Good afternoon. For those who don't know me, my name is Lindsey Jaaks, and I'm a professor of Global Health and Nutrition at the University of Edinburgh. And I co lead together with Peter Alexander, the analytical unit of the Welcome funded Living Good Food Nation Lab, and the principal investigator of that lab is joining us here today as well, Professor Mary Brennan. So after nearly two years of hard work by Megan, who is also presenting today, we are really delighted to share with you this local data dashboard. And the goal of today's webinar is really to just raise awareness of this as a resource and also how it can be used by relevant authorities in developing their initial good nation plans. If you have any questions after watching this webinar or if you're interested in working more closely with our lab on choosing indicators for your plans outcomes, we'd be really happy to meet with you. So please feel free to contact us at our email Living Good Food Nation dot ed dot ac dot UK, which I've noted on this slide. And actually, I think it's on all of the subsequent slides. In addition to the data crunching that Megan has been working persistently over the past couple of years, a huge amount of work went into engaging people who we aim to actually support, sort of the end users that we hoped would actually use this local data dashboard. And so I also wanted to just take a minute before diving in to thank those individuals. That engagement work was led by Tilly on our And we want to also especially recognise the very helpful feedback from various health boards and local authorities who reviewed earlier versions of the dashboard, as well as and recess, who gave really helpful feedback throughout the process. So this webinar is about 30 minutes, and it will be followed by plenty of time, we hope for questions and answers on the dashboard, as well as best indicators. So we'll start off by broadly thinking about how data can help achieve a good Food Nation, really high level thinking about data and indicators. And then we'll briefly introduce nation plans monitoring framework developed by Recess, and we'll give an example of why local data is really important, which will transition nicely into a live demo of the dashboard and how you can navigate the dashboard, which Megan will lead on. And then we'll conclude really quickly with some insights about what we're up to next with the dashboard before moving on to the questions and answers. So just taking a step back to think about how data can be used to help achieve a good food nation. First, I think it's worth kind of going back to 2022 and the Act and the requirements in the Act, which is that relevant authorities publish a Good Food Nation Plan, which sets out the main outcomes and and indicators by which progress in achieving those outcomes will be assessed. And it's these indicators that are really the focus of the local data So what are indicators? Indicators are basically just quantitative measures of either a particular process or a particular outcome. And that's kind of the distinction. The two types of indicators that we tend to think of within the analytical unit. Process indicators which measure what you do or how you do it. So that would be something like uptake of school meals or expenditure per school meal, for example. And then outcome indicators are what you're trying to change as a result. So what are those things that you're doing trying to change? So these outcome indicators could be, for example, fibre intake, trying to increase fibre intake to help meet the discuss dietary goal or something like childhood obesity. So a good plan will have a mix of both these process indicators as well as some of the outcome indicators. And the national plan is a mix of both of these types. So in terms of thinking about, you know, why do we need these indicators or data underlying these indicators to achieve a good food nation, I've just highlighted a couple of things that come immediately to mind when we think about how we would use indicators. One of the things is just informing prioritisation, as I'll talk about with the national monitoring framework, that included 51 indicators in our local dashboard where we kind of have an expanded suite of indicators is, you know, even more than that. So it's a lot to keep track of, and knowing what the underlying data is can kind of help inform what some priorities might be because they may be things that are trending in the wrong direction or where there's potentially, you know, worse performance compared to a national average. So it can help inform prioritisation. It can also, you know, think about prospective monitoring of indicators. It can shed light on whether actions are working. This can relate to documenting assumptions about, you know, the underlying theory of change. Or potentially linking findings on the indicators, particularly the outcome indicators to process indicators or local levers that have been pulled, whether that be relating to public procurement, you know, improving uptake of school meals, that sort of thing. And finally, it can help monitoring these indicators can help build accountability. Just a couple of notes on what we would consider good indicators, and these are very much aligned with what the National monitoring framework outlines is kind of a criteria they use to selecting indicators, which I'll go into in the next section. But just to note that definitely indicators should try to align with the outcomes. As the A mentions, that's really the purpose of indicators is to measure progress towards those outcomes. And if you're including process indicators, they should align with your theory of change. So how pulling certain levers at a local level will actually produce the change you want to see in the outcome. We we try to think about smart indicators, so things that are specific, measurable, achievable within the time frame, relevant and actually are time bound to, you know, aligned with the local plan and the scope of the duration of the local plan. Ideally, indicators should be disaggregated by deprivation, where applicable and feasible to try and address inequities. And then finally, ideally, leverage existing data, though that's not always feasible. So I'm going to go into talking a little bit about the National Good Food Nation