Good morning everyone. It's just coming up on 10 o'clock, so I'd like to get this event started by welcoming all of you to one of the first events for this week's Celebrate Learning Week. This is the Teaching and Learning Innovation Panel. My name is Simon Bates. I'm Associate Provost Teaching and Learning on the Vancouver campus, and along with my colleague Heather Beringer, Associate Provost for Learning Services on the Okanagan campus, will both be hosting and moderating this session. So in starting today, I'd like to recognize that this is an event across both campuses, and our campuses are situated on traditional territories in the case of the Vancouver campus. That's the traditional territories of the Musqueam Squamish and Salewa Tooth First Nations. And this morning, I'm joining you from my home, situated on the traditional lands of the Katzi First Nation and the Quantland First Nation. And I welcome all of you from the land and the territories and the locations that you're joining this meeting today. I'd also like to start with a recognition that although we're celebrating learning this week, there's a section of our community this week that is mourning the loss of one of our faculty colleagues this week. I'd like to acknowledge and pay respect and sympathy to friends, family and colleagues of Seneca Elliott, sociology professor from UBC Vancouver, whose death was tragically reported this past weekend. And with that, I will hand over to my colleague Heather Beringer. Thank you so much for that welcome, Simon. As Simon said, my name is Heather Beringer I am the chief librarian and the associate provost for learning services here at UBC Okanagan and I am honored to join you today from the beautiful traditional ancestral and unceded territories of the Silkshire Okanagan peoples across both campuses, but I'm going to speak for UBC Okanagan we've been engaged in curricular innovation for as long as I can remember as long as I've been here and well before specifically in the case of the Vancouver campus. We are celebrating teaching and learning it's all of its presentations here and I am thrilled today to be with you to celebrate and showcase some of the recipients of our all 2040 and the TLEF in Vancouver projects. And I will not be labored I will move us on quickly so that we can get to the real meat of this presentation I'll pass it back to you Simon. So, just briefly to review the agenda slide. You will probably have heard this event is being recorded, and it will be shared on CTLT's YouTube channel but comments via the chat will not be recorded. The chat today is we have short presentations from four panel participants. You can feel free to post your questions in the chat, and we'll address them during the Q&A session at the end of the four presentations. This event also has closed captions you can see them by clicking on the CC button in the meeting controls at the bottom of the screen. And there's also staff available to help with any technical difficulties that you may have. I'm keeping my fingers crossed for a strong connection for everyone who's presenting and participating. But if you do have technical difficulties then staff are on hand to to assist with that as best they can. So if we could move to the next slide please. The format today as I said is we'll have short presentations from four teaching innovators across both of our campuses. I'll introduce them one at a time as we go. I have just a few minutes to present some highlights of their project. These are projects funded either by the Alt2040 fund on the Okanagan campus and the Teaching and Learning Enhancement Fund on the Vancouver campus. And then we'll have an opportunity for questions that Heather will moderate at the end. So moving us on, it's my pleasure to introduce the first of our panel presentations from Siobhan McPhee, Associate Professor of Teaching in the Faculty of Arts in UBC, Vancouver. Over to you Siobhan. Good morning everyone. Thanks Simon and thanks Heather. Good morning everyone and welcome to Celebrate Learning Week and thanks to everyone for organizing this panel. I've been very privileged to have quite a number of projects funded by both TLEFs and SALTEL projects over the years, which have enabled me to really innovate and explore different types of teaching and learning in my positions teaching within the Advantage 1 program and then in my teaching in the Department of Geography. And they've explored different elements but it's all been focused around what I term blended pedagogy and are a blended approach to teaching and learning.  The first and foremost is that there is often an understanding that when we talk about blended pedagogy or blended learning that it automatically means the inclusion of educational technologies or emerging media. For me that is a bonus or if you like that's the availability of innovative technology and is a way of enhancing the blended pedagogy. But the essence of blended pedagogy for me is a means to facilitate to enable active learning. So that is first and foremost what I think about when I think about blended pedagogy. And I guess the way I teach is the way that I wish I'd been taught in school. I was a terrible passive learner. I got incredibly bored in my classes. I hated rope memorization. My teacher sometimes stressed me out because I didn't see the point of them. And I didn't like that teachers didn't want me to ask questions. So I took one in my teaching I keep that in mind and try and provide students. I don't always get it right but provide students with a space where that I can address those things that I found most challenging. So that's what the late Sir Ken Robinson talks about as the problematic traditional university approach to the delivery of teaching and learning, which is like we're just, if some of you have seen his animation video of we're producing more factory workers. I find it quite ironic because in the university we talk about the fact that we need to not just create workers we need to create thinkers, but essentially for the last 300 years what we've been doing is is replicating ourselves are creating people to fill certain positions. So adopting a more blended pedagogy for me as I said means embracing a new paradigm of teaching and learning, one that fosters critical thinking, and specifically soft skills, as well as of course, the transmission of knowledge. So students are increasingly as we're aware entering a very precarious employment world where the nature of jobs is continuously changing. And if you talk to people who run co op and various others across UBC, you'll know that employers are more and more looking for those thinking outside the box skills from our students rather than what they can regurgitate in terms of information. So, and as I said for me, this the sense of active learning and empowering the students is it is about giving them the tools to be able to direct their own learning and educational technologies and emerging media is a means of doing this but it is certainly just a tool. And it's a very problematic approach if we start seeing technology as neutral and as the answer to all our woes in terms of addressing some of these, the need for more critical more engaged learners and therefore graduates moving outside of the university. So new and ever increasing technological solutions are being marketed or promoted to educators as a means to their teaching being more relevant in changing times. And we can see that even what happened in the last 14 months or so at UBC with a whole host of new tools being offered to us and and then some of those even being removed very shortly afterwards because of some of the very problematic issues that emerge so thinking about technology in a very critical way. So I suppose that's my premise of what I've been doing. I'll speak briefly about some of the projects that I've specifically been funded by the TLF that I've received. So, initially, the initial TLFs were used to fund augmented reality projects are immersive media so I created an app with a small Vancouver startup company that so in geography field trips are a huge part of our teaching and learning approach. This has enabled students to go downtown at their own pace and engage in the history and the present reality of the downtown East Side and the history of the Canadian Pacific Railway the political economy of Vancouver. And then the second step with the more recent TLF that I've been working on is to create more blended courses within the Department of Geography. So, taking an approach where it's some of it is this is pre pandemic it just worked out in my favor then that some is delivered online and some face to face. But the idea again is that students take on a responsibility for their own learning. And this is done through the use of interactive and emerging technologies, working with I'm just going to briefly share my screen can someone tell me how much time I have left. I think we could ask you just to wrap up in the next minute or social one so we've got plenty of time for questions. Okay, that's perfect then. So just briefly share the screen this what I is what I've been working on for the last year. This is a first year course in geography using tapestry which is a tool developed by Stephen Barnes and various others at UBC. And the idea is the students create engage in these modules, and then we meet and have the lecture so just to give you a sense of what these look like the students take part at complete some very I can share the link in just in the interest of time, complete these activities and then when they joined the lecture, they will have covered a lot of the information that we will then be it'll be more of a discussion and more of a conversation, rather than me, just speaking. So I'll stop there and I'm happy to follow up with any questions during the answer during the question and answer time. And