 All right, that was fantastic. I'm sure we're going to have some great questions for you coming up our next speaker is Dr Michael Simione PhD associate professor school of complex adaptive systems at ASU. The title is partnering with data and health hubs at ASU. Good afternoon. Thank you for having me. My name is Michael Simione. I'm faculty in the school for complex adaptive systems. And I also am faculty lead in something relatively new here at ASU. And that is the data and data sciences core. And I'm also here to speak a little bit about another new area in ASU called the health observatory. And my main goal for you today is to learn a little bit more about what we're here for and to encourage you to connect with us. If you are thinking about projects or thinking about working with health or health related data, I think. Listening to the presentation this morning, you know, there's, there's possibilities for different kind of work on kind of different levels of product development. I think, you know, if, if you are very early on in your aspirations to work with health data, then I think we are a great partner. I think if you are late stage and you're working with health data, I think we are a great partner, but for different reasons. But importantly, we recognize that projects kind of mature at different phases and have different needs. One thing that's important for the hub for the data and data sciences core is that we are trying to bring together like a confluence of different opportunities and different research efforts around data science and analytics. And this includes and is very intersectional with health data driven research. I think it's becoming less and less distinguishing of a term for different kinds of research. Or another way of putting this is that different data science driven research has different kind of disciplinary interests or disciplinary stakes. And for our part, if you're starting with data or have an aspiration to do data driven work, we want you to come talk to the data and data sciences core at ASU. We have access to data sets and have interest in getting data sets. And we also are interested in kind of working with investigators to build teams or opportunities to be able to do that data driven work. There is an increasing demand. I think one of the reasons we're here today is increasing demand for data driven work from the health space. Some of you have been working in this for decades, but for those who are kind of new or initiated into this, then the opportunity of ASU kind of simultaneously watching a data science core at the same time that it's watching a health hub and a health observatory. Those are important to keep in mind as they're being designed together and integrated with one another. One of the things that is important from the data and data sciences core is support for first mile work. I think, you know, we hear that term a lot. But what I mean when I say first mile work is if you're working at the level of brainstorms and hunches. If you're thinking about opportunities and proposals and you're thinking about staffing and launching that you haven't gotten a contract that awarded yet. Although we do have kind of availability for that as well when when I'll get into that section in a minute. But one of the things that's particularly exciting is helping researchers launch. And that means kind of connecting them with experts who might be able to say operationalize some ideas or hypotheses in data or if we're looking to get data on a given population to help navigate where we might be able to acquire that information. Or we don't have experience for working in enclaves or any kinds of secure compute environments. And we, you know, might have a workflow and in SAS, but we don't have it and are, you know, how can we do some work outside using synthetic data. We're using open source tools to articulate that to the research that we want. And so everything that we work in is open source and try to provide pathways where, you know, we can connect, connect people to more open source work flows where appropriate in a computing staffing launch is another way that we're hoping to kind of tee up and empower research around health and health data. That is trying to provide as much support as possible for faculty and investigators for the hiring process and for getting researchers and research assistance. So that, you know, we have an established lab and we're already dipping into enclaves and we have research assistance and this isn't your problem. But if you're just getting started in the health space or have aspirations of working in the health space, then getting assistance on securing researchers mentoring those researchers, which is something that we do. We've been cohort those researchers that they're working on projects that are related and kind of commissioned working cohorts to be able to complement each other. So if you're only funding one or two students, they're not working in isolation. They're actually working together and you still get that benefit, even if you're just starting off. And then trying to provide pathways where, you know, even if your student, if your grant ends that students career in doing health and health analytics or data science. And they can roll into another project that's beneficial for them to get continuity. And we care very deeply about making sure that students who go through this program are mentored and get a skill set that matters. And that is kind of appropriate with the standards of academic research. And they're not used merely as kind of affordable and approachable labor. One thing that's important for this is that we want to have a common core for getting data for getting access to data and securing opportunities. And so another way to interact with the core is to think about, you know, if you are interested in doing work in data and data sciences and your interest is just in upcoming opportunities. And you're already benched up to do whatever it is that you want to do. Still another reason to talk to the data and data sciences for. We're trying to become a kind of a common funnel for opportunities because as we mentioned before, data and data science research is becoming more and more distributed and more and more interdisciplinary. We're creating a common funnel for opportunities that that approach the university or that are available to folks collaborating with universities is something that's important to us. We also catalyze projects by linking together faculty and like-minded researchers to to capitalize on some of these opportunities. One big headline that there's nothing else to remember today about the data and data sciences core is that it's an on-ramp to work with ASU and ASU resources. And that because we are that funnel for opportunities for data driven researchers, then working through us grants you access to a number of different affiliated and faculty labs. And in ASU we're set up as a core facility where people can approach us or we can help part out different scopes of work to make sure that whatever work has to get done. Even if it can't get done by your lab or your organization, we make sure that within the resources of ASU that we can piece together a mosaic of something that's going to work. And then, you know, not everything has to be about grant funding or grant opportunities. It's still important that, you know, the paths that trace through this organization are able to create some communities and catalyze some new ideas and thought leadership. And as I mentioned before, this kind of common pool of student researchers where we can start building communities around this kind of work. And if folks have managed large scale labs and are already familiar with some of the benefits of this, but the idea here is to create almost a meta lab environment across a lot of different verticals and to make it easier to approach ASU. This isn't a bottleneck by any stretch, but it is a common on-ramp to be able to approach what can be very difficult to navigate congestion of different labs, resources, and stacks of paperwork. We are tightly related with the ASU Health Observatory who cannot be here today as Tim Lant, the Director of Data Analytics and Coordination. The Data and Data Sciences Corps and the Health Observatory have already been working together on a number of different projects. Co-directing the Data and Data Sciences Corps is Sean Dudley, the Director of Research Computing at ASU and part of Knowledge Enterprise. Overall, trying to think about health and health data from a broad and inclusive perspective is important. Our occasion for connecting today is working with VA and VA data. The kinds of data here are intriguing and there are resources in the Health Observatory to work with that kind of data. If you're a researcher that has other interests outside of that and you're collecting other kinds of data though, then there is a place for that in the Health Observatory. And there's definitely cross-collaboration along those kinds of projects with the data hub and the Data and Data Sciences Corps. Also importantly, both the Data and Data Sciences Corps and the Health Observatory have integrations with ASU's melt exchange for resilience and with the College for Health Solutions. And so we try to think about help as vibrantly and as broadly as the researchers do. And so trying to integrate community resilience and public health and medicine and data science all into tightly overlapping circles with shared opportunities and shared operations. And so this Data and Data Sciences Corps has this kind of final visualization and pun on trees just to show that the Data and Data Sciences Corps has these kind of overlapping orbits in a number of corners with the university. And so that could mean something very specific with ASU's Health Observatory. It could take advantage of some of our relationships with ASU libraries or coordinate to perform any kind of outreach and training. We have a vast network of faculty labs and collaborators, and we also have relationships with different student groups, student clubs, in addition to groups on campus that already employ a large number of student data scientists. So that's what I have today. I talked to you a little bit about how to make working with health data or getting started with health data or even catalyzing existing products through ASU a little bit easier by working with the Data and Data Sciences Corps and ASU. If you have any questions or want to learn more or want to get started, you can contact me at the email address here. I really appreciate your time and attention today. Thanks. Thank you so much, Michael.