Plan, the initial monitoring Framework. This was published in December last year in 2025, and it's a big document, over 100 pages, but it provides a really detailed approach to how 51 indicators were chosen across the six outcomes that were set out in that first national plan, which was also published last year. Useful also is that in this plan and in kind of presenting what the indicators are, they were able to highlight where existing data is lacking and where there aren't existing indicators that could be applied to the six outcomes. And some of the areas that were highlighted in particular were things like food environments, animal welfare, and food culture. And so you'll see when we talk a little bit about next steps at the end of this webinar, perhaps are the things that we're focusing on, particularly food environments. I'll just note that this initial monitoring framework did introduce 19 sub outcomes aren't in the initial plan, which only had the six kind of high level outcomes. But that just helped them kind of really get more specific on where the indicators were mapping onto outcomes in the first plan. So as I said, they had specific criteria that had to be met in order for an indicator to be included in the final monitoring framework. And you'll see these align very much with what we consider to be good indicators as well within our analytical unit. But the six criteria that they included were relevant, so it should actually relate to the elements of the good foundation. Those six outcomes, representativeness. So it should represent key characteristics of those outcomes. Data availability. So they did only include indicators for which there were data already available. They didn't propose any indicators that required primary data collection. Sensitivity. So you don't want an indicator that doesn't change within the scope of a five year plan. So you want something that will really be able to pick up progress on those outcomes. Understanding, so just being understood by stakeholders, including non experts, and then practicality. So it should be cost effective to use and low resource requirements for continuing data collection moving forward. So all the indicators, those 51 indicators had to meet these six criteria in order to be included in the national plan. So I won't go through all 51 indicators, of course. That's not the goal of today's presentation, but just to give an example for one of the outcomes, which is the outcome we're going to focus on as an example in today's webinar, and that's outcome two, which is the kind of environmental sustainability and animal welfare outcome. And you can see here that in that monitoring framework, four sub outcomes were actually kind of delineated. So the first is focused on reducing emissions, specifically from Scottish agriculture, as well as adapting to climate change. The second sub outcome was on biodiversity, pollution, and soil health. The third was the animal health and welfare sub outcome, and then the final one was a specific outcome that highlighted impacts environmental and sustainability impacts of fishing and aquaculture. So for each of these sub outcomes, you can see that there are specific indicators that were chosen that are associated with those in order to assess whether or not we're heading in the right direction for each of those sub outcomes. But the outcome apologies. The indicators aren't perfect. So, for example, if you look at Indicator two A one, so this is greenhouse total greenhouse gas emissions from Scottish agriculture. That is explicitly used as a proxy for emissions from our food system. But of course, we have quite a lot of imported food in Scotland, and so all of the emissions associated with imported food are actually missed by that indicator. And so as are all emissions post farm gate within Scotland. So it's possible, for example, to see progress on this, where you see a reduction in emissions associated with Scottish agriculture. But actually, if we were just relying more on imported foods with higher emissions, you know, if you looked at consumption based emissions, that could actually be trending in the wrong direction. So, you know, none of these are perfect. And our local dashboard, we're hoping will provide some insights into how to interpret indicators for these outcomes. And this is kind of one of the things that we're going to focus on as a next step, particularly agriculture emissions versus consumption based emissions. And then I'll just highlight finally on this slide that there are some gaps. So that final indicator for the first sub outcome on the far left there, the 28.4 indicator on climate adaptation, the monitoring framework notes that they have not identified an indicator that would be practical to monitor for that. So right now there's kind of a placeholder for that indicator, but we don't have a single indicator for resilience of Scotland's food system to climate change risks. So what does this national framework mean for relevant authorities? These national level statistics for each of those 51 indicators are provided in that 2025 document, which is sort of the baseline. And these data will be updated at least twice over the next five years. However, relevant authorities don't necessarily have to use those same 51 indicators. And that document published last year does not include those indicators at a local level. It just has them at a national level. And so that's the gap that we were really aiming to fill with this local data dashboard. And just to really, I think, give a visualisation of why having local data rather than relying on the national data could be important or useful, I just wanted to give an example. This is a screenshot from the dashboard, which Megan will start demoing soon, I promise. This is my last slide, but just an example of why local data is important. And that really is because the national data can hide quite a bit of variability across Scotland's diverse geography. So Um, I think it's really important to look at the local data because different local authorities may prioritise different outcomes and therefore, different indicators to track progress on those outcomes. So just to take one example for outcome two, that environmental sustainability and animal welfare outcome. The national plan, as I said, is greenhouse gas