 Good morning, everybody. We're going to go ahead and get started here as people start to filter in. Welcome to today's panel, which is on coordinating research data support services across campus. My name is Dylan Riediger. I'm a program manager at Ithaca SNR. And with me today are Laura Hibbler, who is the Associate University Librarian for Research and Instruction at Brandeis University, and Renee Barger, who is the Associate Vice Chancellor of the Health Science Library System at the University of Pittsburgh. It had been our hope today to have two other colleagues join us at the table. Scott Walter, the Dean of the University Library at San Diego State, and Jen Green from the University of Chicago. Both of them have had excused absences come up in the last 48 hours or so and send their regrets. We're going to spend most of our time today in conversation, but just to kind of frame what we'll be talking about. As probably most people in this room know, research data services have become pretty foundational components of the research infrastructure and enterprise across disciplines. But at many institutions, they've developed in a very ad hoc fashion over the last 20 years or so. Or else there are other institutions that are just beginning to build these kind of services out who are trying to understand how to do so in a more intentional way than the last generation of services developed. As the demand for these kind of services increases, and as research, data intensive research becomes more complex, and as funders, notably federal agencies, raise the bar for what counts as viable data management and curation across the research life cycle. Universities are recognizing the importance of a more coordinated approach to research data support services. This, I think, will become even more important in the coming years, particularly once the OSTP requirements for preservation of research data that is not associated with publications starts to become a reality, which I think is going to happen relatively soon based on what we're seeing out of the agencies so far. Libraries have been major providers of these services on many campuses, and often we want to remain so. But as the demands of supporting the labor behind data management and curation grows, the need to be deliberate about how to share this burden across units is quite acute. To help intervene in this area, the SNR has put together two cohorts of our research data support service project. This is a two-year project that involves research and then working with our partners to implement a coordinated data support service strategy across their campus. The cohorts, which are just beginning their work, are quite internally diverse. They range from major global research universities to a number of R1s and R2s who are really trying to aggressively build their profile as research institutions, but what binds them together is a determination to find ways to work across campus units and silos to take a crack at, if not solving, at least mitigating the challenges of supporting researchers. So today we're going to talk a little bit about opportunities and challenges in this space, and we're going to do this as a roundtable conversation. We're no prepared remarks. We're going to be not quite winging this, but fairly close. And I'm going to start by offering some questions to Renee and to Laura, and we'll leave quite a bit of time, I think, for questions from you. So my first question, I'll pose this to both of you. Coordinating support services across campuses requires a lot of units to play ball together and be nice and to be willing to work together. Some of the units that we're often seeing in the cohort are the Vice Provost for Research, IT, various research centers, high performance computing centers, and a whole other kind of constellations of units depending on the configuration of a particular institution. What do you see as the role that your library or your library system can play in facilitating the cooperation that's required to make a campus-wide initiative like this work? So to contextualize my response, I just wanted to provide a little bit more information about Brandeis. Brandeis is one of the smallest R1s, and we have about 3,600 undergrads, 2,000 grad students, 600 faculty, and we don't have a medical school, but we have graduate programs in arts and sciences, business, and public policy. And for a school of our size, we have a relatively large number of academic programs and departments. And I think also a related piece of context for Brandeis is that we were a merged library and IT organization until about 2016. So I think that just is helpful as I move into answering the question. So I see the library's role as a connector and translator between different campus units as we do look to coordinate research data services. For example, the library can bring a deeper understanding of the data service needs of different PIs, their needs around storage, for instance, to our conversations with an IT department. And an IT department often takes a different approach to technology and infrastructure needs than we might in the library. But I think we in the library really understand both the pressures that an IT department is facing when it comes to maintaining stable systems. But we also understand those research pressures and the administrative workloads of researchers and faculty and PIs. So we can really translate between those two groups and be advocates on campus for that more centralized approach to research data services that I think is so needed. And by being those translators, we can take into account all of those needs and pressures. And I think also it's worth noting too that the library can be a connector of individual people even on a good-sized campus. For example, we've found that researchers don't necessarily want to share their successful data management plan by posting it somewhere that everyone