I've shared the link in the chat. Thank you, Siobhan, really appreciate the comments on both the affordances and limitations, or challenges around use of educational technology I think that's something that a lot of it is a lot of us have felt over the past 15 months or so. Moving on, we hop over to the open on campus. Raymond Lawrence is a professor in computer science in the urban K bar the Faculty of Science at UBC up to you, Raymond. Thank you everyone. I appreciate being here. My presentation my project was basically creating virtual labs and a help desk so my area of research and teaching as computer science. And our motivation is we were seeing decreasing engagement in our labs, as you also see in person courses as well. The reason is for many reasons many students it doesn't fit in their schedule they have a lot of other things going on, and often unless you force them to attend the labs with marks or some other reason. They're really engaging with the material that you want. So our goal with this project is try to make a virtual labs and have the technology to help them out. Now it seems kind of quaint right now when this project was proposed before coven where everybody was doing virtual labs and virtual lectures, but the results that we take away from this, I think it's really important, because we all are excited to come back in person. We also all know that it won't exactly be the same and nor should it. We've went through this experience and hopefully that's encouraged us to look at everything that we are doing in terms of our teaching and trying to make it better. And that's definitely the perspective I'm taking and our department and many others are taking that viewpoint. Some interesting results that we got from this and once again it was kind of strange because we were throwing into it it really didn't become a research anymore it became necessity, like everybody else which went virtual. But just some feedback we're getting from the students I'm in computer science I love technology you want to deploy technology, but the students don't want all the different types of technology, they're much happier to do things that everyone else is using. So even though we investigated various software for interacting with users, they much preferred to be using the UBC standard tools, whether that was zoom or collaborate ultra. So unless you have really strong reasons for introducing new technologies, they don't necessarily make the pedagogy better. So that was really interesting from our perspective. The other thing is, even when we go in person flexibility is going to still be the key. Our goal with this particular project was to eliminate the labs overall so that wasn't just a technology aspect it was curriculum as well. We had challenges with scheduling as we did with challenges with attendance. What we ended up doing is we have eliminated the labs for one of the courses and at least one more is coming. And the more we can do the better, because even when we're in person if we can be flexible and allow students to engage the material on their own time, whether that's using technology or not that's really where we want to be at. And so that's really where the focus is continuing to be in the work that we're doing right now. Now ongoing what we're trying to do is build some of that technology what will became obvious while we were forced into our coven teaching is although we have a lot of tools out there they don't all work together. It's hard to as an individual instructor to integrate them into your courses. So for even the ones that we have eliminated the in person labs for the technology is still not ideal. And there's two motivations for improving the technology one is obviously students success and engagement and so we want to introduce technologies that will help that. And the other one I'll be honest when I have a class of 200 students I don't want to mark 200 assignments or 200 midterm exams. So one of the things we're investigating is how we can use technology to mark things that you wouldn't expect. Not just marking multiple choice answers but marking diagrams marking things that are higher order skills is really important so that's something we're spending time doing, and I'd be definitely interested in following up with anybody who's also has those interests. We're trying to look at integrating into canvas, because as I said students really appreciate the integration. They don't want separate tools. So if anyone has experience with that including CTLT and other people I'd be happy to have further discussions with you, and I'll leave it at that. Thank you for having me here. Great. Thank you for those, those comments. Again, one thing, a number of things you said really resonated with me one thing that I pull out is when you said the future is going to look different for teaching and learning after, after COVID and I think part of what will be engaged in the future over the next year or so is figuring out what those differences will look like as we as we turn transition back to the campus. Time to explore that and other things a little bit later in the questions for now we stay at UBCO Asia Ravindran associate professor of teaching in English and cultural studies in the faculty of critical, sorry, creative and critical studies. Thanks, Simon, and thanks Heather and Michelle for organizing this event. It's a pleasure to be sharing this platform with my colleagues from both campuses. So I'm leading an old 2040 funded project in developing a certificate and retro sorry certificate and a minor in communications and rhetoric. And the acronym that we've selected is core. We are working on working with a, with a team of four members, Jordan Stouck, Marie Laughlin, Anita Choudhury and RRA and Kerry, and we supported by an exemplary advisory committee of 16 members from different faculty schools and units on campus so I focus mainly on this particular project. What is our objective are three or funded project supports a development of a 15 credit certificate in communications and rhetoric, which will be piloted in winter 2021 and a 30 credit minor which we plan to pilot in winter 2023. So as you can see from the encapsulated information on the displayed poster. The certificate is open to students from almost all faculties and schools and campus, as well as will be the minor, and both will include interdisciplinary content and perspectives and that was our main focus to encourage conversations between different disciplines, and also to make adaptive transfer between the disciplines. So how do we develop this program. Our Dean Bryce Tracer had already initiated discussions about program development and communications and rhetoric, and it appears in the faculty five year plan, but it required and I use a term from rhetoric here. We have a PROS that is grabbing the opportune moment to bring all the elements together for this project to operationalize. So, we were cognizant of altered student academic needs provincial reports with emphasis on communication skills, the restructuring of the BA and BSC at the UBCO campus. This is the availability of old 2040 funding to make this program a reality. So, the next question is why communications and rhetoric. We believe that these two knowledge strands and practices are intrinsically bound together. And an understanding of the strategies of rhetoric that is the use of persuasion is required to communicate impact fully. How is this program different and significant to student learning. There are three strands embedded within our program design, cross disciplinary perspectives, so that students develop the ability for broader understandings of the use of rhetoric across the disciplines, and in expert and lay context, an expanded repertoire of communication skills, so that it is not focused only on academic writing, but on communication in diverse multimodal contexts that facilitates student navigation and effective communication of information across different genres, different platforms and disciplines. And thirdly, the transferability of these skills to professional context, so that employability and professional development are enhanced. So what is the structure of the certificate you saw that in the previous slide that was displayed through discussions with the advisory committee. We have identified four thematic clusters, the self, the individual and others, the community and the media with specific learning outcomes. Courses are classified in these clusters and students must complete one course from each cluster and a mandatory interdisciplinary capstone. We did three courses last year called to three to four into five communication the sciences the humanities and the social sciences respectively, and we will be offering at least one core designated course in each cluster next year, and plan to develop additional courses in the future. In a final point, students can include two courses from their programs to double count towards a certificate through conversations with all the departments at UBC O we've identified courses that align with the learning outcomes of the four thematic clusters to potentially double count. So that's a brief encapsulation of the program structure and content. And I welcome queries about processes related to the application and implementation of this project during the discussion session. Thank you. Yeah, it sounds like a terrific interdisciplinary opportunity for students. Fourthly, last but by no means least, Larry Leung lecturer and interprofessional education co lead from the Faculty of Pharmaceutical Sciences on the Vancouver campus. Larry, over to you. Thank you for the introduction and for inviting me here today. Before we dive right into the project I want to start off with this quote just to give us a little bit of a jolt this morning because I think it does elicit a lot of strong emotions for people