 Thank you, buddy. Welcome to a sunny Manchester. I can't tell, obviously. So this is what I'm going to cover today. Very brief introduction to the UK data service, generally. The main bulk of the presentation will be about the international macro data. We'll give you some examples of the data, tell you about each of the different types of data provider, tell you about the documentation, give you some tips on using the data. And then we'll have a live follow-along demo for accessing the data at the end. And then right at the end, we've got any questions. You can ask questions as we're going through, type them into the Q&A box, but we'll answer those at the end. I'm going to turn my video off. And we'll just share the screen. OK? There we go. OK. So what is the UK data service? We are funded by the Economic and Social Research Council to provide access to important secondary social science data, the sort of data that hopefully you want to use in your research. And we provide all the support training and guidance to use that data. We have a huge range of data. I'm not going to go into all this. But it's more than just the international macroeconomic data. We also host data sets produced by researchers. So if you are funded by the SRC, you are obliged to offer any of the data that you produce to ourselves. And then we will catalog that and hold that for others to access. So this is our website. The important one here, actually, I'm just going to share I'm going to go to this live. Good to be daring. We go to the UK data service. Training events, obviously you'll have been there because that's how we find out about this particular webinar. Our learning hub, lots and lots of really good information about how to use our data and help really useful because, actually, really useful FAQs there. But also, right at the bottom, we've got the help desk contacts. If you want to get in touch with us and ask us questions, you can. And there's details on there and how to get in touch with us. It goes to a general help desk and then it gets rebooted to the subject experts. So the international macro data is data about countries and aspects of those countries. So there's also, I would say, there's also a small amount of sub-country data as well, regional level, usually, or metropolitan area. The data banks typically contain time series data produced by international governmental organizations. All the data are available free at the point of use for staff and students at UK universities. Also the House of Commons Library, House of Laws Library. And almost all of it is open. So everyone can use it. You don't have to be at a UK university. There are some data sets that are only available to members of staff and students at UK universities and colleges. We'll go through which ones those are. But even those ones are simple to access. You don't need to do any difficult registration for that. And they're still free. So our data providers are very large NGOs, international organizations. And they are the gold standard of data providers. They have a presence in every country in the world and the power to create international standards, create statistical infrastructures, and provide the technical assistance for those data sets as well. We have licensing agreements with all these organizations so that the data they produce are free to the UK academic community. So a huge range of things that our data covers are not going to list those out. But you can see it comes just about everything. And this is what it looks like in our data system. It is data at a geographical level. In this case, it's metropolitan areas, displayed as rows, and the years as displayed as columns. And then we have a single subject. So it's the turcal population of the metropolitan area. It's possible to display more than one subject, many more than one subject. And there's also the ability to rearrange the dimensions as well so it looks suitable for you. So World Bank, IMF, OECD, and UNESCO data are open to everybody. The United Nations Industrial Databases and the International Energy Agency data are restricted to UK, FEN, HE staff, and students. Access is via federated access. You probably don't know what that means. It doesn't really matter. It just means that you use your own login for your local university or college. And the data is delivered over the web via a package called ukds.stat. .stat is an application developed by the Organization for Economic Cooperation and Development in association with lots of other international statistical users. So people like the National Bank of Belgium, the Australian Statistical Authority, Stats Canada, and ourselves. So we all cooperate on what we would like the interface to do what to look like and OECD go away and make that for us. Download formats, all the popular ones, really. When we do our little demo, I'm going to start at the catalogue records. And so you can see how to access the data from a search, basically. So we have catalogue records for all our data, and not just for the International and Economic Data, all the data that the UK data service holds. And all of the catalogue records will have an access data button up in the top right. So you can use that to go straight to the whatever package that the data is using. There are also all sorts of metadata in there about the data. So there's very often a data set user guide in there and details on how to cite the study. It will also tell you the access arrangements for that data set. And that's a link. So you can click on that and find exactly what it means by open. There's the access data. OK, and this is what it looks like when you first go to ukds.stat. And that's the web address in the bottom there. Data providers on the left, and you can expand