on campus can see it. But if someone like a librarian who they know asks, would it be all right with you if we share this plan that you had that was successful with someone who's doing a data management plan for the first time? There's often that willingness. So I think there's that willingness to help two researchers don't know each other. In the library, we can be that connection between individual people. And I think that really just builds on so many years of great work being done by libraries and supporting researchers and building on those connections. So going forward, I think that library historic and continuing strength and connecting people will be immensely helpful in coordinating research data support services. Hi, everyone. I'm representing University of Pittsburgh Health Sciences Library System. Our university is a large R1 institution in the top 10 NIH funding. And just to preface a little bit, our libraries are administratively separate. So our health sciences library, I report directly to the senior vice chancellor for the health sciences, and we have a university library system that reports up through the provost. So we do have roles in breaking down silos of both what we call lower campus and upper campus health sciences. But like Laura, one of the major advantages I see our libraries playing a role is as collaborators and connectors. We work with faculty, researchers, postdocs and students in all the schools and all the departments. And so we offer our unique expertise to organize, share and cite data. But we also see a relatively holistic view of challenges that researchers encounter throughout the research data lifecycle. And something that's outside our areas of expertise as libraries, we leverage our contacts to point researchers in the right direction. So I see the library as being key in identifying partners across campus who are offering research data support services. Key in informing researchers of these existing services at their point of need. And also key in helping to compile a roadmap of these services. Renee, if I could just ask a follow-up question to that. How active is your library right now at providing support services to researchers? What kind of services do you offer? Can you tell us a little bit about what the status quo looks like? Yeah, so we are relatively active, especially with the NIH mandate to have a data management and sharing plan. We do mostly consultation and education across the health sciences. We also have a really good relationship with the data services team at the university library system. So we collaborate across campus to address common needs, offer workshops, offer symposiums or webinars on data and data management practices. Laura, is that a pretty decent description of the role of libraries at Brandeis as well? Sure. So far our most popular data services that are offered are our workshops and consultations around data analysis and software, and we're beginning to see more interest in data management plan support. We've offered that for a long time. We haven't necessarily seen a huge use of that, but we are really excited to offer more in that area going forward. And I will say the folks who have been providing the data consultation and workshop series, they've just continuously been really great about adapting what they're offering based on the changes in the software people want to use and going forward as far as the increased support for data management plans as well. Great. So what I'm taking from both of your responses to this question is the idea that the library has quite a bit of expertise that it can leverage and a fairly unique institutional setting in that it is collaborating with other units, but also has ties to researchers that many other units may not share. Having just spent a few minutes talking about things that the library is really well positioned to do, what are some things that you feel like you need somebody else to help you with? What are the areas where library's ability to act in this space are most constrained? So in libraries, I think we have a tendency to fill in gaps in services and resources on campus, and we're often really successful in filling in those gaps, so it's successful in fact that other campus units I think often rely on us to fill in those gaps. So here though, I think, and I'm sure others would say the same, libraries really need support and resources from campus units, like the provost office and IT, particularly with regards to storage needs. As we look to develop research data services, and we also need that collaboration from offices and research administration and pre-award staff, and I think another area that we sometimes need to work on in libraries I think is being prepared not to say yes to everything that is asked of us, or to really advocate in some cases for additional research data services without getting that additional support that's needed. So besides data, where would you most like to be prepared to say no? Well, I very explicitly said be prepared not to always say yes as opposed to saying no. I think storage is the major one that we can't just spin things up overnight that we really need resources and services and that even with all the financial resources that collaboration with campus partners as well. And I'll add to Laura, and based on some of the grassroots committees that I've set on to start to identify and coordinate research data services, one of the biggest challenges is oversight and ownership of the effort. Libraries alone and even small interested groups cannot advance effort at an institutional-wide level. We cannot incentivize researchers to share breast practices or incentivize them for good data management practices or financially support coordination, storage, platforms, or additional staffing. To truly have an institutional focus, we need support from the highest levels of leadership. And along these lines, a