 As was introduced earlier, this is a demonstrator project that came out of an earlier feasibility study called Hugs. I will just briefly talk through why we thought we needed something like this in broad terms what it does. At the end I will talk about where it is going next. The kind of data that we are interested in is anything related to greenhouse gases. Concentrations in the atmosphere so you are probably all familiar. Dengyrchu'r Wyrdd yn llwyddoedd ar gweithgau Cynllunio Cynllunio Cynllunio Cysylltiad. Gweithio'r info o'r cyffredinol i'w ffordd cynghoriad a'r Llyfrgell i'w cyfrifedd fyddaiau gwneud. ac mae ein bod ni'w gallwch ddif offend y type ffoedd gremigau i hyfforddiant bydd ysgol yn mynd i'naint am hyfforddiant newid ynddo. Rydych chi'n mynd i'n hyfforddiant y bydd y ffigur a'r oed yn gweithio'r ysgol i gydag ffasol gregiau, a bod ystod y gofym oedd gennych oherwydd y Gofymwn ymwneud yn heti, i gael gautio mewn gweithi yn ymdraeth gregiau e wasted a'r pwn yn ddod o'u gwell yn y Yuwngfer. Yn i'n ffarriru na'r roedd, wordd o'r llwydd a'r llwy, That's the inventory. But we can also estimate greenhouse gas emissions using atmospheric data as well. And so that's what's shown in the solid line here. The UK has a greenhouse gas monitoring network called the DEC network. We use this information now routinely every year to evaluate the UK's greenhouse gas emissions inventory report that goes to the UN. Mae'r unig oedd yn fyrdd oedd o'n meddwl i ddweud bod y U.K. yn roi fwyaf gyda'r rysg, mae fydd yn finfolio'r ddweud ar y popeth, y perspektif atlawn'r ymdweud, i ddweud o'r hynny'n dduod ymlaen nhw'n ddefnyddio'r ddweud i'r ddweud. Yn ddweud ymddai mwy ffrindio'r model sy'n ddweud o'r ddweud ymlaen nhw'n ddweud ymdweud i ddweud o'r ddweud i ddweud i ddweud o'r ddweud i ddweud i ddweud, going to predict methane emissions from wetlands for example a system that is really sensitive to climate. Okay. There is all this data out there, why the need for open GHG, there was various challenges we found we were facing all the time when dealing with these different data types, models. The first is we just look for example at atmospheric monitoring networks, each of these different colors here shows some of the global networks that y gall wedi cael eich cyffredig, mae hyn yw'r rhan o'i d verifiedu llawr. Mae'r lidwch ar ei ei dweud sydd o bobi o'r rhan o'r llan iawn, a mae nhw'n gwneud bod ganddoch yr adeiladau a'r adeiladau i chi ar y cyfrifadau sydd. Mewn meddwl pobl, mae'r cynnig i'r cyfrifadau o bobi o bwled ar y cael y ganddoch. Mae'r cyfrifadau eich cyfrifadau neu'r cyfrifadau eich cyfrifadau yn y gallu mas, i chi gyrniad hynny'n cael eu gweld o'u'r adeiladau. So we have this problem that a lot of communities face of standardisation, regularisation of data, dealing with data gaps, etc. The other problem is that the data that we have in the atmosphere is sensitive to different scales. So if we made a measurement here outside in London, we'd be sensitive to relatively small scales nearby. Whereas we have satellites now that are orbiting the earth measuring CO2 and methane for example, which can get a much more broad-scale picture but they're sensitive to the atmospheric column. And these different satellites also operate on different scales. So we need to deal with that. And finally we need complicated models that help us understand these different data sets. So we have different models that predict fluxes coming from the surface and then we have to have atmospheric models which simulate how those emissions, once they're released into the atmosphere, how are they transported around by the wind. So that's what's shown here. So that was the motivation behind OpenTHG. So what we wanted to do was build a set of tools, software tools that allowed us to aggregate data from these various different sources and then produce a set of standards that we would propose for the community for how this data should be treated, what kind of metadata do you need, what kind of structures should this data have. And then we wanted to generate some tools that would allow us to do useful things with that data. So that's what we've been working on for the last few years. I'm not going to talk in detail about the architecture here. If you want to come and ask me about how we've done it, I'm very happy to bore you with all the fine details. We originally started off this process as a cloud-based software stack. The idea was that this was going to sit on the commercial cloud. We were going to port it to the Jasmine cloud. We've now made it more flexible than that. It's a set of software tools that can be used on the cloud but also can be used locally. So if researchers want to download these tools just for use on their own server, on their own laptop, they can do that. It's not an archive on its own. We're not trying to replicate CEDA or anything like that. But what it is, is a set of