those links to show all the data sets from those data providers. There is a login at the top here. But for those data sets that require a login, it will also prompt you. And this is what it looks like when it's populated with some data. So again, on the left, we have the data providers and data sets. On the right, we have the metadata panel. And in the middle, we've got the data display. And we'll go through that. And we'll show you how to use that in our demo at the end. So the World Bank collects data on all aspects of human development. It's annual data. It's designed to be comparable between countries. It's all open access. And we have the world development indicators, international data statistics. The African development indicators is now deprecated data sets. And that's been all the indicators in there are now within the World Development Indicators data set. But we keep that on for historical reasons. And there's some national population database as well. So the World Development Indicators is possibly one of our most popular data sets. Highly cited, provides a broad picture of poverty trends, development indicators, use of environmental resources, performance of the public sector, labor market, infrastructure, health, education, and gender. Huge range of indicators for every country. So it's well worth having a look at the guide that's within the metadata. So this is an example of the data. This is the percentage of population using the internet from 2011 to 2019. This is data taken from the version of the data set. We've actually got 2021 data in there now. So a little quiz now to get your brain thinking. So this is using data from the World Development Indicators, which country had the largest proportion of women in parliament during 2019? So if you go to www.menti.com, I put in the code 21327445, you'll get a little poll to fill in. And hopefully we'll get some answers. OK. So that is Bolivia. Bolivia had the highest proportion of women in parliament during 2019. And that data is taken from the proportion of seats held by women in national parliament's subject from the World Development Indicators. Oh, sorry. Rwanda had the highest proportion of seats. So 61% of seats were held by women in the National Parliament of Rwanda in 2019. International debt statistics is a global database on debt and aid. It focuses on the flow of money, trends in external debt, and interest payments. And there are over 200 different time series indicators from 1970 up to 2013 for most reporting countries. And pipeline data for scheduled debt service repayments on existing commitments up to 2022. The subnational population database is time series population estimates for 75 countries at the first administrative level for each country, so provinces, states, regions. Data is available from 2000 up to 2016. And you could lose the total population numbers for each country and the shares relative to total national population estimates. It allows researchers, students, and practitioners to investigate population and intra-country migration trends by comparing population changes over time for 1,350 subnational regions and allows you to study the size and structure of a country's population. This is what it looks like. So this is Belarus subnational data for different regions within Belarus. The IMF data banks international monetary fund. The primary purpose of the fund is to maintain international financial stability. And the data it collects reflects that theme. The fund collects detailed macroeconomic data from all its member countries. And it's watching out for financial crises and balance of payments difficulties. So these are the five major data banks produced by the IMF. Collectively, they provide a global picture of economic development and international trade over the last 50 years. And all of these data sets are open access. So anyone can access this data. So the IFS is the principal statistical publication of the IMF. And it's the standard source for all aspects of international and domestic finance. It's produced every month since 1948. Its data is monthly, quarterly, and annual data for over 200 countries. It's a reference publication. So the exchange rates used in the IFS are used as the basis for conversion for all the United Nations data banks and World Bank series. It has got three sections. Country tables, where the data is fairly raw and unprocessed. It's not designed for making comparisons between countries. It's more for benchmarking countries for their own progress over time. They pull the more comparable series into the world tables, which also has commodity prices for oil, coffee, gold, and wheat. This is an example of the sort of data within that. These are the world's total reserves of gold in US dollars at market price. And so basically you can see the value of gold over time from 1950 up to 2020 with quite a deep dip there after the financial crisis of 2009. Direction of trade is data on the value of exports between countries and their trading partners. For each country, it lists every country it trades with and the volume of trade over time. So that's 250 countries and 12 regional groups. It's monthly, quarterly, annual data. Most countries data extends from the 1980s to the present and it's great research potential for economics. It's authoritative, it's long, it's got a consistent time series data. It's a good subject country and temporal change coverage and the data is harmonized and comparable between countries. It is a huge data set and it looks like this. So month and years across the top, the data starts in January, 1980, runs up to a few years behind present day. So what we have here, we've got the reporter country is Canada. We have all its trading partner countries and it's