emissions from Scottish agriculture. But of course, different local authorities have different levels of agriculture going on. So this is just a snapshot comparing Glasgow to Dumfries in Galway, which, of course, you would expect major differences there because there's not a huge amount of agriculture going on in the city of Glasgow. Um, whereas there is Dmfries in Galway is providing a significant amount of dairy, for example, to the rest of Scotland. So, you could imagine that these different areas would have different priorities in terms of this outcome. And a place like City of Glasgow would probably, which is kind of the blue line here. So it's showing really low emissions per capita, from agriculture. But if you were to look at consumption, given that it is the largest city in Scotland, you would see that actually it would probably have much higher emissions. And so as the next step, I'll talk about later, we're going to be looking at consumption based emissions because, you know, it's the levers that you would pull to address consumption emissions versus agriculture emissions will be different, and different local authorities may want to focus on consumption rather than agriculture because they may not have substantial agriculture going on. So just an example to highlight that local indicators can be really useful to try and tailor the actions that relevant authorities might take, as well as, you know, monitoring progress based on those actions. So, I am going to stop chatting and pass this on to Megan, who's going to give kind of the more exciting part of this presentation or webinar today looking at the actual dashboard demo, and we'll also put the link to the you'll probably already have this from some of the emails we've been sending around, but we'll put the link to the dashboard in the chat so that you can also explore it yourself. But Megan is going to focus, again, kind of this common thread for the webinar today. We thought would be useful to just stick to Outcome two, though, as Megan will show on the dashboard all of the outcomes. Um our covered outcome six being a more difficult one because it's a global looking outcome, and this is a local dashboard. But yeah, over to you, Megan, for if you want to share your screen to start off with a demo. Okay. And you can see that. All right. So yeah, like Lindsey said, I will be demoing outcome two. I mean, essentially the agricultural admissions that Lindsey has showed a screenshot of. So this is our homepage, and very briefly, it has all of the five outcomes that we feel are most relevant to the local authorities and health sports. A feature of this is that you can go onto the map and click on um a local authority or health board that you're interested in and download a summary of all of the figures and the data in the dashboard, and you can do the same thing for health boards. At the moment, the health board reports you are going to get will be a combination of local authority reports, but we are working on just putting together health board reports for you. So I'll just navigate on to outcome two. Sorry, I had agricultural admissions already up there. So we have summary tabs for each of the outcomes. And this shows you all of the indicators that are in under each of the outcomes in the Good Food Nation Plan. And what we have on the dashboard. So you can see for outcome two, there are quite a few of these indicators where the data just weren't available at the local level, or we extrapolated based on data that were already available through different datasets, for example, for the greenhouse gas emissions from Scottish agriculture. So we took these, um, data from a UK government collected data set, not the same one that was collected by the Scottish government because this just wasn't aggregated by a local authority or health board, and there was no way to aggregate it based on how they collected it. So I will show you this one. Okay. I may have to reload this because it seems to be behaving in an odd way. Let's see. Okay. And there we go. Okay. So here you can see the agricultural greenhouse gas emissions in Scotland 2005-2022. I think this dataset is due to be updated soon, so I will publish the updates. Um, as soon as I can get my hands on that. This page is designed to help you explore agricultural emissions across the local authorities and compare local patterns with Scotland and look at how emissions have changed over time. So at the moment, this page only presents estimates at a local authority level. Health Board estimates are pending, and we will add them in a future update. So the purpose of this page isn't really to provide a full explanation of why emissions differ between the areas. Instead, it gives you a starting point for understanding local agricultural emission profiles and helps you identify broad patterns and then supports baseline assessment for your Good Food nation planning. Okay. So on the left side of the page, you can see a map, and this is the pictures, the latest data available, aggregated by local authority. And right now we are looking at methane emissions per square kilometre. And then on the right, you can see a time series, and this is just Scotland. Okay, so Scotland is always included as a reference point, and then you can compare your local authority patterns against the national pattern without needing to select Scotland separately. So for this demo, like Lindsay showed, I'll just use Dumfries and Galloway, and then Um, Glasgow. So you can select them from the drop down menu. You can also type them in, if that's easier for you. So Scotland here is in red. Glasgow City is in blue, and then Dumfries in Galloway is in yellow. Um, so this will allow you to explore emissions for each of these different relevant greenhouse gases, so carbon dioxide, methane, and then nitrous oxide. So I think this is important to note because agricultural emissions aren't only about carbon dioxide. So in agriculture, methane and nitrous ox site are also very relevant. Okay. So I've selected them. Um, and then we can also look at emissions per capita. If you click on the map here for dumperes in Galloway, you can see in 2022, emissions per capita or 7,075.9 kilogrammes carbon dioxide equivalent per person. And then I can also switch to that on the time series map. So this is all