data science task force was appointed at the University of Pittsburgh in 2019 by our provost. The task force was challenged with recommending a coordinated strategy to equip undergraduate and graduate students with knowledge and skills for increasing a data-oriented world to develop and use data science methods in their research and to attract and retain faculty who use data science associated methods in their disciplines. A representative from our Health Sciences Library system was appointed to this task force, along with representatives from the University Library system, leaders from IT, leaders from research computing, the Office of Research, and various schools with data in their curricula. One of the top recommendations from the task force was to create an organizational structure and appoint a leader. As a result, an associate vice provost for data science was created and the position was filled in January of this year. Those are some really interesting observations about the importance of oversight and governance. Is this new position also going to be involved in funding? Any of the research data services? I'm wondering if either of this question I guess for both of you. If we start to try to reimagine where some of these services sit institutionally, many of them are going to be serving researchers who cut across disciplinary boundaries, colleges, different kinds of units. How do you create a funding structure that reflects the diversity of interests and communities who might be intersecting with these things? Recognize that's probably a hard question. Yes, I think that's a difficult question to answer. Do you have thoughts, Laura? I guess I would just say that I think a lot remains to be seen and one thing that we are talking about, many levels at our campus is talking about how to fund things that fall across many schools and programs because there is that recognized need that some of these services need to be centralized and supported centrally. In our planning call for this panel, one of the things that we talked about was the finding that SNR often finds when we interview researchers, which is that they feel like they get the most value out of one-on-one consultative, long-term, or at least intensive exposure to expertise around their data needs. This is a very difficult thing to scale given the realities of staffing and funding needs. And yet it seems to be what a lot of people are asking for. Absent some kind of magical bucket of money that's going to allow you to hire staff at a scale to accommodate this, what kind of things do you see researchers as needing to develop their own competencies in over the coming years? I just want to add a comment, Dylan, about just the landscape and the need for consultation. We're finding there's a lot of education out there, but what they really do need is that consultation at their point of need. And one of the things that we're trying to work towards under the new Associate Vice Chancellor is communities of practice to help sort of leverage the expertise across campus in a somewhat non-financially strapped way. How that plays out is to be seen, obviously, but it's something that it's happening. We have various levels of expertise, but without the funding to actually support consultation services, finding other ways to make that happen. So are you acting as kind of a convener and a provider of space for those kind of communities of practice, or do you envision that being how you would fit within that? Yes, I do envision that. That we would definitely be convener, be able to offer space for those services. I guess what I would add is certainly sustainability and scalability is a challenge, but finding ways to make it more sustainable. We offer a lot of these things within the library, but if we're working with other campus units where we know there is that need for developing additional skills to embed training and existing training that they already have there to meet, for instance, with almost all of the graduate students and provide additional training there. Another area, too, I'll add is we're seeing increased need for programming skills, and again, there's lots of education, but is that one-on-one? This is my project. Can you help me? I'm stuck with, especially R and Python. We do genomics data in our library through our molecular biology information service, and so we're challenged with that gap right now and whose role is it to support that and what a sustainable model might look like. So I'm curious, hoping to hear some insights. Laura, you kind of kicked us off by talking about the idea of the library as a unit that could connect across institutional silos, and I want to kind of follow up on that thread a little bit because I think most of us who spend our time in or around universities are pretty familiar with those silos. As Brandeis was making the decision to participate in this project, can you talk through the process a little bit of how you initially created a kind of coalition of the willing and where you went to turn to find partners and how that kind of evolved? Sure. So the Brandeis team for the Ithaca Coordinating Data Services Study includes myself as well as two of our data analysis specialists in the library, and then we, as is recommended as part of the project, we also have a person who's part of a research center in one of our graduate schools. But we also talked to our Office of Research Administration about recommendations for who to involve and really want to make sure that at the later stages, even those people who aren't on the research team itself that we're really involving them when it comes to interviewing people and providing updates on the study. And our team member who's from outside of the library, when we first met, I actually thought she had a really interesting perspective on our campus and the potential impact of a project like this. She was really saying since we are, as