the value of exports per month from September 2015 up to June 2016. So there's 250 countries and all the groups that it trades with, all the countries and groups, reporting exports and imports. So there are around 125,000 time series, around 3.75 million annual data values and 52 million monthly data values. So it's an enormous data set, one which is very good to see in UKDS.status because we can split it down to its constituent parts. The balance of payments statistics is a time series data set covering the standard balance of payments components and international investment positions of countries. Most countries data extends back to the 1970s to the present date and that's quarterly and annual. And the government financial statistics tells you how it gets its money and how it spends it. Come as data, government income, such as taxay, debt, expenditure by sector, so defense, education, health, et cetera, for all levels of government, so national, state and local government. There are 174 countries, it's annual data, runs back to 1990 to present date. And the World Economic Outlook is a report presented by the IMF staff, its analysis and projections of economic developments at the global level. The WAO contains the data that underpins the annual IMF World Economic Outlook report. So it's data on national accounts, inflation, unemployment rates, balance of payments, fiscal indicators and commodity prices. And it's a forecast, so it looks forward. So I think it's currently forecasting up to 2026, maybe 2027 now actually. So an example here, so there wasn't, after Brexit, there was a revision of the GDP growth forecast for 2017 and that's reflected in the World Economic Outlook of April, 2016. So it cut the growth forecast across the world with the UK taking the hardest hit. OECD data, it's rather huge. I'll, the next screen shows you that. So the OECD is a partner organization and it tends to be first world countries, so G20 countries and a few other fast growing economies. The data is completely open, but for the most part it only covers those countries within the OECD. So that's what the OECD data covers. It's an enormous set of data sets, absolutely enormous. And I'm not going to list those. So an example of that, green house estimations for the UK in tons of CO2. And so we'll go back to the quiz. If you've got www.menci.com, use code 66550536. Which country out of the OECD countries do you think had the highest long-term employment rate in 2016? So this uses the Better Life Index from 2016 from the OECD and it's the social welfare statistics group of data. Okay. So Greece had the longest term on employment rate in 2016 following the financial crisis and the subsequent imposition of quite strict financial regulation by the EU. UNESCO data. Education statistics from 1970 onwards, innovation statistics, so that's research and development activity data from 2005 onwards, culture from 2009 or 1995 for feature film statistics and communications and information from 95 onwards. All open data. And an example of this, youth literacy rate for 15 to 24 year olds for both sexes. This comes from the UNESCO education statistics. Very useful because although we have similar data from OECD, that's only covers the OECD countries whereas this covers all countries within the UN. So also from the UN is the industrial development organization part of the UN family. These are statistics on industrial and manufacturing, industrial and manufacturing sectors. There's in-stat two and in-stat four which is in-stat two is less detailed but has data all the way back to 1963. In-stat four is much more detailed but only data from 1990 onwards. This data is restricted but it is freely accessible to users from UK, FE and HE. Example of that. So this is output from UK manufacturing sectors for 2017 and as you can see by that, by far the largest sector is food and beverage followed by motor vehicle production. So little quiz using data from the UNIDO data sets. The US had the highest value of weapons and ammunition exports in 2016 but which country came second? So if you go to www.menti.com and use the code 15341204 you should get a little poll up there. Now, I should update this next year. Actually, just things are changing rapidly. So in 2016, the second most valuable export country was actually Indonesia. Now, there are a couple of emissions on here. We didn't have any data for the Russian Federation and the People's Republic of China apparently only exported $22,000 worth of ammunition and weapons. I'm not quite sure if we can believe that but anyway. So we also have something called the Human Rights Atlas but it was a one-off publication. It has data from 1980 to 2012. It was created for the ESRC by the Human Rights Atlas project and it brings together more than 240 different measures of economic, social and economic development so of economic, social, political and legal life for over 200 different countries. It uses published data from the World Bank, the United Nations, academics, NGOs and other bodies to give a picture of the lives and rights of human beings over a 30-year period and that's open data as well. So this is the sort of thing that you can produce using the Human Rights Atlas. This is political terror scale. So blue are countries under a secure rule of law. People are not imprisoned for their views and torture is rare or exceptional. Political murders are extremely rare and that goes through to red where terror has expanded to the whole population. Leaders of these societies place neural limits on the means or thoroughness with which they pursue personal or ideological goals. But IEA data, this is one of our restricted data sets and this is the only place you can get IEA data other than the IEA itself which