changes kind of come along with the policy. All right, I'll take it from here. Thank you. So after the faculty thought exchange we then asked our administrative members of FTP, what their concerns were related to these to this upcoming mandate. As you can see through the word cloud that plus sign represents FNA. So how are these costs going to be covered is our main concern from an administrative perspective. And we hear a lot of these do center around the actual costs. And, you know the management of these of this data. Next slide. So from there, we are putting we have put together a group within FTP to look at all of these areas. We have a great group that is made up of data management experts, cost analysis experts and we also have a federal representative from NIH. So we will be meeting routinely and hopefully get some guidance going forward ahead of January 2023. Next slide please. So our, our initial issues that we're going to be working on our exploring cost models what options do we have thinking about FNA. It's clearly not F, so where will these, where will this recovery come from. And, importantly, as already mentioned is quantifying these costs. These are highly distributed so there isn't like a place to go and look up how much x costs for each or for each data set. So, and again as Melissa said this is throughout the life cycle it doesn't end when the award ends. These costs will continue after the grant funding has ended. So, where will those costs be covered from that point. And then we will also be working on guidance on drafting data sharing plans and budgeting for these costs at proposal stage. So, part of the mandate that this has to be recognized at proposal it's not after the fact. So the expectation is that there will be data. So, what is that plan, what does it look like a proposal, whether that is awarded or not. So, these, these are really important things that we as administrators and faculty are very concerned about we're very excited to have NIH on board as part of our working group. It, it would not be possible without their perspective as well. And to hear our concerns and those of our faculty. Thank you. Next slide. I'm up next. I'm the project manager for the realities of academic data sharing initiative at the Association of Research Libraries. The realities of academic academic data sharing project or just rads as we call it is funded by an NSF eager grant so Cynthia who we heard from in the beginning. Today is the PI on the project and Wendy who you'll meet a bit later in the presentation is a co PI. And we're about six months into the project. So next slide please. So, why is the rads initiative significant and why is it important at this time. So as you can already tell from the conversation today. It's quite timely, especially with the number of changes happening into in next year 2023. Federal policies requiring public access to research data have increased the required infrastructure and costs to meet the federal mandates. So of particular significance to the rads project is the shift in the research data landscape since the issue of the 2013 Holdren memo. As Cynthia mentioned, directed federal agencies with more than 100 million in annual conduct of research and development expenditures to develop a plan to support increased public access to the results of research funded by the federal government. So this federal mandate transformed how institutions and researchers manage their research data. The rads project investigates these changes by asking three questions. How are researchers sharing their research data and what is the quality of their metadata. How are researchers making decisions about why and how to share research data and what cost do they incur. And what is the cost of the institution to implement federally mandated public access to research data policies. So next slide please. So we are asking these research questions to institution administrators and researchers at six academic institutions. So Cornell Duke University of Michigan University of Minnesota, Washington University in St. Louis and Virginia tech. So next slide please. So project goals and objectives concerning costing questions have been divided into sort of two workflows, institutional infrastructure and researchers themselves. And the researcher workflow kind of builds on the institutional infrastructure foundation because as we know our academic institutions support our researchers. So first, rads researchers conducted within the project conducted a landscape analysis of existing costing frameworks. So these for the frameworks that we evaluated are the Koger a part costing framework which you will hear more about from Jim today. The UK data service data management tool and costing checklist. The National Academies of Sciences engineering and medicine biomedical data cost driver framework. And there are several others I'm not going to list them all here, but you get the idea we kind of looked broadly at what was out there. So each of these frameworks include activities or categories which define public access activities within the larger costs of data management. So each of these costing frameworks is useful and identifying activities and processes required for public access to research data, but as is already mentioned, none address the entire research lifecycle. As project investigators recognize the need for more comprehensive understanding of the processes and activities required to make research data publicly accessible in order to then determine their corresponding costs. Next slide please. A