 We're doing good Mike. You want to kick us off? We just started right now. You're good. All right great great. Is there any camera for the room or am I just transmitting to the blind here? You are a disembodied voice. Oh all right. So okay so you can't even see my camera. Nope we minimized you first because it was covering the screen. Sorry. You can't minimize me? Oh well great yeah if um if you're ready I assume we are on slide number two with the research computing and data capabilities model. We are on the first slide. On the first slide? Okay well then yeah I'll start by introducing myself. Well hey thanks for letting me dial in virtually today. I would much rather be there in person both for the conference and obviously for the networking events at night are very fun in DC. My name is Mike Numickie. I currently serve as director for high performance computing at Mississippi State University. We have a pretty robust super computing capability here at Mississippi State University. I think people don't expect to find that here in the south. We have two top 500 systems. We got 45 petabytes of storage so I wouldn't say we're the biggest but we're definitely not the smallest which I think kind of lends us to really kind of talk about how we can coordinate and make research computing and data more accessible and more available to our researchers. So if we could go to the next slide and talk about the RCD model. We're there. Cool all right so if you haven't heard of the research computing and data capabilities model I would highly recommend that your organization take a look at it. It's produced by CARC which is the campus research computing consortium. What they've done is they've developed about 190-ish questions that assesses your ability to research computing and data. And when you think about research computing a lot of people think about high performance computing. They think about the system but the reality is that there's several other aspects you know in this conference is probably primarily concerned about data which is very very important when you're trying to do computer and analytics. So what this model can do is you know just looking at the bullets there various approaches and factors for creating and maintaining an RCD program. So super computing is not just about a computer it's really an ecosystem so it can kind of look at your strengths weaknesses opportunities. It's great to obviously compare to your peer institutions. It helps your VPR feel comfortable about maybe where you're at. And then it also identifies collaboration opportunities with other institutions but I would say today's presentation the actual more important thing is was collaborations within our own institution and how we were able to be more successful there. So if we can go to the next slide we're there. So a little bit about the journey of Mississippi State University. We're really not talking so much about a new process or a new technology but we're really talking about using existing models and frameworks to build a team of people. If you're an attendee of PERC this year's theme will be human power computing because it takes a lot of people to run computers. So previously I mentioned hey you know we've got this system but there's other components to run a successful high performance computing. And this is the actual RCD or research computing data capabilities model that we performed at Mississippi State University and you can see that we actually look pretty good in our system capable system facing capabilities but then when you look at things like research facing capabilities the ability to engage with researchers and help to connect them with the right analytic and data resources that's a little bit weak. Our data facing capabilities our software facing capabilities and then even a strategy those are a little bit weak. So we can now go to our VPR and I found this to be a very very powerful tool to communicate with her on where we should do investment and research computing and data. So just kind of going a little bit more in depth here if we can go to the next slide. There you're good Mike. Okay cool sorry I didn't change my own slide yet. So so kind of you know before we kind of talked about the system facing capabilities the data the software and the research or facilitation these categories further break out to help you better understand where you are more capable and where maybe you need more investment. And you can kind of see here is that when you look at Mississippi State infrastructure systems we're actually pretty pretty strong in those areas and when you look at our system operations we need some help and documentation and I can validate that's true. The other thing is we need help in a change management and version control. I can also validate that that is indeed true. And some of these things right when we evaluate our organizations we already kind of have an idea of that these things will exist but this just kind of adds some you know some finite data to it and it helps you communicate around your organization why you're asking for resources and then it also kind of helps you communicate to those researchers what maybe you can do for them in a more robust way. So that was of the five system face of the five facing system is one that I wanted to talk about and then I wanted to expand on the next slide which is our data facing capabilities. So as we a university as the HPC director we started conducting this evaluation and what we found is we got to the data facing capabilities and it wasn't that we can't do it it was that we just don't know. So I had been attending some conferences over the last couple years and they said hey if you're not working with your library you're probably not doing it right. So I reached out to Dr. Pankle who I'm not sure if she's in the room there but she's definitely at the conference with us today and I said hey have you guys been thinking about research computing and data and they had which was a really great thing to hear is that they were already moving forward in that direction as well and you'll find out later