I mentioned earlier, the smallest, or one of the smallest are ones in a relatively small university. She really was excited because she felt like we have that potential to develop a stronger coordination off-campus that might be a lot harder at a much larger university. I certainly share her excitement, but I also realize just how much work there is to be done as well. And I just think going forward are continued steps and trying to build stronger connections, even on a siloed campus. It really just comes back to those connections we talked about earlier, like connecting with a few of those siloed units who can then help us connect with even further siloed units. And just one example from our recent work, we've really been working a lot with our pre-award team staff on campus to prepare for the new NIH data management and sharing policy. And they've just been so helpful in that they really know what research grants are underway, who's going to need support, and they just bring an in-depth understanding that's just really valuable. And also they, I think, going back to that idea of sustainability of our services, we do those communications that go out really widely to everyone on campus or all faculty in a certain division, but by working with our pre-award staff, they're really able to also do some targeted messaging to people who need this information at that moment in time. So that's been really helpful. And I think working with units like that around campus can help us then connect with other units that we haven't connected with as much. Rene, a somewhat similar question for you. You mentioned earlier this task force, and I imagine the task force will be involved in some way, shape, or form with the research team that you've put together. Can you tell us a little bit about the task force composition and maybe in particular how you're working across the bridge between the College of Arts and Sciences and the health sciences? Is that a particularly significant divide at Pitt? And if so, what are you doing to kind of work across it? So actually the Ithaca project we're using as a starting board, jumping board to continue our collaboration across campus. One of the challenges that we do face as a health sciences library system is just by the organizational structure at the university, many other players in the research data realm don't necessarily think of the health sciences library system. They're thinking more of the university library system. But our partnerships with the university library system, if we're not pulled in, they at least reach out to us and let us know and we get ourselves pulled in or reach out to be pulled in across the larger campus setting. Within the health sciences, we've been coordinating and collaborating with our health sciences CIO, our various deans in the schools of the health sciences. We have a CTSI program that also does research and data support that we partner with to offer joint programs, joint classes. We partnered with our office of sponsored programs to offer education under the NIH data sharing and management policy. And it's these partnerships that I think any way that we can partner across the university to offer our expertise in a way that is assisting them with some of the challenges they're having, it goes a long way into getting us recognized as a partner in the research data services space that leads to, as Laura mentioned, more collaborations, more ways to connect, and more ways for us to be recognized. As you kind of project yourself forward into the future, how will you know if you've been successful? What is a good way of thinking about what success might look like in the next two to five-year timeframe? What does that mean to coordinate services successfully? That's a great question, and the first thing that comes to mind, although I'm sure there's a lot that could be added, would even be, and I know this is actually, it's probably on my mind because of the ongoing work of the Ithaca project, but even just a comprehensive inventory of the data services on campus, because I don't think that we're alone and not really having that currently. We sort of know who's doing what to some extent, but we're always surprised to hear about different services and supports elsewhere on campus. So I think even just having that inventory and knowing who to turn to will be a really important thing to have in the future. That was also on my list, Laura, but some other things that I hope to gain, especially working with the Ithaca cohort, is to think of metrics to measure that success. A roadmap of services being one of those, but also how can we measure this increase in collaboration across the institution? Can we measure an increase in siting of data sets or an increase in the visibility of data? Spending less time on ad hoc solutions and a coordinated effort. Another thing though that I would personally like to see and learn from the project and from our efforts at the university is to see where support services are lacking and collaborate with our campus partners and our associate vice chancellor for data science to determine the staffing and the skill sets that are needed to fill gaps and have those conversations to see if the library has a role in filling those gaps. That's great, thank you. Just to push a little more on the metrics question, which I think is a really interesting one and also to say something about the inventory. This is an important part of the project that SNR will be doing. We are in the process right now of putting together a national inventory of research data services at a pretty good sample of R1s, R2s, and liberal arts colleges, as well as Canadian Carl institutions. With the idea being that we want to begin to understand the kind of landscape of where services are being offered, what kind of services are being offered, where, and to give people the opportunity to see kind of a heat map of what is