particular value in parsing out what these activities are is the National Institute of Standards and Technology or NIST research data framework preliminary framework core. So the NIST framework identifies the research data lifecycle stage categories within each stage and over 100 subcategories or activities that may be required to make research data publicly accessible. Next slide please. So in addition, research data fairness activities are integral and super bad exclusion and inclusion of what is required to make research data publicly accessible. So any activity that is deemed deemed necessary to make data or metadata fair are included in our assessment. During these frameworks and activities campus mappings of institutional infrastructure were conducted at each of our six academic institutions. RADS researchers understand these frameworks cannot capture all services and activities at each institution and departmental and organizational administrators will be surveyed to surface any activity gaps. Next slide please. Several more months into the project leader this year. Campus administrators will be sent a survey to first identify which activity or service they support at their institution and to second determine the costs associated with that activity. Next slide please. So as I mentioned, we aren't just interested in the cost to the institutions but the cost to the researchers as well. Funded researchers in five disciplines, environmental science, material science, psychology, biomedical sciences and physics, our six institutions will be surveyed and interviewed to identify what activities and processes they support at each institution. Funded researchers in five disciplines, environmental science, material science, psychology, biomedical sciences and physics, our six institutions will be surveyed and interviewed to identify what activities and processes they are using, what activities are missing from their workflow that we did not capture, and what costs they incur for each of these activities. Next slide please. So, again, building on the survey that we will send to the institutional administrators we will also ask researchers, what are their direct and indirect costs, what are their ongoing costs after the end of the project life cycle. And if they had identified any costs in their data management plan, and if so, how did their estimate change or not. And then finally, after we've collected all of this data, we will do an analysis by discipline. And by institution recognizing that different institutional sizes will have an effect on what cost means, and as individual case studies. So quickly and some to wrap up. None of the existing costing frameworks address the entire research life cycle and I think you've heard that a few times today. Activities for what comprises public access to data should be clearly defined and cost for public access to data are best captured across project activities as one time or recurring, direct or indirect and as labor or capital. So that's all I have for you now and I'll turn it over to Jim. Thanks, Shauna. Thanks for this opportunity I appreciate it. Before I jump right into the slides Shauna has mentioned this group a part a part is a group that was started with a you and a PLU. 2016 and a part stands for accelerating public access to research data. It's probably worthwhile links that we can send out if you haven't seen it. It started in 2016. There was a number of informal groups that formalized quite a bit. And then in 2018 NSF provided a funding grant. And a report was issued out of a number of meetings with, I think at one point there were 30 universities that met multiple times together and remotely. And then there was some additional funding from NSF and from NIH and there's still ongoing wonderful work in this space. So, this group Koger the slide that you see in front of you. I was invited to a part because at the time I was the chair of the board of this group the council on government relations. I went to the APR meetings I was the only non librarian non IT non faculty, non vpr person in attendance. My background is administration and compliance and costing, and I'll talk a bit about what I mean by that here shortly. And throughout the course of that had some great discussion about the cost, and who should fund this stuff and that's a bit of what I'm going to talk about here and in about 10 slides. But very briefly Koger if you're not familiar with it is a group of about 200 meeting research universities. It considers itself and functions as kind of the national leader in this space with regard to advocacy around different regulatory issues. And they spend a lot of time as as as underlined here, doing analyses, developing position papers, interacting with federal partners and so forth. They also work a great deal with directly with the FTP with a you and a PLU. Next slide. So not knowing whether people understand what we mean by costing. I'll briefly explain that I've been, I was a Duke for 30 years I've since left Duke and part time at Yale and part time at FTP. And when we talk about costing, we talk about how universities and research institutions are going to share the cost of research with the sponsor. Sometimes that's a direct charge if the sponsor pays for something directly, and lots of times it's an indirect cost, also known as FNA or facilities and administration. But but critical to that is this thing called the administrative cap. Universities have a cap on its administrative costs of 26%. Many universities are five or six or seven points over that