so I want to go over this quote with everyone. What moves to innocence are those strategies or positionings that attempt to relieve the settler of feelings of guilt or responsibility without giving up land or power or privilege without having to change much at all. The concept of a settler moves to innocence was articulated by tucking Yang in 2012. And I think it serves as a very powerful reminder of the complacency that can occur in Western academic institutions. And it's so incredibly important for all of us as Canadian citizens to engage in the collective responsibility, both indigenous and non indigenous to participate in meaningful contributions to this area. So our project is called uproot a community based approach to decolonizing and indigenizing the pharmacy education myself I'm a pharmacist and obviously I work in the Faculty of Pharmaceutical Sciences. We call the the shortened form of the project we call it uproot, because we're really trying to do two things number one we're working to uproot the deep seated colonial structures that exists in our teaching and learning practices. And two at the same time, ultimately, we want our students to uproot their own values their own views their assumptions and their biases about indigenous health and cultural safety. With the ultimate goal of course of creating practitioners that are culturally safe and competent. And so one important element. I really want to share upfront here with everyone here today is obviously I am a non indigenous educator, and I'm operating in this space. And I understand the power and the privilege that I have getting to work in this really privileged space here. This work is built on years of partnership building. And I'm really happy to be here representing the entire team here today. The purpose of the project is really to build strengthen and scaffold indigenous curricula. And we're doing that in two ways number one, building a core pharmacy course on indigenous health and wellness and number two, revamping an elective that we've been running since 2012 into one that uses a blended model of indigenous community based learning and classroom teaching. The curriculum is overseeing by an indigenous advisory committee comprised of indigenous experts and partners and community members, as well as self identified indigenous students. And really what we're aiming for is having the meaningful participation of our partners to ensure the way that we go about building curriculum the way that we deliver curriculum and the way that we evaluate this curriculum, really respects indigenous knowledge and practices. And so one of the key elements of this TLEF project is really the reciprocity with our partners. I mentioned this already that this has been built on probably eight or 10 years of relationship building which for myself and my colleague Jason who's serving as a lead on this project with me really prioritized as sort of our most important element. So one of the key things that we ask ourselves in this type of TLEF is typically when we're building curriculum and you heard me talk a lot about curriculum building. That benefits the academic institution that benefits our students and I'll admit it it will benefit me in terms of sort of my career progression. And so really as part of this project we really wanted to flip the script on that and really prioritize what's important to our partners. And one of the key elements of this is to to build community based projects, really that are based on indigenous identified needs and priorities. And so that's sort of what we're looking to build on first before we start the curriculum building for our students. Again the community based projects will serve as an important opportunity for ongoing reciprocity and for maintaining the partnerships that we value a lot in our faculty. I wanted to just keep my introduction nice and short and really invite any questions during the Q&A period, but that's just a little bit about our project. I'll go a little bit closer later on as part of the TLEF showcase. I'm happy to go over details during that part of the session as well. Thanks everyone. Thank you for those presentations. Heather I'll hand over to you for the for the Q&A we've got I think 79 people in the session, not counting the panelists and ourselves so I think we'll have plenty of input for for a great discussion. Thank you so much for that Simon and I'll remind everyone that you can ask your question by typing it into the chat and I will do my very best to moderate sort of start off perhaps the panelists with a, you know, a starter question will get in their light and maybe we'll use the same order for our panelists that we did for their presentations because I'm a librarian and principles of organizational management are pretty important to me. So I will maybe start with you then Siobhan and ask what motivated you to take on this project and then ask each of the panelists to start us off with that. Thanks Heather. What motivated me is, as I was outlining is really the same motivation that I have to taking a blended pedagogy, which is, I wanted to be an educator that I desperately craved when I was in school and in university. And I think that we, it's actually incredibly challenging to be within an academic institution and be an innovator, it seems to be a contradiction which I find astounding. I'm grateful to CTLT and TLF and for, you know, enabling those of us who want to be innovators and creators within the confines of the traditional academic institution to do so. What has continued to build on your question Heather, what has continued to push me as just the feedback and reflections I get back from my students as I build more of these as I provide more blended pedagogy put more emphasis on the students. They thrive under this rather than shy away from it. I agree with some of the comments that you know they don't want to be overwhelmed with tools that is very true, but they do want the independence. They've just never been really taught how that is and so I think we're kind of starting from the ground up in that way, and I'll stop there to allow others to answer. I mean, can I pass that question to you and both to answer and maybe even build upon some of what Siobhan's put forward. Sure, I really agree with what she said, I think educators were challenged to always do better. And so that's the first thing the reason why did this project I want to keep doing better for the students so they have a better experience and one way of doing that right now is being more flexible being able to accommodate and developing your curriculum your tools in order to do that. And honestly, the second part of it is I don't like marking, which most people don't. So if I can automate some of that and give them better learning experiences that's a win-win. Isha, can I ask if you want to build on that as well? No one loves marking. No one loves marking, I totally agree with them. And I think I agree with what both of you have said with regard to this responsibility that we carry with regard to making changes in the curriculum. And I think one of the reasons why we developed this program was in response to student needs because students felt that it required, the focus has always been on academic writing, but academic writing is only one part of communication. And I think we that's what we wanted to encourage the ability to navigate multimodally using multimodality in different contexts and different platforms. And of course, the other thing was these to encourage these conversations. We wanted to dismantle this wall that exists between a CPSnow one set two cultures. And we wanted to encourage these interdisciplinary conversations. And finally of course, how would it be possible for students that learn specific skills and oral communication or academic writing to adaptively transfer that in different contexts, not just academically in different disciplines, but also professionally, also outside the academic context. And these I think were the main reasons that motivated the development of this particular project. Thanks, Heather. Thanks, Asha. And Lyra, can there anything you'd like to add to that and talk about your motivations? Yeah, that's a great question about sort of our motivations for this project. I think, I think when we look at Canada as a colonizing power and the history in Canada here with cultural genocide and the intergenerational trauma that has resulted in it, academic institutions are not safe from that academic institution have a strong history of colonial based education that's centered on assimilation and extraction of indigenous peoples from their world views and their communities. And despite all of that indigenous communities in British Columbia and across Canada are thriving. And so I think one thing that really motivated us was the fact that there's an opportunity here to take a strength based approach and a community based approach to curriculum building. And so one thing to acknowledge is all of the decolonization, indigenization efforts that we all see across all of our campuses for me is a direct result of the strength and resiliency that is displayed by our indigenous partners and the non indigenous partners that they're working with. And so I think for our project there was just an opportunity for again for us to take a strength based approach to addressing the truth and reconciliation calls to action for health programs to integrate this type of learning. Again, not just for health programs for all programming and also just in response to, you know, even the last report in plain sight about systemic racism that exists in our healthcare system. I think there's a very, very important call to action for all of us to participate in that. So that's sort of what has motivated us with this TOEF project. That's wonderful that's really powerful. We'll remind people