that they have a lot of strengths that we don't have and we have a lot of strengths they don't have and by partnering and you know collaborating that was really strong. So you can kind of see here is that we provide maybe broader coverage that 70% number is that the available coverage to the university but when you look at our data analytics our data analysis data visualization data discovery and collection we're not as strong in those areas. So the great thing about this was it really identified an opportunity for Mississippi State to collaborate within itself to create more research computing and data capabilities. So that's kind of what's you like I mentioned earlier we're really focusing on building a team not necessarily a technology or even a new process and that's where you kind of come to our research team slide up here next. You're good. So you're looking at that research team is you know high performance computing is where I lived in my own little silo and then you know through this analysis we found out about the libraries and really opened up IT services and that's where I will turn it over to my colleague Lauren to go with the next few slides. Thanks Mike everyone I'm Lauren Geiger I'm the digital archivist at Mississippi State University Libraries and so like Mike said HPC and MSU Libraries are kind of the core of this team but we could not do any we couldn't even begin to do this collaboration without the services of everyone here. ITS is crucial for understanding the cyber infrastructure of campus ORSC is up to date on the latest mandates and standards and absolutely none of these talks would be happening if it weren't for our researchers and making sure that we are looking at what they need and doing what we can to ensure that those needs are met and then being able to work and obtain some of their wants. So as Mike said there's a lot of strengths and weaknesses when it comes to both the library and HPC but one of the beautiful things is that they really do balance out. When looking at the library we are really strong in research data management whether you are cataloging a collection or you are processing some archival papers everything we do sort of involves data management on that front. We do a lot of work where it comes to describing data making sure that people are able to not only be able to find it whether it's physical or digital but being able to actually work with it being able to use it. Data visualization is another area we have become very strong in with the accession of our data science librarian Dr. Carolina Sinesh Kouchi. She's another member of this team and we also do a lot of data visualization through our library instruction workshops through our research services which is no longer the word for it and then our digital media center does a lot of technology instructions sessions that involve this. Second we are very service oriented work. Everything we do involves around making sure that our patrons and our users can be able to get what they need and get it in a timely fashion and be able to work with it to the best of their ability. We are really good at making sure that people just are able to get the materials they need and if we can't necessarily find them then we can know who can get them. Third we're really well connected on campus from our subject specialist to our embedded librarians to the librarians who really focus on instructions and orientation work. We have connections to several different faculty and staff members throughout the entirety of our campus. We're also located at the center near some of our largest colleges and that never hurts. The strengths of HPC really focus a lot on where we lack which is the data storage and I'm going to pull up my notes so I can make sure I'm saying everything correct. So when looking at HPC their great strengths really are the data storage and the computational capabilities and knowledge systems. So HPC has a rate enabled disk system that provides nearly 12 petabytes of space for their research computers that can be accessed on almost 800 desktops or laptops. When looking at their long term storage they have an LTO tape library that holds nine petabytes of near line storage. They also have two top 500 computers Orion and Hercules. Orion was benchmarked in 2019 as the fifth fastest computer in the US higher education. They also have a network system across the entire state of Mississippi that connects them from MSU to facilities like the NASA's Stennis Space Center and through and this is all done through the Mississippi Optical Network. Clearly they have more storage compute infrastructure to handle data than any of us would know what to do with. So now that we've gotten some of our strengths out of the way it comes to our challenges and our approaches. One of the biggest challenges we do have on our campus are our silo departments. There hasn't necessarily been the strongest history of pooling resources or collaborating when it comes to these programs or software which can lead to some pieces some resources being purchased twice. One of the things we really want to focus on is building relationships that are focused on RCD and being able to work with the researchers and the staff and the faculty and be able to collaborate with them when we are when looking at their needs. Limited access to software storage and compute is another area that we are slightly that we are working on. When we're to be able to work on this more we are looking at trying to figure out how can we work with our researchers to discover their needs throughout campus. We are actually hosting an event on Thursday called Data and Donuts where we are going to bring together the researchers to talk in a very informal way about what they want to do. The third want is that there is limited staff and faculty capabilities to support the researchers. By building systems and support capabilities through workshops, trainings and incorporating this into their daily workflows we are hoping to be able to sort of fix this issue and be able to make sure that we have the support system in place to be able