cap, because that cap was set at 26% in the early 90s. And what that means is, for example, well, when I was at my former institution at Duke, we calculated that of the 900 or almost a billion dollars of research that Duke does Duke University contributes about 125 million dollars to support that that is in cost sharing that is in unrecovered costs in the FNA rate and lots of different things. So as we look at an issue like data management and data open access and public data access. The reason I've written this slide that this is a quintessential costing issue is because it is something that greatly interest the people that are going to advise leadership. And as to how to fund these things. And the reason it's a big deal is because it's potentially a lot of money. As you think through the life cycle of open access. And one of my future slides I talked about that as Christie alluded to. It could be a direct costing issue where the grant pays for something directly or an indirect or FNA issue. The regulatory environment specifically is evolving. Although, as, as Cynthia pointed out, this has been a topic from multiple decades. NIH in particular, although they put the notices out on this new deadline. A year or so ago, January 2023 is right around the corner and there's a lot that needs to be done to figure out how to execute and implement on this but also how to fund it. I won't go through all of these things because it gets a little technical, but that middle bullet about a complex internal control environment. What I mean by that is, if, if, if this is all about making if one aspect of public access is about making the data available so that individuals can get to it at a university. That could be a network server that's funded directly on the grant as a direct charge. It could be funded by it as part of the overall it infrastructure. It could be a purchase on a procurement card that the faculty member gets reimbursed and that could be capital or not capital, or it could even be me purchasing Amazon cloud space on my own personal visa and getting reimbursed. So capturing those costs, understanding how they're going to be director in direct charge are very complex things that institutions are wrestling with right now. And I won't go through the rest of those items, but suffice it to say, it makes it even more complex as you look at those indirect cost pools that I allude to are the library. DA is departmental administration, GA is general administration, which is often where it for example is funded operations and maintenance equipment, and then your research base in general, all complex things as we look at this. Next slide. So before we get into the life cycle what I wanted to take a minute. Thank you very well and that's who some of you might know was on point for NIH and the implementation of NIH's new policy for data management sharing. She has since left and is working with OSTP, but she presented at Koger in February 2021. And then she is out on Koger's website if you want to see the details of it. But, but I think the things that really underlie us or reinforce just the importance of this is not only why is open access and public data access important. That is clear, but, but Kerry was very effective at mentioning time and time again, the vastness of the culture change that is NIH's goal for faculty and postdocs and graduate students in the management of data and the public access of data, and data management and curation and everything that goes into that. And, and as you all know, as well as all the presenters know, culture change is hard, it's expensive, it's difficult, there's lots of aspects to it. So again, as we look at these costing issues, if we were implementing just one little element of this, the costing and the magnitude might be one thing, but when we're talking about a real culture change about how data becomes so critical and such an important measure of the research and what NIH wants to do that, it really makes it all the more critical. Next slide please. I'm not going to go through this next slide at all, but these are the four notices that we're talking about. They came out in October 2020, they're effective in January 25. They described the overall program and then they have a separate notice, as you can see on the highlights of what is in the data management plan, what are the allowable costs, and we'll talk a little bit about that 21-015, because it's wonderful that NIH created a notice. But it's, at this point, it's but a nod to really what the details are that we really need to sort out, which is why, as Christy mentioned, there is a, there is an individual from NIH who will actually be on Christy and Melissa's committee. And then there is a discussion of a repository. So really good out of the gate, strong messaging on this, but still a lot more work that needs to be done. Next slide. I was working with APARDS, and I'm going to drill into each of these so you don't need to look too closely at this. One of the things that became very clear to someone who does not understand the details of what is meant by public data access or curation or any of those things was when we talked about costing things, oftentimes people were talking about different elements and really didn't know it. A carpenter saw everything as if it was a woodworking project and a plumber as if it was a water problem, and so forth. And so in one of the meetings with the public access to research data, I created this chart, and I'm going to drill into this in two slides. So next slide. Column A is all the activities, and I