happening on not only their campus but across the landscape. We've asked all the participants in the project to do this inventory on their own institution. They're using a somewhat more detailed tool than we are in that theirs provides them the opportunity to dig much more deeply into the personnel who are running these things and how to contact them, staffing models, things like that. And I know from talking to VPRs in particular that this seems to be a pretty ubiquitous answer from their office about what they need to learn first is just where these things exist. So that's kind of like one way of thinking about success, creating a level of transparency or clarity for the institution to be able to understand what it's doing, presumably also for then researchers to be able to understand what's available to them. If you think about more unit level ways of understanding success, like for the library, maybe I'll ask you this question for starts, Laura. How will the library know whether they are being successful as in their part of this partnership? I think some of the methods that we've been using over the last few years will be helpful here, just keeping metrics, but really looking beyond just sort of quantitative tick marks of consultations and workshop attendance, also trying to gather where possible some of that qualitative feedback about what this service offered by the library allowed a researcher or their team to do that they wouldn't have been able to do otherwise. And I think that it would be really interesting to not just ask that immediately after someone uses a library service, but further down the road closer to completion of the project. And this might be hard to capture, but I think it would be really useful to have data from researchers around campus about not just what they were able to do, but maybe the time savings that they found in being able to work with library data services. Do you have anything to add to that, Renee? I would add also the qualitative, we do not do a lot of the showing of the qualitative data. So I like that as well as it's following up to talk to the researchers and get some of that qualitative data. Again though, more quantitatively, that's something I would like to hopefully as a cohort think about what measures can we quantitatively identify and as I said earlier, things like the signing of data sets and the reproducibility of data. What kind of measures can we come up with that show evidence that the library had a role in that? One final question, and then I'll turn it over to the Q&A. These kind of services are quite expensive in terms of staff capacity and other kinds of resources that are required to do them well. Are you imagining that this project is kind of cost-neutral? Is the idea to offer the same number and type of service but in a more centralized fashion? Are there cost savings potentially? Is there going to be a need to increase the amount of resources that you're devoting to data support? And if so, are those going to be internal funds? Should federal agencies, other kind of actors who are helping to fund the infrastructure for research be involved here? What is your early sense of the financial implications of this project and of the goal that we're pursuing together? Do you want me to start? I will say that the goal to really coordinate services, in my opinion, the hope is that it will not be a cost savings, but it will at least avoid duplication of effort. And so if we can align our services as a library against the other services that are being offered across campus in a way that is avoiding duplication of effort, but is also focusing on common goals and together collaborating to figure out what is missing, what needs to be improved upon. And then as far as financial resources go, I envision as a, again, it's a university-wide effort that, whether it comes down from chancellor, provost, to our internal budgets depending on where it makes sense for those services to sit. I really like the way you phrased that, avoiding duplication of effort. So there's not necessarily cost savings, but by avoiding that duplication of effort, that hopefully is just helpful to everyone, especially given that a lot remains to be seen, but it seems like in all likelihood there will be additional costs on universities as we are trying to fulfill mandates to make data more openly available and just the storage needs that will be involved every step of the way. Great. I'm going to turn things open to Q&A now, and I will say that in addition to whatever questions you might have, because of the absences of two of our panelists, we've lost about half of the institutional diversity that we had hoped to put on display here. So please feel free also to use the opportunity to make some comments to contribute to this conversation that may not be a direct question, but speak to how these issues are playing out in your particular institutional context as well. Hi. I'm Cara Wiley from Caltech, and Laura, I was feeling a lot of this when you were talking, because we're also a really small R1 and a lot of the things that you were talking about, we are also dealing with. And I mean, this is not like fully formed, I guess, but I'm just wondering, so the other units on campus that are our partners in, you know, research data support services are perhaps even less well staffed than the library is, at least on my campus. And so there has been some, it's not just thinking about like what we say yes to, but there's been sort of like, you know, stepping back from the line with the library sort of being the only one who didn't step back yet, right? And so I'm interested in a little bit of kind of exploring opportunities if we are going to grow these services, maybe growing support, not in the library, but in other units on campus, so like advocating for more people in research computing support, for example, or maybe even like shared positions or