to build up the RCD that we want to have. The final challenge we can see is recognizing the value of an RCD. I come from a very strong data side. I was the metadata librarian before this. I know all about how to make sure that you can find and make materials accessible and discoverable. I got thrown into the world of high computing in July and so I wasn't quite sure how it could really be that successful or that useful for us but through my conversations with Mike and being a part of our research team I can see how RCD can go beyond the typical like you would think of it being really useful for engineering and for our ag school but how our humanities departments could also really benefit from all of this. So a way that we can approach this challenge is really communicating with everyone not just your senior leadership but your faculty, your staff, your boots on the ground researchers about how RCD is going to help them in the long term. We want them to be able to take all the data that they've collected and that they've spent so much time working for to be able to use it as many ways as possible not just to be able to say okay one and done project put the data on a shelf and probably never touch it again. We want them to see that when they work more on a data management plan and incorporating high compute we'll be able to extend that data lifecycle and be able to make sure that it is accessible and discoverable for as many people as possible. To this end we are working on a CC Star Area 7 planning grant. We are looking to throw this grant to establish specific needs and wants for campus stakeholders. The main goals are to better understand research computing needs so that we can be able to meet them. We are looking at creating a cyber infrastructure plan that will evolve with their needs and be able to accommodate all the growth and change that higher education is naturally known for and then we are also looking to broaden research computing support to be able to create sort of this ecosystem on campus of research and data collaboration. Some of our future objectives here are whether or not we get the CC Star grant we know that this is time sensitive this is important work and we're going to be doing it no matter what but if we do get a lot of data from the grant then we want to be able to use that to better direct our resources and to be able to make sure that we are maximizing our productivity to use a very business speak in a library language world. We are also hoping to create a storefront at the library to assist faculty and researchers so that they can leverage their research and compute needs where this would be librarians who work at the campus whether they're on our team or whether we would start to incorporate this into their work being able to say hey a researcher comes in and says I have XYZ data how can I work with it and we may be able to say well you need to go talk to high compute or okay maybe you need to do some better descriptions they probably come down to talk to me and then our last work around Michael talk about is how we're going to democratize the research. Yeah and I just want to kind of talk about Lauren saying hey I've been learning about high performance computing I got a tour of the library about six months ago and I'm a lifelong nerd not an academic and I always love the library I take the kids there but I found out it was way more than just checking out books it was really really amazing so I do always kind of a I like to throw in there it's like man there's a lot of learning going on here and collaborating these ways is huge and that kind of goes back to democratize research compute data management right is it if you know Lauren mentioned earlier if you're an engineer 100% you probably got access to a computer you know how to use it you know how to apply it but if you're in the digital humanities I think is is what it used to be called you're probably will have less access and then in some cases maybe have less access to the people that could help you take your data and apply some of these analytic techniques that require high performance computing and for instance Mississippi State does have a social science research center and we're really trying to engage with them to find out what kind of data do they have how could we apply it to further their research and their research goals we've met with our anthropology department we've met with our psychology department our biologist so the idea is just to make sure that that that research compute and the data management can be further and wider available to everyone on campus there so thanks for listening and I will turn it over to Montana State. Hi I'm Doralyn Rossman I'm Dean of the library at Montana State University and my colleague Jason Clark is the head of research optimization analytics and data services at MSU library and not to be confused we've got two MSU's here so they paired us up and got a lot of MSU today. So some of you may have heard a talk I gave in the lightning talks in Denver this last spring about this project so this is a bit of an update we're going to give you an assessment of a need partnership formation background and projects and instructional collaborations and specifically this is around the formation of what we've called the research alliance at Montana State so much like our colleagues at Mississippi State we had actually conducted the RCDCM work as well and just to re-emphasize what Mike was covering this is a self-reporting tool so this is our own assessment of how we think we're doing and but it involves expertise from across the institution so we had librarians data specialists IT people participating in it and rather than explaining the whole thing again we do have in our presentation slides that will be on the CNI website a link to our actual report and Jason's going to go into more detail when he speaks and then just make you aware there are five different areas that you report on in the survey and these are the five areas researcher facing data facing software system and strategy and we specifically for this conversation