just kind of cut that column into pieces. This is probably somewhat infantile from the perspective of you all as professionals that manage this. But from a big picture perspective, what we wanted to be clear is that when we were talking about the cost of public data access, we weren't talking just about about number nine, which is storage after the end of the grant. We were talking about data management plan development, which is a cost that is incurred before the grant is even awarded. And as some of you might know, the hit rate is probably around 25%. So that means generally speaking three out of four times that a proposal is submitted, it's not funded. And so there was a cost there that is generally speaking never really reimbursed. And then you can see, as far as that timing column there, some of these things happen during the life of the award, some of them happen post award and so forth. So again, in the discussions with the public access group, the public access to research people, we were talking through, okay, when we're talking about costing really what element of this are we talking about. And then we were talking about who's going to pay for it. And that's, again, the columns across the top. I just talked about column a which is the life cycle element element. And then as you talk about who potentially could pay for this, you can see in the top green section, the sponsor could pay for this somehow directly. Now, there's lots of issues related to this because there's, there's congressional appropriation language that requires that that money awarded to a grant can generally only be funded during the life of that award it cannot be incurred it cannot be spent for a future cost. So it's, it's, it's not easy for NIH to say, I'm going to give you $500,000 for five years of work, and then I'm going to give you another $300,000 so that you can retain that data after the end of the award for 10 years. That is very, very difficult for them to do not because they don't want to, but because the way money is appropriate to Congress, there's significant limitations. So there can be those ways that the sponsors can pay for it. In the blue column there's ways that the institution can pay for it. Some of those ways, institutions can recover it. If it's part of the indirect cost rate. If, for example, it's in a cat cost pool, then the institution might incur $20 million a year. And if all of that is in the cat portion. So there's no way for them to recover any of that whatsoever. And then the, the third big bucket is external repositories. Again, that is more about the storage costs during and after during the award and after the end of the award. But that is another way that the cost could be shared. And so this was all about a construct to determine, hey, what pieces are we talking about during the life cycle. And then when we talk about those elements, who were the potential payers from a costing perspective. Next slide. And now I wanted to just take, I think I just have two or three slides that are specifically about what Cougar is doing. I did briefly look at the list of institutions that generally are involved with this group. And I would imagine most of you have individuals. Most of you, most of your institutions are members of Cougar. And most of you have individuals that participate in these meetings, especially because it's much easier being online. But even when we were meeting in DC on a regular basis, I would imagine most of you had individuals that went. And so, as I mentioned, Cougar has expertise in addressing various issues in this case. We've established a work group that is, that is going to develop the expertise share with other associations. And by that we mean, ARL, AU, APLU, and so forth. And look at the issues specific to NIH's data management and sharing policy. And so truly this work group is really focused on readiness for January 2023, although there's broad issues of how addressing this problem is going to address. I'm sorry, this, how we address this objective will also support many of the other things that we do. The big objectives that we're trying to do deliverables, one is advocacy. So we're going to make sure that we understand what those four notices say that institutions understand it that there is harmonized across institutes as much as possible if they can be. And so there'll be a discussion around advocacy from that place. There'll be deliverables related to education and resources for the Cougar members so that we, so that we Cougar can help the institutions be ready for January 2023. And then there'll be an explicitly a cost of compliance survey and report. Cougar has done this around the impact of COVID, for example, in impacting research universities. They've done this around the recent research security and foreign influence over the past three years. And they're really adept at doing that analysis and understanding what what the cost of compliance survey and report is, and they'll be working with Cynthia, so that there's no kind of duplication of effort but hopefully some synergy as we work through that. Next slide. We have three primary objectives or current work group priorities. One is a series of briefing sheets, which is basically to some degree, although NIH has been sounding this drumbeat in one form or fashion for a decade or more. As far as this specific issue about the data management and sharing, it came out in October 2020. And just to be blunt, there's been significant distraction between COVID remote activities, the foreign influence and research security and so