I'm going to prioritize questions that come in from the Q&A but don't have any yet. So of course I have another question over Jessica. I'm going to read that first but here's my other question first, which is to ask about the impact that your project or projects I know some have done more than one have had on your own teaching a practice and maybe talk a little bit about a little bit about like what I learned from this project for myself in practice and student learning as well. I'll do the same thing and start with you. Sorry Heather just clarify what did I learn from the project. Yeah, what impact does the project have had on your own teaching practice. Okay, okay. Yeah, I think I'm actually it's okay and also tied in slightly with one of those first questions that came in and because it speaks to that which is, I think I you know I was trained in a in a way of teaching where we are seen as the experts and we transfer or transmit knowledge to our students and what I've learned over the last eight years at my time at EBC is often I'm I'm still a learner myself and always will be, even though I'm also an educator and I suppose an expert in a very small field. So I really have learned to take the feedback from my students. Yes they don't always know what they need or what they want but then again I don't always know what they need or what they want so I think it's a dialectical relationship and I think that anything we build by build I don't mean literally build you know a tool or that but I mean by building courses and interacting with students is that it should really be taking on board reflection and comments from students and that's certainly something that it's also taught me to be more empathetic because I've always been hard on myself as in like motivated and challenged and often students, not all students have the same approach to their learning so it's about being open to different ways of engaging and learning. I hope the other panelists here won't mind if I do pivot to the question that came in in the chat I am going to read it because for the recording the chat is not recorded so I'd like those watching the recording to be able to know what the question was and here it is several times the panelists mentioned that students did not like or want certain things. I'm all for listening to the needs and wants of our students, but I wonder how true it is that often students don't know what's good for them. That sounds old and crotchety, but this is true for many pedagogies that are well supported in the literature, such as spaced practice and more frequent assessments. If students are overloaded, maybe it means we're expecting them to take too many courses. I'd be really interested to hear Raymond maybe I'll pass it to you to start your thoughts about that. Yeah, this is an excellent question and as I mentioned in my opening remarks, we really have to figure out as educators what this new normal is going to be. And that involves taking a lot of different data points involves the knowledge we have our colleagues, other things that have worked in other universities and research. And the students and well, and there's not a perfect answer to this but I think the key thing is to look critically and to look scientifically, it shouldn't be just opinions, you should be doing experiments and figuring out what works and what doesn't on your domain. And just because it worked in one place doesn't necessarily work in another so there's a lot of flexibility that has to happen there. So there's for the particular person asking the questions I don't think there's a right answer, you can say in your course this is the best way to do it. One thing I've learned in my own teaching practice. It's a very personal thing as well. And what works for one person may not work for another as well depending on your personality and your delivery style. But I also believe that you can often sell many things. So if you're truly passionate about it and you know it's going to help the students will buy in you just have to be passionate and sell it to them and convince them. I saw nodding heads issues or something can you add to that or present your opinion on that. I would love to add to that and I totally support everything that you said Ramon because we often accuse the students of plagiarizing or cheating in the exams and we find methods and means to police them and I personally am totally against all of these systems. So I think this is an opportunity for self reflection as well. Students may not always know what's good for them because I often hear responses from students. Oh, you know online asking questions from other students which is the easiest course. So that's not our objective. Our objective is to ensure that learning takes place. So when there are instances of plagiarism my suggestion would be how about engaging in self reflection. I'm not trying to not accuse students of plagiarism but fine means so that we support students and so that they are not compelled to what they're taking it maybe because they're taking too many courses. It may be because the content is is extremely difficult for them, whatever be the reason, I think it's a moment for self reflection and it's a moment to reflect on our own courses as well. Thanks for that excellent question. You have a notice to unmute it so you are ready. Yeah, I love the love the comments from my fellow panelists here. I think, for us, I think that's a great question. I think we're sometimes the challenges will come from is when when programs standardize the way in which we teach across multiple courses. And what ends up happening is, you know, our curriculum is is evidence based I think a lot of us are and the pedagogies that we implement are things that are very well supported by the literature I think the challenges when we do that across all the different courses. So that space practice, multiple assessments, multiple checkpoints they appear in every single course and then somehow we've kind of gone the other way now where the pendulum has swung so far the other way where we're implementing all of these great different pedagogies but now it's looking very similar across courses and I think Raymond had a great point is that you know sometimes those ways of teaching do not necessarily match the educator and what their strengths might be. And so, you know, given for the example that I talked about I think, for example, implementation of indigenous pedagogies for learning are is not just beneficial when we're teaching indigenous content or cultural safety. In fact, many indigenous pedagogies for teaching align with with certain Western methodologies, and they are quite effective to utilize those across other types of teaching as well. So it's a great question. Thanks so much for that. Another reminder, we would love to get more questions in the chat, but I have another that I thought maybe I'd go back to which is a little bit around the projects itself but themselves that you were working on. And maybe to ask you to put your mentorship or peer hat on and see if you have advice for others who might be considering engaging in these kinds of projects applying for TLA for all 2040. Some of your thoughts on the process or advice on what people might think about in preparing to do that. Yeah, absolutely. Two comments. One would be dream bake. You know, don't feel like you have to fit into a box. This is what the TLF, at least in my experience or for it is the ability to push the boundaries. And the second thing I would say is absolutely seek out the support that CTLT offers to go through the process. It's incredibly helpful. And they're pretty honest and we'll tell you if you're on the wrong path. And so yeah, I would say that the support is there and and use it. And sorry, I said two comments. The third thing I would also say is on anyone you speak to it CTLT through the process will tell you this but if you're applying bringing in the voices of students whether it's through doing a survey with them or having them be a part of the application is also very powerful not only in the possibility of getting funding, but also in for your own experience in shaping the project. Thanks Raymond can I ask you the same question. Yeah, I want to echo that the CTLT has been very supportive your other colleagues I want to call out Michelle Lamberson on the Okanagan campus for being very helpful. If you've written grants before I don't think those are as onerous as some research grants. So I really encourage you to do it. I guess my big thing is do it. Get out there and make a difference that's really important not have enough of us are trying to innovate on this and it's great to see so many here. If you have any interest in doing it do it it helps the students that helps your department and helps the university. Do you have anything to add to that. Yeah Raymond I completely 100% agree with you just go out there and do it that's what I would say as well. For us what was really interesting was identifying the advisory committee and having these conversations so we were more or less practicing what we wanted to actually implement through the program. I think that's really important identifying what this project is going to be about but also getting feedback from others on campus so that they contribute to your project. I think our project we even though we discussed it over a period of time it all came together only during the final weeks. So I think it's important to just start working on it. One of the things though that I'd like to comment on is the actual implementation, because our program was completely new. So, one of the things that I would like to say you're planning to work on a new program. Expect the unexpected expect a lot of paperwork expect some frustrations along the along the way. But believe me, you get tremendous support from everyone on campus. You get