focused on researcher and data facing roles we also took a look at the research cycle so this is a graphic that we made that was modified slightly from other ones we found out there on the web but more broadly you know if you think about the research life cycle there are many different stopping points on the way and frankly people who need help in this life cycle don't care who you are who you work for they just care that you know what you're doing and that you can give them the help and so that was part of what we were seeing as Lauren mentioned in a presentation earlier I heard is that people don't like to be bounced around they just want to find that help and so we were realizing that that was what was happening and so we decided that if we could do some co-location that that would benefit the users but it also would benefit us and being able to do our work better so we can in the research alliance all see ourselves in some portion of this circle here or oval I should say so initially the research alliance was actually floated when my predecessor interviewed for his job as to the dean of the library and 10 years later I got to help see it come into fruition and so this has been an idea because we saw these tensions of around bouncing around and data services were growing we continue to identify potential partnerships through just conversations across the university we were participating in a lot of conversations while we were co-locate not co-located and so that it was hard because it would be once a month once every two months that we were talking as a larger group so we were leading to a commonly shared space which we thought would get us over the hump of having some better oriented services we also identified through our partners we all pitched in money to build a space together and the space allocation it's physically housed in the library which again is in the heart of campus and so that's a really great opportunity we also worked with Rebecca Bryant from the research development partnership at OCLC she has some really good perspectives on what's happening out in the research landscape and so she provided a bit of a mirror to us to see where we were going so the partners that we ended up with are the office of research development so that's our pre-grants award office under the vice president for research the second center for faculty excellence which supports teaching and research and they're under the provost's office the undergraduate scholars program which supports the undergraduate research experience for our undergraduate students also under the provost's office research cyber infrastructure which is in the university information technology vice president's office and then the MSU library and our roads division and jason's the head of that and as the library we report to the provost so you've got the provost's office the vice president for research's office and the cio's office um chief information officer's office all represented in this alliance so that's I think pretty cool um so we wanted to put together something that was a vision and our vision for ourselves is that we bring together expertise from across MSU to help researchers achieve their goals we make your grant proposals more competitive your research more visible provide data management and publishing support and help you translate your research into the classroom we came up with this description of ourselves before we even moved into our space we needed to sort of have an identity for ourselves amongst the group this is our initial floor diagram this is on the third floor of our library and basically it was a space that we just it had been study space and I if you during the q and a if you want to ask me what students think of us taking away study space I'm glad answer that um but this is a mixture of hoteling spaces office spaces teaching spaces um conference spaces and so we actually took this diagram and this is what we've got printed out when you walk in because it's a bunch of different people in different offices and so we've got like jason's over here and oops the upper left in the library space we've got center for faculty excellence across the top but anyway the point is this is a space that we're all together and it creates all these collisions and and good kinds of collisions not vendor vendors we also came up with some tag lines as we emerged as the research alliance uniting research expertise in a single space simplifying faculty and student access to services they'll increase their research impact and then supporting successful research from idea to achievement and your one-stop shop to increase research impact so these are different tag lines we use depending on the context um and then in my last piece here um I wanted to emphasize some of the things we did in sort of going into this one of the things I kept saying to my predecessor is we need a memorandum of understanding we don't report through the same people I'll ultimately to the president but that's the closest to all of us and so we wanted to have an MOU because it's like being a roommate right you're going to move into a space together and what are some ground rules that we've decided upon and that really helped us think through a lot of the logistics of what does this look like in reality from who turns on the lights to how do people schedule with us to what do we do if we want need to buy more copy paper I mean a lot of those little nitty-gritty details um it was a little challenging moving from that virtual to the in-person because we've been meeting virtually for so long that it was suddenly real this summer when we moved in um we needed to define our services and communications so how do we present ourselves on the web do we have an email address um how do people make reservations uh we had some challenges with figuring out what the naming looked like because we've got so many partners um Center for Faculty Excellence ended up having their name sort of pulled out because they support teaching too and so we've got Center for Faculty Excellence and Research Alliance on the big window and then