tools to pull data from public archives and process them into a consistent format and then do useful things with them. And then we've got some researcher-focused tools that then take that data once we've aggregated it and allow the users to manipulate that data. So just to show you what it looks like, you've probably seen these things in Jupyter notebooks, for example. So this could be running on the cloud somewhere, or it could be running on your local machine. There are tools there where people with programming skills can start to interrogate the data in various different ways. It's all been built on a whole variety of open source tools. These are just some of the libraries that are imported into our library. And we have a GitHub organization where people can come and look at our code, fix bugs, propose new types of tool that they want to add to it. And we're trying to grow our user community now. So feel free to visit. The other thing that we were keen to do was once we've got all this data together, we now want us to show people what we can do with it. One of the really cool things that we did was during COP26 in Glasgow, a whole bunch of groups were coming together from around the world to make greenhouse gas measurements in Glasgow at the time to kind of try and showcase what we can do with atmospheric data. And so we used OpenGHG as the live data streaming hub, if you like, to aggregate that data together, standardize it, and then show the attendees at COP what was happening. So we built this tool which showed some of the datasets that were being made in Glasgow. And we added some additional tabs which told people once you've collected this data, what's it used for in the real world. So that was a really nice outreach tool. And as I'll say in a minute, we're also now modifying this for other projects. So that's a very, very brief overview of what we've been doing. And I think one of the most exciting things now is that this project is still ongoing. We've finished our funding from the Constructing of Digital Environment part, but we've now been able to take this project to the next step, hopefully. The main focus is still to try and grow this user community. What we really want is for the greenhouse gas community to take ownership of this code and contribute to it. And we do have external users now. We're obviously using it in our groups in the teams that have helped develop it. But we now have some external users, and we're keen to grow that. We're using the aggregation and visualization methods in the software to help with the visualization for two different projects. We have an international greenhouse gas monitoring network called Agage. So we're just building a dashboard now that will show the Agage data using OpenGHG. And then also the UK DEC network. So I'm going to show a QR code in a minute if you want to see some UK greenhouse gas data. We have that up on the web now. But perhaps the most exciting thing from my point of view is that OpenGHG is now going to underpin what we're calling a prototype operational greenhouse gas emissions evaluation system for the UK. So this is a new project that has just started called GEMMA. It's been led by NPL, but it involves Met Office, Bristol, Edinburgh, various other groups. And the aim is to take what I showed before about pulling together these various different ways of estimating the UK's greenhouse gas emissions. And instead of having this just be part of a two year reporting cycle that happens when we release our UNFCCC inventory reports, what we want is to have an information centre where people can come to and see maybe one or two months in arrears what have the UK greenhouse gas emissions been in near real time. And so that obviously requires all of the types of tool that we have been developing in OpenGHG. It requires data standardisation because we're getting data from a whole different range of networks. It requires tools to analyse that data, bring in different models, different statistical methods, and then present the outputs. And so that's the niche that OpenGHG is filling now. And this is obviously not going to read all this in detail, but this shows the data flow for this new operational system that we're developing. And OpenGHG sits really at the core of this. So we've got two years to kind of prove the concept here with all our partners. And then hopefully if that's successful then this will become, we're hoping, a big picture would be nice if this became something analogous to the weather forecast. If we can have a greenhouse gas reporting system that's operating in near real time into the future. So that's where we are and that's where we're going. If you want to see an example of the data that we're collecting and how it's visualised on OpenGHG, you can use that QR code there. There's also a poster at the back and I've got my laptop that can show you the dashboard on there as well.