interactive, and you can go through any local authority, click on it, and then you can see the emissions info. And the same goes for the time series. I should note that we're looking at methane now, and this is measured in carbon dioxide equivalent. And if you're not familiar with that, it doesn't mean that methane or nitrous oxide are carbon dioxide. It means that their climate impact has been converted into the amount of carbon dioxide that would produce a similar warming effect over a defined time period. So it just is a way of making them all comparable. And it's usually over 100 years. And that's because different greenhouse gases trap heat differently and are made in the atmosphere for different lengths of time. So CO two equivalent is a standard accounting unit. Okay, so we can then switch. So you can see Dumfries and Galloway has a very high, um, per capita emissions rate of methane, and that's because there's a lot of dairy farming going on there. If you look at carbon dioxide, obviously you see a different pattern here. So local authority emitting more would be Orkney Islands, and this doesn't mean like one is better than the other. It just means that I mean, this is just what the data say. And you can just interpret this as would be valuable to your own local Good Food Nation plan. Um, and then we can switch that to per square kilometre again and see how those patterns change in relation to Scotland. Um. Again, this is all clickable. And then finally, we can look at nitrous oxide. So these emissions would be due to fertiliser use and things like that. FF is a big farming area, so this is generally higher here. Okay. So next, I will just scroll down to this breakdown of agricultural emissions we have by source. So again, we can select local authorities, so we can look at Dumfries and Galloway, compare it to Glasgow City. So this is total emissions. Um, so in tonnes of carbon dioxide equivalent, and you can see where all of the emissions are coming from. So whether it's from, electricity, gas, livestock, or soils, this is broken down differently in the in Scotland's Good Food Nation plant. Again, it's because it's from a different dataset, and this is the data that we have access to at the local level. But, okay, you can see how yeah, Glasgow has very, very low, um, agricultural emissions in terms of total. And then if you click on percent of total, we get a figure like this. So let's see. I mean, most of the emissions here coming from livestock. And then in Glasgow, there's more emissions from gas compared to Dumfries and Galloway. So I think the key message from this page is that it supports a baseline assessment. It allows you to see what greenhouse gas emissions data are currently available at the local level. And again, we can aggregate this to the Health Board level too. Um, And then you can compare this with the Scotland wide estimates and look at trends over time and examine sort of the broad source profile. So I hope that this page gives you a practical starting point for understanding emissions in these areas. Yeah, because it brings public data together in a form that is supposed to be easier to access and let you compare and interpret it for your own good food nation planning. Okay, so I'm going to stop sharing the screen now. I hope that that was useful. Okay. Thanks, Megan. That was really useful. So I'm just going to move to the final section, and I realise we're at our Q&A time, so I'll just go through this quickly so that we've got lots of time for that question and answer section. But just to flag up the QR code and link for feedback. All sorts of feedback is very welcome in terms of the dashboard navigation, but also in terms of any indicators as well. So feel free to fill in the form or contact us on the email that I mentioned. Let me see if I can get my Here we go. So final bit of this recorded portion is looking at next steps. So as Megan mentioned, there's a couple of health board level data gaps which will be filled in where available. As I had mentioned earlier, we'll be filling in greenhouse gas emissions, water use, and eutrophication from food consumption rather than just having what we currently have, which is the national indicators on agricultural emissions. So these emissions which we've derived include emissions from imported food. And we also in the next month or so, we'll have data on food environment. And in particular, what we're focusing on in the first pass is super market access. So to just give an example, we've derived the proportion of the population that's within a 15 minute drive or a 15 minute walk to the to a top ten supermarket retailer, and this will help fill some of the gaps at the National Indicator monitoring Framework mentioned in terms of food environment indicators. We are also working on some micro videos, so videos that are less than 5 minutes long, which can be a sort of self guided resource sign posted and kind of uploaded to the dashboard to help guide, you know, engagement with these data, as well as data in general for good F Nation plans. So the topics that we currently have in progress now just are listed here. So talking about what data is more broadly, how data helps achieve a good food nation, what to measure, and guiding through how to decide on what to measure, where there are resources on existing data beyond our dashboard, how to use the dashboard, building on this webinar, making sense of data, and then finally being careful with averages, where we'll talk a little bit about where disaggregation, for example, by deprivation, could be valuable for some indicators. We very much welcome any other suggestions for topics for these micro videos, particularly after you've had a chance to engage with the local dashboard, so feel free to submit any other suggestions via the form or just via the email that's mentioned again at the bottom of the slide. So we will end our formal recording of the webinar there. And what we're really hoping the second half of this presentation would be is just focused on some broad discussion and question and answer. I realised that I was the person responsible for setting up this meeting, and I have messed up the setup such that I've disabled the microphone. So I think we're going to have to do it via the chat. So if you could I'm going to stop recording now. I