all the partners listed on the next window over um I mentioned the communication channels and ultimately the reason we did this initially was for our users but as Jason is going to say to you there were a lot of benefits that came out for us as partners and so we've seen a lot of new opportunities come forward um and so I'm going to invite Jason up here to cover those and the other thing I'll say while he's coming up here is um there are tremendous benefits to having a lot more faculty coming in the library as a result of this partnership so again during the Q&A if you want to ask me about that I'd be glad to share. Hello and if you had the opportunity um UCSD University of Gartenden um did a presentation on an e-research alliance which is a very similar idea but they're talking about international collaboration so if you didn't see that one um please check that one out on the video because these are similar ideas scales are a little different we were thinking locally with a lot of our collaborations but there's lots of room and opportunity um for for this idea uh so I'm going to talk a bit more about projects and collaborations and the early successes with with this project um again a lot of this comes back to infrastructure you heard Cliff talk in the plenary about what he what what he was envisioning is infrastructure in certain ways but I would posit to the group that parts of our infrastructure are yes computing power but also expertise people and the social relationships we can build locally and uh even beyond internationally um what I'm showing here again is the through line with a lot of this is uh obviously Mississippi State was thinking um further down the line towards a more front facing service we were a little bit ahead of that and we had started that that collaboration and now we're ready we're ready to have that that shop that stop stopping service where people can come in um but that doesn't start without assessment which is part of this another part of this through line and what you can see here is anything you saw in yellow is a tier three in the rt dcm tool um so those were opportunities anything we were kind of below 40 um and identified or assessed as less than uh a tier two or a tier one service um this is a the reason we bring this to to this group is because we found this not only really valuable for ourselves but michael always also spoke to when you're moving outside your environment and you need to show something to the provost and you do this assessment and you can kind of speak to you can benchmark against other institutions this moves people it moves your organization toward change so i'm just kind of i'm not going to spend a lot of time i just want to share the details of these questions are interesting um you can see we had a goose egg on researcher awareness um so one of the first things uh doryland put forward was that we would bring a group of librarian specialists together um so we started with an acronym like we always do um research optimization analytics and data services uh 6.5 fte primarily our scolcom people our open education folk um some data science capabilities mostly um through some some of the work that i do um and then we had our data librarians and um some analysis or analytics folks and in our slides a lot of this stuff is linked um the mo u actually isn't linked but like the roads proposal if you want to see that um so the slides are richer than they appear i'll just i'll just mention that um the other component of this as we did that assessment we started to realize what the activities could be um and you saw that list of five partners and this this ranged from like training professional development mentorship grant proposal development um computing data science all of that kind of going under that umbrella and so those early conversations were about how do you fit all of that into a kind of a singular vision and parts of these activities so you can see on here um the different generic activities that we place these and these have become uh they're they're kind of connected to services that we that we put forward um you probably recognize in those uh that third bullet publication presentation preserve disseminate measuring impact those were those are the places where our roads group really is integrated but um being part and seeing all of this this sort of suite of services has been really beneficial for us and for others in outside of the library so what's happened what's happened is a number of projects and and uh the virtual partnership again the idea had been around for a long time we went through various forms of not only our own internal leadership we uh different people in the provost's office so there was like i just want to present to this group that this there's like a long game with some of these ideas and we we just worked through it and just we had a vision um dorlan was some continuity i was some continuity but we watched and trying to place this uh there were there were ups and downs it wasn't like a straight through line so just encouraging you all if you're thinking about this that that's something uh to just be be patient with but here we are uh we moved in together in in august um which is an interesting question we should probably get to uh with the students asking questions um but immediately these these projects have kind of been in place but they um they also took off as we started to co-locate so you can kind of see we doing things with um research computing around gpu's and access to gpu's so we can build custom models i'm going to show a couple of two visualizations just so you can see this um we can now do we're doing uh there was a need for network analysis on generally like the way research outputs happen and the scholars and how those collaboration networks happen so we were able to do some work to uh diagnose and forecast where how research happens who are likely collaborators things like that um we've always been part of teaching an instruction you can kind of see that there uh we've also been interested in visibility of our researchers we're a land grant with