many other things that that most of us are a little more than concerned that we are nine months out from a pretty significant go live in related to an issue that it is as discussed before, we'll have some significant culture implications, as well as business process and technology and so forth. So one is about briefing sheets and we're creating a briefing sheet to help discuss what this issue is with leadership and institutions. Specifically, there is some institutional readiness assessments that are being conducted so that institutions can really understand kind of where they are. It's a little bit parallel to what Cynthia said earlier with six or seven institutions involved in the NSF grant, but it's helping an institution understand the diversity of the implementation. And by diversity, I mean, in disciplines, oftentimes campus schools and departments are quite different than schools of medicine, school of medicine, even amongst themselves are very diverse and complicated because they have institutes and centers, some of which may largely have implemented this if it's genomic and genetic, others that really haven't, and a very broad continuum. And then lastly, as I said before, we'll be doing some advocacy around the notices. Next slide. This is what the first briefing sheet looks like. We will make sure that we work with Cynthia to share this and share accordingly. This is a very early version of it, but it's a basically a three page document that summarizes what is NIH. And what have they tried to do in this space, and what are they trying to do effective January 2023. Next slide. So this is the slide that you saw earlier. The only thing that's different is the red line in the bottom and I just kind of wanted to close with this. All of us on the costing side. And on the regulatory side, I'm sure Christie and Melissa deal with this all the time. We want to make sure that we help with reducing burden, managing the regulatory risk, helping from a compliance perspective, but, but we also want to stay out of the way of the business of running a university. And, and sometimes the costing questions. If not handled adeptly can create issues related that that could impact internal operations or budget and management decisions. And that's not at all what we're trying to do. But we're often trying to insert ourselves and understanding how these incremental costs will be where the cost will exist, how much money they are so that we can capture them and potentially charge them as direct or capture them as indirect. And that kind of is a closing point, because it really is a critical kind of difficult proposition that you're costing people at your institutions are trying to do is they work with the IT individuals and the library individuals and the vice presidents of research and so forth. So I think that's my final slide. And Shauna we get. I think I turned it back to you Shauna. Yeah, so we are just going to run a quick Mentimeter poll if participants here don't mind. I'm sure most folks are familiar with Mentimeter by now. If you could just grab your phone or your browser put in the code on menti.com. So we were going to have kind of full some discussion around the Mentimeter activities and questions but we are running short on time. So Jim, if you don't mind, we'll just let everyone take the poll and then Wendy can step in and sort of facilitate the final discussion questions. Sounds good. Thank you. Thanks. So yeah, so please get started. And you can scan the QR code there or enter the code. And then we have four questions. However, question to list about 19 activities. And these are just a sample of activities that we've included from our discussions here today surrounding cost. If you could just kind of glance at those I know it's a long list and we are running short on time. And then the question after that is just sort of centering like, what are you most concerned about in terms of costing from that list again not comprehensive, just to give us a quick marker on where your thoughts are at. So, Wendy, I guess I will turn it over to you now once we get our results from the mentor. Thanks, Shana. And I think it'll be really useful as we go through this and I currently showing the answers to the first questions as a point of discussion to display the results so thank you. This one may take a minute just given how many there are. I think we had about 27 people identify who they were so we're getting near, I think, totals ish for this question is there anything that stood out to you Wendy. So clearly there are some things that are rising the top but I also am kind of excited to see that everything has at least one vote. I think that as we've talked about as you know brought up by I think every one of the speakers today. This concept of what is actually involved in meeting data sharing requirements is huge there's a lot of pieces to account for. So as we try to gather information in order to provide the services that are researchers and institutions need to be able to support this, that we actually are capturing the full range of activities that might be incurring those costs. You know, the, the one of the requirements of the NIH incoming plan is requiring a data, they're referring to it as a data sharing plan is to have a data management plan, but one of much of the requirements are going to be similar in there. And it looks like those kind of support services might already be in place, like to hear from people about whether these things that you are already doing are incurring costs and whether you're able to capture