things like that. And so I'm just wondering if you've been thinking about that at all, given the, I guess, size similarities and that sort of thing, so thanks. Thanks. And I think actually I've been told at least that Caltech is the smallest R1, I think we're the second smallest, so, and I really appreciate what you said about, you know, the staffing challenges that IT has, and I think because it's easy at times to get frustrated with the current state of things, but we do know our colleagues and that they're often struggling with the same resource constraints. So at the risk of sounding like glowingly optimistic, one thing I really hope comes out of the the Coordinating Data Services Project with Ithaca is that not only can we avoid that duplication of services, but that by bringing, talking with all of our partners across campus, we can have that coordinated advocacy too for the additional resources and not just that advocacy, but that shared understanding of places where those resources might be best situated. So I know that's a little bit of a glowingly optimistic outlook, but I'm really hopeful and think there's a lot of potential with the way that this study is laid out. Thank you. Hi, I'm Alex from Papa Ithaca, the all caps of Ithaca, not SNR, JSTOR. I'm wondering, you're talking about, I'm wondering whether or not you see opportunities for collaboration across institutions. Obviously you're doing that within Ithaca, within this SNR cohort, but I'm wondering if there are opportunities, services that either exist already or that might, that might provide support for organizations like yourself to be more efficient or anything like that. That's a really good question. At this point, we are not, but just because we are trying to figure it out at our own institution, but I can definitely see that. We have a lot of strong institutions around the Pittsburgh area that would make natural collaborators for us, especially in space. We have the Carnegie Mellon University that's very close to us, and we do have faculty that are sharing different roles, dual appointments, so I do envision that perhaps that might be a way that we can go as we figure it out first within our own institution. And I'd say we're still figuring a lot out at our own institution at Brandeis as well, but I think there's certainly already that knowledge sharing between institutions and the consortia we belong to, as well as I mentioned the meetings we've been having with our pre-award staff and they're part of some collaborations with other institutions around things like templates for new data management plans that were new to us or that are very newly developed that they really felt very strongly were going to be helpful for researchers at Brandeis, so I think there's definitely a lot of potential there. And I wish that Scott were here because I know he was going to talk a lot about some cross-institutional collaboration within the Cal State system. Yeah, I was just going to mention that. This is where Scott would have been really useful. Other questions? Comments? Hi, Judith Conklin, Library of Congress. You mentioned storage at one point and in this ever-growing, data-driven society and institutions, are you ever asked by your IT department for storage projections? And if so, how do you do that? I have not been asked for storage projections. Some of my colleagues from Brandeis are here who might be able to say if they have been asked for such information, but I will put them on the spot. But I think it's something to think about and really difficult to plan for a few years out as well. Yes, I agree. We have not been asked about storage predictions either, but definitely something that is important to consider and I'm hoping it's on the minds of others in the institution who are supporting our research supports. Just if I can just add a comment to that. I've had some conversations with people who are operating generalist repositories recently. So, somewhat different scale than the institutional repositories that your question was directly about, but they're anticipating pretty substantial increases even over the next 12 months in the volume of data that's being deposited. And I think it's pretty reasonable as the full impact of the requirements to deposit data not associated with publications start to play themselves out. There's still a lot of uncertainty about what exactly that will mean, but I think it's pretty safe to say it will mean a pretty substantial increase in volume even if we don't know what the exponent is yet. It's going to be quite large. So, I don't know that this is scalable, but I'll just answer that question because we have been asked that at Caltech. And what we actually did the library was we conducted a survey of all of the labs on campus to find out what data they have now. The stuff that's on the hard drives under their desk, that sort of thing. And we're trying to use that to answer a few questions including the amount of storage that we're going to be asked for, but also trying to use that to answer questions about like research data security and risk and that sort of thing. Kara, is what you learned from that exercise terrifying, reassuring somewhere in between? I mean, for us it's pretty terrifying. Just the volume of data that we're really looking at that at this point we're really not prepared to deal with. On the other hand, it's like, you know, what's scarier, the monster that you don't know or the one that you do? I think that it's given us some reassurance that at least we have some data points that we can plan around. Thank you. Hi. I'm Marcel Feldman from the University of Toronto. And one of the areas that we've had success in getting sort of more people working in RDM in research data management is we have a tri-campus committee, but we also have the two librarians who are dedicated to RDM who've actually developed with the committee a method of training, sort