all the enrollment services, every single person on campus and so it finally works out well in the end. So, identify a project, and just begin the application for the next time. The call is out. Thanks so much, Asia we got a question direct for Larry so I'm actually going to put you on the spot a little bit Larry and ask this question. Can you speak to the depths or commitment needed to build relations with indigenous community and scholars to build relationships and center reciprocity in developing the curriculum. What type of legwork was needed and what was maybe your personal aha moment in that process. That's a fantastic question. I love that question I love that that's sort of the line of thinking that some of our participants are thinking of. Yeah, I think I spoken about it a lot about sort of the partnerships and how it's taking us about eight to 10 years to get through this point. One of the things that's important to recognize. And one thing that I've mentioned before is you really should allow your partnerships to drive the work instead of allowing your academic work to drive what you do with your partners. I think oftentimes with even TLF funding or other types of funding. We often go in with preconceived notions of what we think would be best. And I think it would be the metrics of success that we normally deem are important in an academic institution getting grant money publications, getting great learning for our students. And it's about sort of changing and shifting your mindset to really go in without a particular agenda and allowing your community partners to to drive the decision making process and to drive what projects should be done. And I think that's true for both working with Indigenous partners, but also other community partners. I think flipping the script there is so critically important in building a really strong foundation. And so, you know, for me, that kind of contributed to my personal aha moment. And this happened eight years ago. I, you know, before going into community, I researched the community. I figured out, oh, diabetes is a thing that's happening in this community. It's very prevalent. So I came up with an entire program myself about how we could address this through education and some practice changes. And I had an elder pull me aside and just talk about how incredibly cold and colonial my process was, which was really not centered on that. And I share that because I, I'm happy to be vulnerable and sort of the mistakes that I've made in this process as a non-Indigenous person. I think that was a really personal aha moment for me is to understand that your partners understand their community, their own health, their own practice better than you can, even though you're from an academic institution. And so really, they're the experts in that area. And as such, we should treat them that way. And so that includes including them early on in the grant writing process. It includes ensuring that there are specific line items that are geared towards improving their capacity and education and whatever else they might be. So that's sort of some of the legwork that I think is just kind of go in with an open mind and have some open conversations around what that work might look like. I'm working in areas where I never thought I would work in. And I think that's really exciting. Thanks so much for that, Larry. I'm going to channel speed dating here for one moment and try to do two questions in three minutes really quickly and put the panelists on the spot. I'm going to ask this one to you, Siobhan, because you've done multiple projects, I know, and there's a question about whether you could comment on the most effective methods you might have used to assess how effectively your projects enhance learning. Yeah, yeah, I saw that question. That's a really good question. I think, as I already said, having continuous check-ins with students, so I run halfway through the course survey with students, asking them their input on how they're finding this specific tool that I've designed to have them engage in active learning. And then I do a follow-up survey at the end of the course. And then I follow that with a focus group where I ask for more specific input from students. And I've done that in both my projects. And that has worked very well. You get the kind of broad quantitative view and then get specific input from students. That's great. Thank you. Raymond, there's a key question about whether you have managed to find any applications that support automated marking. There's no perfect tools. I encourage you, Canvas does a lot. If you're in math and science, we have a WebWorks integration, which can do some things as well. But it's still open on some work there. So if other people are interested in that, I'd be happy to talk to you about working on more stuff. And I'm going to sneak in one last one, eating into Simon's closing remarks a little bit here, I'm afraid. But I think it's important. And Asia, maybe I'll pass this to you. I'm going to shorten it a little bit. But to say, do you perceive notions of teaching collaboration projects broadening post-COVID-19? For example, structural changes to courses, programs, other collaborations that meet interdisciplinary or interprofessional learning goals and repeated teaching work of teachers working on making similar goals of inclusive learning, for example. Absolutely. That is our intention as well. And we just started with a certificate. We've, right now, we've garnered feedback from students as well as faculties and schools on campus. But as we develop the minor, this is definitely what we're looking forward to developing collaborations with faculty, with faculties from other campuses to include that interdisciplinary and cross-disciplinary element in course structure, as well as course delivery. Thanks so much for entertaining my speed dating analysis at the end. I really appreciate that. And we are out of time for a Q&A. So I will pass this over to you, Simon, for some closing remarks. Great. Thank you. So I want to start my closing remarks with thanks to all the presenters and all the participants, because the questions that were coming in, these are great questions. And to have to try and answer them in 30 seconds or so really doesn't do justice to the, you know, the depth and complexity of the question. So I wanted to thank everyone for that participation. Maybe just offer four quick comments in summing up. I was frantically taking notes as the Q&A was progressing. The first one is just around the diversity of the projects that these funds support. We shared four with you in this session. You'll have an opportunity after this to look at more in the virtual poster session. But even in those four, there's a huge breadth of pedagogy and pedagogical and curricular innovations that were being talked about. I'm thankful for the way that as an institution, the funds, the alt fund and the TLF really demonstrates this commitment to advancing education and its enhancement across our campuses. And so I think one of the really gratifying things about these enhancement funds is they really support a broad range of projects both in a disciplinary sense, but also in a pedagogical sense. Another thing that really came out for me was teaching as a community effort. And I mean community in the broadest sense there. Every single one of the presentations that were highlighted, the projects that were highlighted were partnerships of some form. Through peers, colleagues, students, central support units like CTL, CTLT, communities outside of the university. And, you know, one of the panelists said, we just want to keep being able to do better. And, you know, I think we could all subscribe to that, but in doing that we recognize that this takes time. Many of these projects have had very, very long runways. Harry who said eight years of building these collaborations with community. So it takes time it takes resources, and it takes support. And again, I think there's there's tremendous community strength. And again community in the broader sense in helping provide that support. Another thing was I saw real connections to institutional priorities, educational renewal program development into disciplinary initiatives and opportunities, Indigenous commitments and our responsibilities to those as we build and enhance programs and curriculum. The first thing I'll offer is I think celebrate learning week has always been for me anyway a moment to work to try and reflect to press pause and sort of take a bit of a wider view around teaching my own teaching and across the institution. And I hope you'll have some time at least this week to engage in that reflection. There are a number of times we heard how really important that is at the moment given what we've been through of the last 15 months I think we really are as an institution at a bit of an inflection point for teaching and learning with many different futures ahead of us. There are no easy answers because our teaching as we all know it's complex is messy. It doesn't always transfer neatly from a research paper to our own particular context. So I really do get the sense that this is an opportunity for us to to reflect on what the future could be and what it should be. I think this brings us very close to time. I believe Michelle, am I handing back to you for some comments on the showcase that's coming next.


