 We'll start with a project overview. So CEL is a £6 million five-year EPSRC project, and we've got another 18 months or so left. UCL is leading a consortium of eight partners up at their logos there at the bottom. And their aim is to provide an energy data resource for the UK research community. So that means providing high-quality smart meter and link contextual data for innovative research in the public interest. So we are recruiting and collecting data for around 8,000 to 10,000 households in GB. And we're aimed to be representative of the SMETs to populations, so people with second-generation smart meters. So you're probably aware, high-resolution smart meter data could be a real game changer for research. But there are substantial barriers at present to getting access for researchers. So you've got the technical barriers of actually accessing that data, the legal barriers around the sensitivity to the data, and then the financial costs of getting access. So to counter this, CEL is providing a central resource for the UK research community. So we're already funded. You don't have to pay for individual access to the data. We're providing a secure lab environment. So a smart meter data is personal data. So we've got this virtual environment you can work in. Our UK data service team has overcome the technical barriers to actually accessing the data from individual meters. We provide data linking at the household level. And what I'll mainly talk today is about the observatory data set. So this is the data set of the 8 to 10,000 households, and that is for study on its own, or to act as a control group for your projects. And we're also going to be providing a laboratory function where researchers can recruit their own participants and we'll be able to access their smart meter data for you if you have consent. So so far, we've recruited around half of our participants and we're currently in our final wave of recruitment, so letters went out last week. And we're aiming to reach hopefully 10,000 in the next couple of months. We are open for business. So we've got a UK DS study number 8666, which you can search on the UK DS website, check out all our documentation and some code. And research has already begun. So we have researchers using the data now in the secure environment. So to give you an overview of the different data sets we're using. So there's electricity data and gas data from the smart meters. We've also got weather data, the survey and energy performance certificates. And this combines into what we're calling the CERN Observatory data. So the electricity data is daily and half-hour readings. In theory, all participants should have this. We also have export data if it's available. So if someone has solar panels, we get them their export data. And that's active and reactive power. When people sign up, so they can, they give us consent to access their data and we can go back up to 12 months depending on when they moved into the house and when they got a smart meter. The gas data is quite similar. So again, daily and half-hour readings, but not so many people have a gas mains meter. So that's 70% of our solar participants. The weather data is from the ECMWF and it's irrefiberated analysis data. So modeled based on readings. It's publicly available and hourly resolution 30 kilometers spatially. Initially we just were providing surface temperature but in the next data release we'll be providing up to 920 more areas. And that's a little bit behind the other data sets because it's released quarterly. Now, when people sign up to sell, we ask them to optionally fill in a survey. So that's about 40 questions about the dwelling, your participants and their attitudes and behaviors. And pretty much everybody at least starts the survey and most people are completed. And that's just one-off connection. And finally, EPC, which you might be familiar with, about half of the phones in the UK have an EPC. So we source that externally and it's publicly available but we link all of these data sets together. So now we're going to a little bit more detail about the data you can expect. So we collect the smart way to data via something called the DCC gateway. So that's a messaging service and that sends us the data directly from each household meter. We get the electricity and the available gas data in half hour in daily readings. We also get inventory data. So basic information about the meter although we're not currently making that available for researchers in UKDS, but something potentially for the future. So our team at UKDS collect readings every single day and we then make them available in UKDS approximately quarterly in terms of the files you can expect. So there's daily and half hourly files. So these are reads for each participant for each day and for each half hour with the available energy data. We also create a retype summary table. So for each type of reading for each participant there's the amount of data available with each type of error flag that we've created and some basic re-statistics of the moon and the max. We also creating a participant summary table. So that's a high-level data quality summary for each participant. So that includes non-smart reader data and basic info. And I should say that the energy data includes both the raw data and these error flags we've created and some basic error collection if possible. In terms of the different retypes available. So this table shows you all the different retypes for the daily and the half hourly data. There's some example values in units. And you can find this table and a lot more information in the documentation we've created which is on the UKDS website with the study. I'll just say a few things about the sensitivity of smart reader data. So consumers own their own smart reader data. It's personal data. So we write to participants and get their explicit consent for collecting the half hourly and daily smart reader data. And that's going forward until they withdraw consent or move out I don't have a stated end date for that. And then as I said before historically back up to a year if possible. So most of our data goes back to around 2019 a few of the earliest readings from August 2018. And as we'll talk about later all projects need to have ethics applicable from the university and be approved by the cell data governance board. So the cell survey is answered online or on paper. It's about 40 questions and it's optional. It's mostly multiple choice and then there are some derived variables that we've added in some. So things like the number of adults and the number of people in each age category. And we've also included some error flags and some basic data cleaning. Here's, this gives you an example of the types of questions we've asked. A copy of the survey can also be found on the UKDS website, the study. So things about energy and heating including the heating practices time changes to energy efficiency. Information about the accommodation but the number of rooms when we think it was built. And things about the household and specifically the household at the end. So how they're managing financially if they've got an electric vehicle and they're working status. And then the energy performance certificate data is the publicly available dataset. It's about 80 variables and about a half of our participants have that data. So it's a mixture of practical data for things like the energy rating, energy. And then numerical data like the total flow area in the square. The weather data, as I mentioned before it's publicly available and it gets updated every three months. So it's a re-analysis model of climate data. It's an even space locations, 30 kilometers apart. And in the datasets, each participant has a grid cell variable to link with their nearest data point. So we can do that. And we're moving from one variable to around 20 extra variables in the next data release which will be in a couple of weeks time. So a few things about the data governance board I mentioned earlier. So UCL is the data controller for cell data. The data governance board of the DGB is formed of independent experts. So from industry, government, academia and consumer interest groups. So it's independent from the team at UCL and from cell. So they acted the data owner to review and approve data access requests. And UCL acts as the DGB secretariat and we have a technical advisory role. So in order to access the data it will require accredited researchers, it's only available to UK University employees, legal reasons and access is always within the secure virtual lab environment. To give you an idea of some of the projects we're planning or we started, we've got one project on the COVID-19 impact on energy consumption to see how lockdowns have impacted how people are consuming energy. We've got a project about smart EPCs. So how smartly to data can enhance energy performance certificates or provide a different alternative in use energy performance certificate. And then we'll also be producing an annual report to report on some of our smaller projects in general findings from the data. We're going to be linking cell with the English Housing Survey, hopefully recruiting some of their participants to match up their EHS data with our cell data. Some of our consortium partners have got projects as well. So for example, Leeds Beckett have a project characterizing building thermal response to understand the time spent in thermal discomfort as people wait for their homes to heat up in winter. And it's out hunting that researching habitual energy consumption over periods of weeks and months in order to understand the potential for peak demand shifting. So that gets you a flavor of some of the projects we've envisioned and I'm sure that will be far more that you might be interested in doing. So if you'd like more detail, we've got our website and email address for inquiries. If you'd like to subscribe to our newsletter to get updates about the project. And of course, you can check out the UKDS website with that study number there. So far we just have the conference paper about cell, but we'll be producing a few more publications this year about how the data is collected and the data descriptor.