of a train the trainers, and so they've leveraged liaison librarians. So between that committee and the liaison librarians, that's worked really quite well in positioning the library, but also in getting people involved in the entire process. So I'm just wondering if either of you or the other participants, if you've done something similar and if you've had success with that? We haven't in data services done train the trainer very much, but I think there's a lot of potential there. Other areas of the library do a lot of training of even students who then are able to train other students and researchers across campus, and it's really quite successful. So I think there's a lot of potential there. I also agree that there's a lot of potential there. Things that the library could, we do have a data catalog that requires metadata and encourages researchers to deposit, it's not a place to deposit their data, it's just a placeholder to point to where their data might sit, whether that's in a repository or elsewhere, but there's opportunities for sure to be able to train others because if that's a way that researchers want to go to make their data accessible, we wouldn't be able to sustain the amount of research and projects that would go into that catalog. So I can definitely see areas and opportunities to train grad students or researchers to input their own metadata to associate in the record. But also all thinking about communities of practice is a way to, hopefully, organically increase the expertise across different units. Mark Laversweiler, University of Oklahoma Libraries. To answer your question, we don't know what's already in existence. We're talking a lot about the new creation stuff. So the answer to your one question, we get a research group that's sitting at six and a half petabytes of storage, and that's not new. That's the archival thing. They anticipate another petabyte within the year. My question is in regard to retention. Right? As we build our staffs and we try to bring in this expertise, there's also what incentives do we have, what advancement opportunities, not necessarily moving into management. In the libraries, it seems to be that's the common thread. You kind of work in the trenches and then you get to a managerial position. There's the whole retention process when you've got expertise walking out the door and you're still trying to fill your holes and then new holes appear. That's a great question about staff and retention of the people who have these skills. And I think we're all seeing that it's hard to fill and retain staff in some cases. But I think certainly revisiting job descriptions and compensation if a job has changed enough. And I think there also are some of those things working on a college campus or university campus that are appealing that perhaps people wouldn't have that opportunity to be involved in. Otherwise, for instance, one of our staff members who provides a lot of our really crucial data support services is teaching a full semester course. And it's just over the moon so excited about that. And certainly it's just an opportunity that he has that I think is important to consider. And identifying those skill sets and professional development opportunities for the staff that are currently doing to advance their skills as well is also something that is constantly on our minds. Mark Jordan, Simon Frazier University. In Canada, Canadian research universities were kind of forced to or compelled to develop research data management strategies as part of the federal tri-agencies, the three main funders in Canada, the federal funders. And this was a great, I think a great strategy on the part of the tri-agencies because it really did, I'm only speaking from my experience at Simon Frazier University, not the experience at my peer universities. But it really forced us to, the outcome of that process was a written research data management strategy that we needed to make public. But that was the end goal. But the journey to get to it was even more important and more available because it allowed us to better know our partners on campus and in the formulation of the strategy to clearly articulate or at least start to clearly articulate where, who is responsible for what? What are the, what's the overlap? Where can we improve efficiencies and improve service to researchers? So I think we were fortunate to be forced to do that. And now we're moving into the operational phase. So the things that we identified as aspirational goals in our strategies were now that we've delivered the strategies, we're now moving into more of an operational phase to kind of get those things going. Thanks so much for mentioning that actually because we've been at SNR, we've been following goings on in Canada quite closely. And I agree they're quite interesting and it's, there's obviously some pretty significant differences in national contexts. But there are a lot of lessons that we can learn and that we've been trying to incorporate into the design of this project. I will say that the second cohort, which is going to be meeting for the first time next month, includes three Canadian institutions. So we're going to have a kind of a little mini cohort of Canadian schools who are working through this kind of next phase of the process that you're describing and I think it's going to be quite exciting to get to see what that means for them. And one thing that I just wanted to comment on was you mentioned how helpful it was to have that strategy that came out of that process but just also how helpful the process itself was. And I think the same will be true with the Ithaca Coordinating Data Services project and that we're really in the very early stages but already just that process of talking with campus colleagues has been helpful. Just hearing about not just challenges with storage but challenges with storing encrypted data and also from our campus colleagues