All right, well thank you very much today for giving the opportunity to talk remotely. It's really nice to be able to have that option. I think especially when people aren't able to attend in person because I haven't been in apologies for that. Right, so as people said, I'm Richard Onigliffe. I'm from the University of Bristol, but of course we work with lots of different collaborators as many of these projects do. So I'm going to talk today about OpenGHG, which is a community platform for greenhouse gas data analysis and data science. So you're just going to give a bit of background as to the kind of motivations for this project. We wanted to talk a little bit about what we use things like greenhouse gas measurements, greenhouse gas data for. So the most obvious is that you might have seen this sort of plot before where you can see this rise in carbon dioxide. This is in parts per million. This is from the Manilao Observatory, part of the NOAA Global Monitoring Laboratory. And you can see this very steady and perhaps even increasing rise in the last few years for carbon dioxide. So we measure greenhouse gas data. We want to look at it. We want to see what it's doing. We want to look at these global averages that are associated with this information. But we can also use things like the measurements that we've been making in order to try and understand. I'll talk a little about the kind of models we need to run as a part of this. But we want to think about how we can understand things like natural fluxes. So fluxes that we could be influencing by the sort of man-made things that we're doing, but also that are just kind of responding to the temperature changes. It's really important to understand the kind of feedback mechanisms we're getting with those. And also to think about how we can characterize our anthropogenic emissions, so our man-made emissions. So there are various different methods we can use in order to try and characterize the amounts of emissions that we think we're producing. And for instance, you can do inventory methods, which is what tends to be reported to the UNFCCC. But as well as that, you can use measurements in order to try and work out what these emissions are. And again, you can have to run some models, which I'll talk about a little bit in a bit. So evaluating national emissions reports is a really important thing that we can do when we're measuring greenhouse gases. So one of the challenges associated with this, and it's kind of a good challenge to have in a sense, is that we have a range of independent networks and projects. So I've just included here a few examples of that. We've got sort of the national scale. We've got the kind of international scales. This is the ICOS network across Europe. And then we also got global scale networks as well. And then on top of that, there's also different types of measurements. So not just measurements that these tall tower stations or flask measurements. We've also got things like satellite measurements. So as we've had talks today about, you know, the idea of how this kind of remote sensing kind of uses Earth observation. And so of course, you've got that in the world of greenhouse gases as well. This kind of gives you a different type of measurement because when you're measuring on the ground, you're kind of measuring what's coming into your your sensor. Whereas when you're measuring from the satellite, you're measuring a whole column of information. So you need information about how that can tie back to the how you can do these comparisons. You need additional models. And also you can see it kind of gives you this wide range of these different scales of these spatial temporal scales. Yeah. And then finally, we've also got this idea that in order to interpret this information in order to try and get out that kind of that top down that I mentioned. And how do we how do we do that? We can do that by running these sorts of models. And what this is basically showing is what's called an air history map. So the idea with this is this is showing you where the air came from in order to be measured. So where our measurement sites are the blue points here. And this is actually going backwards in time. It's telling us where did that air travel from because that's going to tell us what we're emitting these gases, which is really what we want to know if we know our missions, we can work on mitigation, we can try and improve our our emissions going forward. Okay. So, so I sort of mentioned a bit about this idea of this some sort of use of phrase a few times top down measurements. So do you have these two different ways of kind of characterizing emissions associated with, you know, how we're producing these greenhouse gases. So one of them is the inventory method, the idea of bottom up measurements where you kind of do your counting. You kind of look at the various different sources and you decide what you think is kind of going into your national totals. But there's also this idea of being able to use the measurements in order to try and form emissions. And so what you can basically do is you can use your kind of estimated emissions, you can create these air history maps. So that was the same as that that video that I just showed on the previous slide. And you can use that to create this modeled measurement comparisons. You can say, if these are the true emissions, how well is my comparison looking if I compare that to the measurements? And one of the things that we do is we can use that information, we can run that through various different approaches, Bayesian inversion methods, and we can try and see if we can improve upon this. Can we improve these emissions in order to try and to improve this comparison between the models and the measurements? So just to kind of characterize the typical workflow that we go through when we're trying to put together these these top-down emissions estimates. We kind of go through that data acquisition steps. I talked a lot about the sort of networks that we have, the satellite data. We have to go through these modeling steps. So that's the kind of what I've been talking about with these air history maps that we want a week. In our group, we want a model that's produced by the Met Office called NAME, but other groups will use other models as well. So there's an importance of how you're doing that and how you can compare these outputs. There's also this data model comparison, this idea that you do need to do things like correcting the drift. You need to make sure if you're using multiple sources of data or how are you calibrating those against each other or are they on the same scale? So especially with the satellite and the ground base, we need to be very careful about how we compare those two things. And then also in general, you have this idea that then at the end you can kind of come out with this inverse flux estimate. So you pull all these things together to produce this output. And so you can kind of see, I've just kind of highlighted the sort of considerations, the challenges that come around with this. You have this idea of need for easily easy visualization of lots of memory intensive parts of that. How do you standardize these diverse data sets? How do you consider these different inputs? And largely this has done lots of manual steps as many of these things are. That's how science works. Sometimes you do a proof of concept and then you think about how to automate that later. And also this is largely done on a case-by-case basis. So we'll look at a specific area. We'll use the methodology to come up with some emissions estimates and then our work will move on essentially. And we're not kind of continuing to just keep generating that output in the same way as you would necessarily want to with this sort of work. So what we've basically done is we've tried to think of a good way to be able to deal with these challenges to kind of pull together this methodology. And so this is the basis behind OBGHD. So I've kind of said here that we've kind of characterized this as two parts. So this idea of standardization, this idea of pulling together these different data sources. So having a prior knowledge of how to interpret this information. So like I said, there's global networks, there's regional networks, there's different standards associated with those. And there's also a Bristol we have. We run the the DEC network which is the UK network. So there's the kind of internal standards there. So we want to be able to pull together different data formats. There's also this idea that some of these products are produced in really nice, accessible ways. There's the CEDA archive. There's the ICOS carbon portal.  So pulling from these external archives so that we're not storing the data. The purpose is not for us to store the data, but it is to allow people to be able to compare this data into comparison. And then as well as that, there's also this idea of these, this is the measurements. There's also these additional products that I've been talking about. So these things like these air history maps, emissions ideas, inventories, maps and so forth. Things like what are the global scales of things. And being able to pull that information together is another really key part of what we've been doing. How do you connect these pieces of information in order to try and work on ultimately a pipeline for this, for producing these things? And the way that we built this tool is very much on the idea of open source. In the previous talk, there's obviously talk about Jupiter notebooks. That's something that we have at the heart of what we're doing as well. This kind of idea of a reproducible science is obviously really important. And so we've pulled together lots of open source tools. This is just an idea of how we kind of characterize that. We've got a, we've pulled together lots of, it's a Python based library. So there's lots of open access to be able to look at these things. And also it's fully open and accessible. If you wanted to, you could go and have a look at this on GitHub. All the code is available for you to look at. And we have been releasing that as well. So there is a version that you can download if you're, you know, if you happen to be using Python, you can download that using PIP or condo, for example. And we've also built this with the idea that we want to build it to be