an outreach uh goal um for citizen to engage in citizen science and that sort of thing so this was right in our wheelhouse and then with the undergraduate scholars program we have student mentors and then we also have uh students that we hire into these projects um who are occasionally giving course credit or mentoring and or just the the library is a lab for parts of these activities um what i'm what i'm showing here is one of the first the research analytics and this is a our ability to sort of look at big the big data in i'm going to call a small data in local small data and do um topic clustering network analysis understand where people are um and we were able to actually predict or offer recommendations for who they might collaborate with outside of of the university um and this was connected directly to our center for faculty excellence partners they are looking frequently for who who's a good mentor who would who would if i was going to do research outside of our community where would i go um so these are the kinds of asks and just by being co-located and being intentional about our services these are the kind of partnerships you can start to see um we've also been doing uh visibility in general just general uh how do you how does research and data and outputs move into the ecosystem not only locally but even beyond so this is a small example of work with the office of research development um i'm pausing because they also want they're they're also looking to do some partners like that we do a lot of service outreach learning opportunities and there's a data set that we can do an analysis on now that'll do very much uh answer some of the same questions this is actually about our data sets um in in the building or in that we we curate and i really want to come back around to this and we'll we'll have a little more time um i'm gonna we're gonna ask you questions we want to hear from you too so um this is about people for us um this is right outside my office this is the where the the component where the our partner rci partner is sitting and this is a data science consult and then there's another the student is sitting with another student and the point i'm gonna make with this is that the virtual partnership was good um we had a lot of momentum but the i i'm able to move see say hello if i hear something or they might pull me in and say hey this student is working in this direction do you have projects or do you have a data set that might help us um this is the type of stuff that's happening now with the co-location um it's intentional work to connect so it's beyond co-location these are kind of the ideas i was just making um and then if you if you if you're not familiar with uh rebecca bryan she puts she coined a term around social interoperability and this is really parts of it in practice where we're um thinking along what are the services where do we align how do we align with other partners how are we stronger but then also how do you connect once you're in a space how do you do this socially and uh intentionally so things like open house uh we're part of the research development day which is a training event in january for all of campus um we've done data needs and assessment together there's monthly meetings with shared governance um weekly check-ins and even the the the fun stuff like t times and potlucks um i'm gonna put this is our contact information so you can see lauren and michael and then dora lin and myself these will be on the slides but i also want to just move us to some leading questions and you're free to ask any questions about where we anything you've heard but we also wanted to just try to facilitate a bit of a discussion so if there's something striking you in these questions that i put on on the screen or if you just want to kind of talk about some other things we want we want to hear from you so please ask questions as we turn towards this part of the presentation thank you i have a question related to the rcd capabilities model um one of the things that we hear consistently that it's complex and there's resources that are needed to um leverage the tool and so it would be great to hear from you how you you know got the team together to go through the model was not a part of um ms you doing that because um okay do you mean like conducting the assessment itself or like discussing the results uh both the combination but even just if you just want to focus on conducting the assessment so i wasn't actually a part of conducting the assessment that was done solely by um mike and his team at hbc and then like after looking at the results he brought the library several from the library in and we brought in its and we brought in um osrc but as looking through the model and like just assessing it and taking a look it's very very long but it's not overly complicated you have main bulletin main bulletin points of like here's where your strength is like data facing or data visualization data analysis but then you get to write notes that you create saying okay why were we not strong on this why are we very strong on this and so there's lots of parts but they all feed into each other to create a really good picture so i would say if someone brings you this and you want to take a look at it please don't be intimidated by it yeah and then lauren if i can yeah add add to that so i will say um so lauren you're right i apologize you weren't up front so um deborley associate dean of the library is actually when we got to the data part and i'll tell you so it was a little bit of brute force up front where you're like hey we've got this tool we really need to see where we stand and um we started at hpc and just realized that we didn't have the whole skill set or all the capabilities on campus um and then when we did bring it to the library they provided significant uh help on assessing the data facing portion as well the other thing they did do for us is that we the hpc brought a lot of the software and the system kind of knowledge we were able to go with that through that with the associate dean and just kind of confirm that maybe