despite our best efforts and the amount of outreach and promotion we do, sometimes they're still just not available. They're not aware of some of the services that we provide that they would find really useful. So I think the process itself will be very, very helpful. Okay. Karim Bogida, Stony Brook University. First, thank you Laura, Rene and Dylan for Ithaca in general for doing this data services thing. And we're part of cohort too. So we're looking forward to working with all of you. My question is probably hard to answer. It's for Rene. You have new AVP data science. So if this position, I believe it's part of the proposed office but if this position doesn't have staffing and budget so it's basically a coordinator and influencer. How can you achieve that? I think it's a first step. The position sits under the provost and our associate vice chancellor for research. So it's a first step based on recommendations from the task force and from the growing data challenges across the university. I don't say or can't say with any certainty that there's not plans for staffing and budget behind that because I agree with you. I think there has to be. And the project here too is perfect timing to be pulling that position in. He is part of our Ithaca project group. So I think the things that we learned especially in this first year and as he's doing other fact finding across the university that the project is going to help inform those decisions as well. Shima Wang from Northwestern University. I want to circle back then about the question about funding model. At Northwestern, in response to this coming requirement mandate university formed some approach. Myself, a student of library and CIO and VPR we become the executive sponsor group to kick off two working group on the data security, research data security, infrastructure, policy, service. So we're working on that. I tried to put my arms around about if there is the funding model to be emerging from this exercise. I have hard time to figure out to articulate what we really need funding for. Is this for repository infrastructure, security, storage, or is this for the human labor on the library IT side or the VPR office side or this is for something else. So my question to the panel is have your institution discussed this kind of issue? Where you imagine the centralized funding distributed to roles and responsibility among the libraries, IT and the VPR office, what that could look like? That's an excellent question. And again, that we're looking forward to figuring that out or at least coming up with a better reflection of what that's going to look like. But from conversations that I have had and what I'm seeing definitely, I see funding needed or money needed to support the data storage. And also as far as staffing goes, again, I'm hoping to identify those gaps to work across campus to find out what needs are not being met and what policies roll out and more and more data requirements, data sharing requirements are needed. What exactly does that look like? And I think it's too soon for us to be able to say that. But again, with this project and these collaborations, that's something that we're hopeful will have a better handle on. But also thinking about what skills are needed for people. I think there probably will be some things that come out that there are skills that are needed to meet some of these demands. But I can't say or speak to what that might be at this point. I would agree with what Renee said, especially not to kick the can down the road, but even in the next few months, we're going to be seeing what type of feedback is provided on some of these early data management plans that have been submitted since the new NIH data management and sharing policy went into effect. What type of additional support do PIs need, that type of thing. So I think once we begin to see how new mandates are impacting the research needs, I think we'll be better positioned to figure out exactly where the funding should go as far as storage and staffing and training. You all thought you had ducked the question the first time I asked it. Not so. I think we have time for one more question. Todd Gropone, associate university librarian at UCLA. And we just concluded a two-year-long research data infrastructure, research data and infrastructure plan. Shimo, it's about $75 million, I think, we're talking about just to get started. Like Pitt, UCLA has a health center on campus, and so it is, you know, we're trying to be comprehensive. And I just wondered, you know, fundings of, I mean, it seems like a lot of money, but UCLA is a $1.7 billion research enterprise. You know, in context, it's not really. I don't think, that's my argument anyway. I'm wondering if you guys have had conversations on campus about funding data services through larger grants, research funding, indirects, that sort of thing. Thanks. That's actually a very interesting question. We, from the library perspective, have not talked about that. We've talked about inserting funding for open access and for thinking about how to deposit data, but not for actually the services. So that's actually a very interesting question. Are you, has that come up at UCLA? Yeah, I mean, because it's logical. If you think about it, we insert ourselves in grants for services such as systematic reviews or the clinical care guidelines that are being published through larger grants that we naturally insert ourselves in and provide the financial resources as part of that grant to support that. So that's actually a really good idea. We are out of time. Thanks so much, Laura and Renee. And also thanks to all of you. Those were a very good set of questions. So thanks for coming. And we at SNR will be providing updates about this project as it develops. As usual, we'll be sharing what we are learning with the community at intervals throughout. So we look forward to continuing this conversation.