extensible. We want it to be something that the community can contribute to. So this idea of transformation, where we go from individual, where we go from kind of these data sources, and we add those to the, we add them into the, into our object store, I don't know what that means in a minute. But also this idea of, of transformation, where we might have various different databases or formats that we want to be able to interpret the information from and then put that into the, the overall thing. So, sorry, there's a question coming through on the chat, but I'll just add a bit. So just kind of go into a little bit into the structure of the way that we have designed OpenGHG, just to kind of emphasize those points that I was going through. So as I said, you can go and look at this yourself if you're interested in having a look at the way that we build this. But the idea is that we have this front end here, which is to do with how we standardize these diverse data formats and store that data. That all gets put into what's called an object store. So essentially that's a database, but one of the really nice things about the object store, and this is kind of a cloud-based technology that we've, that we've adopted with this, is that it's not based on a folder structure. It's very much based on this idea of keywords and searchability. So when you add data, it's kind of, in some sense, it's stored in a relatively flat way. There is a little bit of hierarchy in there, but the idea is that everything is tagged and it's tagged in a relatively standardized way. That means that when you search the database, you can find things that are connected. And also that's a really important part of how we're building this aggregation idea. How can we connect these different things together? We need these overlapping keywords to understand how we can group things together. And so the idea is that you can retrieve data in this kind of fully searchable way. And then also there's this, there's lots of this idea around the front end. So we can retrieve, compare, aggregate, analyze, and create these interactive visualizations. So I'll kind of show that in the next slide as well. And so there's these plotting tools that we have as a part of that. So we are continuing to develop those as we're going forward. But also this idea of this aggregation is pulling together of these different pieces of information. So we can do these comparisons that we need to do if we want to do the sort of science that we're interested in as well. And so this is just a quick demo. So this is actually a Jupyter notebook just to kind of go back to what's been discussed before. And so this here is just demoing how we would compare data from different global measurement networks. So these two networks, one of them we've loaded into our database, another one that we have pulled from an external archive. And so here you can see there's lots of them, I think I'm nitty gritty of the metadata associated with this information about what this is, what does it mean, what scales is this on, who is the data owner, and so forth. And then you can see that we can basically plot that up and we can make comparisons between these different sorts of data, which is often something that people want to be able to do. And this is all done through something called plotly, which is a nice interactive toolkit, which does integrate really nicely into Python. And so you can see how you can zoom in on this, you can play around with the data, you can export images as a part of that as well. And so that idea of that individual science, people can go back and have a look at this, for instance. And then just another quick demo just to kind of emphasize that aggregation idea. So here we've basically got some methane measurements within to really key and important greenhouse gas that's been in the news a lot recently was a focus of one of the COP meetings recently. And this was basically looking at methane measurements that were made and comparing them to potential waste emissions. So waste being one of the sectors, this is landfill and so forth. Can we compare that? So we basically take the kind of predicted emissions, we take these measurements and we say we can compare them. So you can see that there's obviously an offset between these two because it's not necessarily taking in all of the different things that would add up to the total methane, but you can kind of see roughly what the contribution would be in the sorts of things that we were interested in for this. And another thing here, and I kind of mentioned COP there when I was just talking through the previous slide, but here we've got this idea of how we could use, how we have used open GHG for outreach and will continue to do so. And so this is basically something we put together for COP26, which was in Glasgow. It was great.  And what we did is we created an interface that would then allow this live data to be available for anyone who is attending, anyone who is interested could come and see how these different points in Glasgow, how these numbers were changing day to day. So this is the carbon dioxide and what we think. And the idea with this is that we can obviously modify this for other projects. We are very interested in doing so for a lot of the networks that we have as well. And this has been built with open GHG at the back end for this. And so just to kind of also show some of the kind of spin-up science that we've managed to get as a part of this product. This is a paper that was published this year by Alayla Balola, who's a PhD student in our group. So really great work that she's done around how she's been using machine learning tools in order to try and improve the computational aspects that we have. So I talked a bit about how we have lots of memory-intensive steps that need to go into this. So one of those name-intensive steps is this idea of creating these air history maps. They're really important for the work we do because they give us that connection between those measurements that we were making and the potential emissions. But it can be very intensive if, whereas we get more data, especially satellite data, it's great. But it also means that if we're running it for every single point, then suddenly we're getting into big computational challenges or having to scale down that data, which we don't want to do. So this project, the idea here was to try and see if we could use machine learning tools. So using this idea of kind of interpolation. So we would still run our model, but we would allow, we would kind of include some meteorological parameters and use the machine learning tool, train it on these kind of subset of data that we were running in order to produce these predicted air history maps. And obviously we would also want to make sure that that was doing, we weren't losing too much by doing that. So one of the things Ellen put together was this comparison of this emulated generated footprint as we call it, this air history map versus the true name generated footprint. You can see that it does a relatively good job. So I think this is a really nice piece of work to kind of boost. And then this is obviously something that we want to integrate into the tool. She used it to do this, but we can kind of do more with this as well. And the last thing I just wanted to mention is this idea of what we're going to be doing with OpenGHD going forward. So this is a really nice project that's launching at the moment where OpenGHD is going to be used within an automated pipeline.  So hopefully there's a little bit of familiarity there. But the idea is here is that we want to take this entire pipeline that I've been describing, this idea of creating this these top-down emissions, these comparison emissions to be able to do this national inventory comparison. And we want to do that in an automated way. So I kind of mentioned how we do this on a case-by-case basis. We tend to run this and then there's lots of manuals that are required if we want to spin it back up again. But what we want to do is basically take all these steps, take OpenGHD at the core and the heart of this to essentially allow us to start to produce these emissions maps and emissions outputs on a regular basis. We're still kind of designing is actually what that's going to look like. We're thinking about their various inputs for that. We need to think a lot about how we can kind of automate a lot of these manual steps and make sure we're still producing high-quality output. There's lots of things to think about with that. We need to make sure we're integrating different sorts of models. We need to make sure we're integrating lots of different data. But the idea is that overall the product that we've produced is going to be something which is going to be really much at the heart of this. It's going to be able to allow us to create that searchable database to aggregate that data to allow us in order to kind of go through the whole pipeline in order to be able to produce this comparison. And that's everything from me. So thanks very much for listening. Shall I stop sharing now? So I'll set the questions. Do you have any questions on the slide? That's really good. Nope. Any questions from the floor? Anybody? Okay. I have a lot of issues around SQ3 measuring the green light that we chose. Even SQ3. So I want to ask how she's focusing on this measure of green light that we chose. Really, on both points for the national and national government. Then the second question is about, should we mention of some organizations, some, you know, international organizations that are measuring green light for the nation? So I want to ask if you are a venture, you are using your model, or you're using your data system with campaigns, for example, a graph method or probably the GSG protocol. And at the end of the day, you find out that your data set has some