there wasn't some existing capability that we had overlooked over there i will tell you that you're right this is a data science project and a lot of times the hardest part of any data science project is fighting the data set and it does require some time but i can tell you it is worth the payoff and i will agree completely with lauren is you know once you sit down and become familiar with it yourself as you guide people through it it is not um it is not over daunting uh in my opinion does that does that answer your question for sure i think you know a part of it is convincing the internal stakeholders to participate 100 percent and you know that's that's a bit of an art if you ask me in the sense of you know trying to figure out what do people want and then trying to figure out how that how to convince them this fits in with what they want so um good luck at your institution i i know it's that's a hand car wooden shoe right that that doesn't have a one size fits all i would i would also say our experience can you hear me is this on okay um our experience was a little different was grass roots and so we have an embedded data librarian her name is venice baird she was on a particular grant but she's also very active in the kark community which created the tool um so she recognized the opportunity and we had enough connections but we've kind of brought it grassroots we knew we had a story to tell to the provost and our current dean um but we wanted to gather uh gather information and do that assessment so that we could bring the talking points and we could benchmark ourselves and make the case so you can kind of you can stay here and come down or you could kind of follow our our model either either either could work potentially depending on your culture yeah um thank you so much this was so interesting um so i'm from the university of kentucky and we are opening um a service that is it's collaborative but it's not quite as intensely collaborative as these two examples and um i'm curious i think this is mostly a question for the montana people so when you talk about co-locating the other folks who are not coming from the libraries what what is their percentage of time that's dedicated to this and how did you advocate for that time um so they are permanently located in the library most of them so the office of research development this is their offices like the people that's not what you're more so like if you think about their distribution of effort so are they full time like this is their job they are there to be at this center and help whenever okay so they um all of these entities were not in very great spaces on campus and so frankly at first i think they were just excited about being in a better space and then they were sort of seeing the benefits of actually co-locating so um they we encourage people to come by by appointment so um that's our primary encouragement but people can drop in and sort of we've got office hours that people can drop in but there's not an expectation that they're ready at a drop of a hat so each person in there is trying to hold specific office hours that they're sort of in charge of advertising themselves and we put that on our research alliance website as well we also still have individual web pages for all the entities in there so we haven't like taken away their identities they're just part of a bigger thing so um we do have students that Jason had mentioned when they people first walk in we've got students that we have hired from some of the different partners so that if somebody comes in at least they've got somebody there they can say hello welcome to the center you know how can we help you um so i'd say on average um we probably have each of the people in there you know having five to ten hours a week of more drop in but the rest of the time they're just doing the rest of their work okay and did i insert the study into all your questions yes no that's great thank you yeah hi my name is Cara Watley from Caltech and i have a related question evidently we were tracking on the same thing i was interested in the service models for both of your services and kind of how you developed them um and my experience is on most campuses the library has a different concept of what service is than many of the other units even if they are public facing um and one of the challenges of these kinds of collaborations is getting everybody on the same page for what that means and then i'd love to hear more about your MOU Montana because i think that was brilliant um and if you could just share some more details about it i'd love to hear them thank you i think for the service concept um we were anticipating that this was going to be a challenge because we are so much more service oriented in the sense of being used to people coming up to us without necessarily expecting them so i think i would say would that still a little bit of work in progress but one of the things we had to do is try to create what Jason helped do is create a cheat sheet for the people at the library entry service desk so they could sort of tell people this is what you've got up in the research alliance and then a cheat sheet for the research alliance people to understand when somebody came in looking for a library service how they could refer back out so that's been a real learning opportunity about the work that each other has done um and we do also try to do things like share calendars so that if there's a workshop going on that people understand that that's research alliance workshop um and a lot of that we did put in the memorandum of understanding and we tried to guess on a lot of those things ahead of time invariably things come up that you hadn't come up with but in the memorandum but the memorandum says we will revisit it once a year and so it's not like it's set in stone permanently so i think part of what's helped with the memorandum is that it's really made it as a shared effort so we don't say this is your job it's not going to fall on the nicest person to go take care of this thing while all the other people are doing the more important work it's you