those costs in practice already. I believe there's one more question to there we go. So, this one again is standing out to me as we're seeing more people clicking on interested in understanding better the costs around active are archiving data post close out, as well as meeting and managing data that have specific security issues. And I think that what we'll see is that neither of those things turned out to be top on the list on the previous slide of activities that we already are feeling that we're doing a good job at are already providing in our institutions. Any last call or should I go on there's one more kind of open text question. No, Cynthia, given the time. I wonder if we should just kept to go on to the discussion and leave a few minutes for I'd like to also give the opportunity for people to ask questions if they have them. Maybe you could put up the prompts of the discussion questions, instead of going to the taking the time to do the fourth slide. So at this point I do welcome comments and feedback Cynthia is going to throw up some questions that we had posed as a group that might initiate some discussions but also please feel free to unmute yourself and speak up if you would like at this point. You can put the question in chat will monitor there to as a librarian coming from the science side. One of the biggest challenges that I had in switching roles in my position was learning vocabulary and I think something that I'm really curious to hear people's experiences about is making sure that we're speaking a common language amongst the various different players. Jim mentioned institutional versus sponsor versus the researchers themselves and whether or not, as we try to gather information about costing. If we're understanding one another and referring to activities and describing them using the same kind of terms, and if people have thoughts or experiences or have had issues with that in the past I'd be really interested in hearing about that as well. Sorry slides are going wild. My apologies. Wendy I'm not sure if you can see the chat but we have a plus one to common languages. Some researchers are doing data management but not necessarily thinking about it in those terms. Yeah, I think that is really to I think it true. I think that it'll be really interesting as we move through this process in these various groups and continue the conversations to find out what practices are already in place that people might be not yet associating with the concept of data management or data sharing, and which ones are going to be new that maybe we need to focus on some concerted efforts on around at our institution. Cliff, would you like to to speakers, I can read your question to there's a couple of questions, how are the rise of specialist active repositories changing the landscape. And when we speak of public access does this simply mean access by the public, or giving them some help in understanding and using it. The second question prompts in my mind this idea of working through this in an iterative manner. I think that at a baseline, if we're talking about compliance. We don't have the data up there as a first step, but then instigating something with something like active repositories and fulfilling the ability for people to actually use it is a logical next step and certainly required in order for it to have the worth the effort to put it up there in the first place. Melissa you have your hand raised. Yeah, and, and I think in the case of the NIH policy, at the very least, it is definitely the latter. One of the stated goals is to maximize the investment in research by promoting secondary use of the data. I think that is especially the case when we're talking about data that was collected using human subjects. We want to really make sure that to the extent it is consistent with that subjects privacy concerns that we're maximizing the impact of the contribution that they've made to science so I think it is absolutely to ensure that those data can be used to further research. And as a data curator myself, I certainly have seen a lot of cases where people have shared data to meet, for example, publishing requirements, and not completely thought through what it takes to get someone else to understand that data and I think that education piece it isn't just an awareness of it being a requirement, but an education of what is required to meet it that is going to have some costs associated with it as well. I think we're getting close to time but we, I think we could certainly fit in one more question if someone's got it. Hearing none. Any, any final wrap up comments you want to make. I guess I would just thank you all for listening for thinking about this with us. We look forward to future discussions. I think that there's a great synergy between the efforts going on with the FTP and Cogar and the ARL RADS effort, and I look forward to looking at all of this aggregated together to see how we together can all move forward with it. Well, I thank you all very much for a wonderful and very comprehensive look at the current state of play. I hope that you'll keep us posted I think things are going to get very interesting when the new NIH policy role actually takes effect, for example. There's plenty more to talk about here. As a side note, I hope we can figure out some way to get those charts that the the poll charts into the into the recording or the slide deck or something and we'll be in touch on that. So, with that, let me thank all of the participants here and Cynthia for really pulling this all together. It's been great.