outliers. And how are you going to run that? So I think, Rachel, the first of those was how are you going to use this tool to very measure greenhouse cash flow, the different conditions. Is that right? Yes. And the second was how are you going to deal with the discrepancies between different measurements from different sources? Okay. Yeah. So I think the one other thing is to kind of highlight when it comes to this tool is around where it kind of sits on that pipeline that we've been talking about. So one of the things that we do work quite closely with the people who make measurements, or at least one of the communities that make measurements specifically in the UK. And so they want to be able to use the tool to feed in some of these, their raw data, and to kind of go through their calibration levels in order to make sure that they understand how the data, what the data looks like to make sure that looks sensible. So I say that one thing is that for a lot of the networks that we would deal with, we would be sitting after that stage, because when you're measuring from different inputs, the standardization is going to be happening prior to it coming to us. We would generally be dealing with level two products. So we level two products from satellite data and also dealing with the kind of the validated data in a lot of ways as well. And so in a sense, it kind of depends on how you want to use the tool, because we're not going to be making prescriptive decisions about if your data looks right, you have to decide if your data is doing the right thing. And so we just want to make sure that we're providing the tools for you to be able to do those comparisons and to make sure that that makes sense. So there's lots of calibration that goes on with regards to, so in the DEC network particularly, they do lots of work on calibration. They scour the data. They make sure that it looks sensible. And in terms of different scales, these things are known. The calibration scales are known in advance. And so if you want to be able to compare different data sets, then as long as we know the calibration scales, it's easy enough to make sure that we're making them comparable with each other. And when it comes to things like comparing against column data, so when we're looking at remote sensing, for instance, this is why we want to run these air history maps, because we can look at the measurements and we know that there might be some sort of bias between them because that's kind of known. There's a lot of work that's been done on that by the way, like about trying to make sure that there's an understanding of the various differences between the way that things are measured on the ground and the way that the satellite data is measured. But when we're running the models, when we're thinking about how we get out these emissions inventories, we can do things like allow for a bias parameter between those two things and that can be solved as a part of the inversion. And then we can use that in order to understand what differences there might be. And that would also characterize differences in the models as well. So not just a genuine bias in the data, but also a potential bias in the way that these, the way that the model has been run for these two different types of inputs. So I think that that eventually kind of sits at the heart of all of those things, but there's obviously got to be input from other people in order to try and make those things work. Your first question for Rachel. Yes. Okay. So, Rachel, we had a workshop on data ownership and recognition earlier when federating lots of data sets, how do you ensure they get properly cited? It's a really good question. I mean, I think that one of the things that I wanted to emphasize as a part of this is that we're not trying to act as a data store.  So in terms of citations, when you're pulling from these external archives, all of that information is going to be included, especially for instance, with ICOS is really good with this sort of thing. So when we're pulling this information from ICOS, all of the information about how to cite that data is going to be there. Similarly, when you're running from, so the NOAA network has what's called an observation pack that they run. And similarly, they have really good metadata in there. So I think more than anything, we would say if you want to make sure you're citing data, go back to the original source. Don't try and use us as a place to understand how and where the data came from. Use us as a way to kind of look at the data to visualize the data, but you're always going to be wanting to make sure that you're citing it from the correct external resource or the paper that is associated with that data. And so as much as possible, we try and make sure that metadata is retained and that information is always stored so that when you're grabbing these data sets, it'll have information about where that data came from. But I would definitely say that people need to make sure they're doing this properly, and they're going to make sure that the data is cited from the correct places. There's a question from Lou Dowrick. So thank you for a great talk. Do you employ common metadata, for example, community-recognized vocabularies to promote interoperability? Oh yeah, that's a really good question. So one of the things that we've really been trying to make sure that we adhere to what's called the CF compliance standard. So we're kind of going through the moment in trying to make sure that that is being applied correctly in lots of places because there's lots of things around various terminologies to do with the way that the attributes are stored and X, Y, Z. So yeah, so we very much do try and make sure that we're adhering to those standards. And in a lot of the projects that we work on, we do work with some of these other communities and they're really big on making sure that these standards are correct. And so yeah, it's definitely been something that we have thought a lot about and is at the heart of what we want to do is to make sure that absolutely we're trying to make sure that we're adhering to this terminology. I can't guarantee that we always get it 100% right, but we're definitely trying to make sure that we are. Okay, another question from Matt Bright. Will you use cloud resources for people to run analysis and if so, which platform will you use? That's another really question. So when we initially started this project, we were hosting on the Oracle Cloud. So that was for the two-year original set of funding and so that tenancy ended because these things, you tend to buy it upfront. So we have a tenancy on Jasmine Cloud that we want to, whether we are in the process of trying to move over to at the moment, that's a bit longer than we hoped. So in terms of hosting, Jasmine Cloud is where we want to be. In terms of actually being able to run a lot of the tools, if it were possible for us to kind of, we need to talk to the guys at Jasmine and kind of decide what's feasible because I know the job in Cloud and it sits outside the kind of Jasmine infrastructure. And so with that, there is batch computing that kind of sits in the background. So when the cloud resource itself there's always limited ability to be able to run these kind of big intensive jobs, but lots of kind of visualizing data, looking at the data, doing this aggregation, that's all totally feasible in a cloud platform. If you wanted to be doing some of these bigger modeling steps, then we'd probably think about how to link up with HVC resources if possible. So Jasmine is kind of going to be the home for this going forward following the kind of finishing of the Oracle Cloud tenancy. There is the slight downside of that in that Jasmine tends to be UK focused collaborators. And so obviously we would like this to be something that's successful internationally. So it's something that we will need to think about a little bit if we're kind of limiting ourselves if we're hosting this on Jasmine. But I think that long term hosting on somewhere like Jasmine is better as we found than a commercial cloud tenancy. So do you think that that seems like the best approach for us going forward? I have the question. I think it's come from the chat. The Yara asked, is it possible to use this tool to compare local areas in the UK? Are you set a resolution question there? Yeah, for sure. So it depends on what data you have and what data you have available to you. Because obviously, if you're talking about things like local areas in the UK, there are some fantastic data sets that exist. There are some of the people that we work with at Crumfield who have these beautiful data sets to do with land data. But that's kind of primarily focused around certain areas of the country. So you'll get some areas that are really well mapped like London, for example, but you won't necessarily have this really good mapping across the entirety of the UK. But we also have things like, there's a model called UK GHG, which is a, Pete Levy runs that model at CH, I think he's at. And that's a really great model. That is kind of trying to do this higher temporal, higher spatial resolution over the UK specifically. And so yeah, that's something that we've been integrating as much as we can. So at the moment, the product is still run, it's an R-based model. It still run externally from open teaching. We don't run that model. But if you produce, if that model was accessible, so if you run that and then you produce the output, you put that into the tool, then yeah, absolutely, you can use that if that's on a resolution that you're interested in to be able to do things like comparing different areas, you could define different areas that you're interested in looking at cycle. So yeah, that would be definitely feasible. We don't have the ability to do it at the moment, but that's why things are scalable and extensive.