know we all own it and i think that set that tone up front this is a jointly shared effort so i don't know if you've got anything you want to add i just want to i want to make sure lauren has because the question was also about services and what you were seeing like how did you set up that model so we're still in the beginning stages the very plain stages so we haven't we don't have the concrete set up like montana does but one of the shared things that montana and i do montana and ms mississippi state does have all the ms us is we're both land grant institutions then that kind of harkens back to the core mission of every one of us because we have extension offices throughout the state so we have around 80 of them i think that's how many 80 how many counties we have and so being able to tie that back into even if you are a behind the scenes if you're not public facing you are still working at a land grant institution the purpose of a land grant is to educate the public is to be a resource for the public and so that getting everyone on the idea of that at least that's an approach that we can handle and we can take going back to the mo u i will make sure to go back to the slides and add a link to that so that you can find the mo u it's not meant to be private it just didn't make it into the slides for some reason and and there are there are there are revisions we've made there are things like we we uh suggested analytics like what would are we need metrics for what does success look like now that's not that's not formalized in the mo u but it is it is a goal right it's part of like yeah we need to be thinking of this so we can continue continue the partnership and see and kind of define define success so this is a question for the folks at montana and i'm curious about what the collaborations look like with the office of research development what sorts of in in you know cross-pollination happens there yeah i think so because i'm kind of buzzing because uh just last week there's there's a new i kind of mentioned it in the presentation but so typically the there there's an outreach branch and then there's a generative like how do you build a collaborative team how do you think about a grant proposal um and both of those those are two of their primary surface surfaces so the the sort of matchmaking or the recommendation of what you know what is what is our research community how does it work those those kind of our our our entrance into that question or that service is usually around analysis of local research okay they're really interested in that that's the the generative side of sure of research development and then you've got the outreach component which are looking they're looking for how do we how do we talk about impact how do we bring the message about this research to the extension agents so that they could could potentially use it um and then most recently just how do we catalog the the outreach of so one of the things we can do with our local local data is understand how what kinds of service partnerships are out there so in the same way that we were doing analysis with something like an output like a data set we can mine that data for the partner and say oh this is a service partnership that exists here's another one these two are related in this way this is the faculty member that worked in that direction so that that component of outreach is is the other piece that we really see from them and it's early it's early um i think there'll be others that i don't even know about yet i think thank you i think the other thing just to add to that is i think we just talk more is just in general call we come a conversation and so we realize that they are helping people pre-grant awards and i don't know how many times i've experienced on campus where people say oh i just put that in my grant right if i just put in my grant that this is where i'm going to store this data and maybe i need some funding to help store the data right so they we are sort of more on their minds at saying hey we can help with data management plans please pull us in when you're at that stage and not have it as an after thought so and a lot of that just sort of brainstorming of how we can coordinate that work so i think if nothing else the library is actively on the minds of the other people in the room and that's partly because we have a physical presence in the space they're not just in the building with us we're in the space with them right so i think that makes a huge difference in just thinking about that whole cycle that i put on not just your piece of it thank you yeah thank you i want to be mindful that we've got actually yeah we have four minutes before the next session starts so i just have one more question as a land grant institution are you working with the other libraries in sharing you know best practices and the processes that you put in place in this are in our states you mean yeah um montana is a really small state relative not physically but land uh institution wise the university of montana is really the only other school that's anywhere close to the size of us and we're we're double the size of them so um so we are willing to do that but i think what we're taking on here they're just not scaled to the other institutions in montana i don't know about mississippi mike and i um during some of our meetings we've talked about potentially scaling upwards but for right now we're trying to focus on just getting the framework around would you agree with that mike 100 percent i i definitely like to get something more established at mississippi state university but i will say mississippi as a state has two other r1 institutes and one r2 research level institute so there are aspirations and i don't want to get too deep into that now but there are aspirations of creating this as a broader statewide capability yeah and i think there's i guess there's potential there for us but we've been kind of inwardly focused up to this point i'd say um thank you all for staying for your great questions and for the collaborations of the msu's so um and go enjoy some lightning talks