will ask you to pay. So it's free to our users. It covers around 130 countries. The majority of the IEA data sets contain annual time series from 1960 onwards. There is one data set that goes back a lot further than that and we'll come to that. It covers energy production, consumption, stocks, energy stocks and energy price. The greenhouse gas emissions covers CO2, methane, nitrous oxide, hydrofluorocarbons, perfluorinated carbons and sulfur hex fluoride emissions into the environment. So it's an extremely valuable resource for anyone studying climate change. So some examples from the IEA. This is production of electricity by renewable sources. Hydro, wind, tide wave and ocean, solar photovoltaics, industrial waste burning and burning of biogases. As you can see, orange is wind, yellow is solar photovoltaics, green is biogases and blue is industrial waste. Wind has completely taken off in the UK. It's by far the largest source of renewable energy. Now, the one data set that we have that goes back a long ways is the world CO2 production. That goes back to 1751 and it's an estimate using academic papers. As you can see, it hugely takes off in the industrial era and this is kilotons of CO2 production. So we're going to have a follow along demo right now. So if you can open a web browser and go to httpsukdateservice.ac.uk and we'll do the same. We can have a look at some aspects of, actually, what we'll do, we'll go, yeah, we'll start at ukdateservice.ac.uk. And we're going to look for the direction of trace statistics. So we're going to look in here, direction of, so if we search in the search bar for direction of trade just accept those analytics. Here we go. The first thing, first thing we get is the IMF direction of trace statistics. I shall just increase the size of my screen. IMF direction of trace statistics, 1948 to 2021. Click on that link. We'll get some more information about that. So we've got the title of the study, study number, if you want a unique identifier. So the data is open. We have a persistent identifier. So what that means is that this will always exist. And if you follow this link, it will always take you to the data. It doesn't matter if we change our URLs. How to cite the data and some information about that as well. Okay. We click on access data. That's all about that. Now, you might have to register for this. I don't know. But there are some special terms and conditions put in for the user of the data. You just have to be aware of these. That's all. Click on access online. It should take us straight to the UKDS.stat and to that particular data. So there we go. So this is dot stat UKDS.stat. And you will notice it opened up three windows to start with. And one of those then collapses. You can always open it again. It opens it to start with just so you know it's there. And then it collapses it again. So this is the direction of trade statistics. It's the November 2021 edition. So it's quite recent. We will get that updated as soon as we can. We're concentrating on our data at the moment. So we want to have a look for this. We're going to have a look at UK exports to its key EU partners in the last 10 years. So if we want to look at the data, I will open the metadata up again. Got an abstract of the data just so you know what it is. We've got some get that if you want help, there's a get in touch link there how to site it. And then we've got all the the guides on using this. They're all downloadable. And then we've got some metadata about the data itself. So if we want to look at our specific question, which is on UK exports to its key EU partners. We can customize the data. So we put we just put in what we think is an interesting looking set of data to start with. So we can customize that we can customize each one or we can look at all of them at once. So we'll just look at all of them. And we're going to unselect everything that'll clear all our selections. So we're going to look at the United Kingdom, which is hopefully there's a Europe section here we go. So select United Kingdom. And we're looking for goods. Value of exports free on board free on board is a technical term used in exporting. It means the value of goods at the exporters customs frontier. And the value of that is in US dollars. And we're going to look at exporting to Europe. So we're going to look at exports to Denmark and France and Germany, Ireland, Italy, Portugal, Spain, and also going to look at world exports as well. And we're going to look at annual data. If we go further, we can look at time. I'm not good to select a time at the moment because there's a better way to do this. But if you data, it won't load anything because we haven't got a time dimension. Customize and then we'll select time from here. And if we do that, we get to better selection interface. And we can select the last 10 years and then we'll view data again. And again, nothing will come up because we haven't told it how to display this data. Well, okay, we do get something, but it's not very good. Good interface. So we're going to customize the layout. So at the moment we've got countries as rows and columns as times and then this is counterpart countries and frequency as options. We're going to drag, click and drag the counterpart country down as a row. And we'll leave the indicator of frequency up there and we'll view that data again. So we've got the reporter country, United Kingdom, and the countries it's exporting to. We've got the goods value of exports free on board and its annual data. I'll just collapse that again so we can see all the data. So in 2012, the value of our exports was $472 billion. In 2020, we're down to $395. Now, it was only down to $469 in 2019. I'm not doing any analysis, but 2020 probably COVID. And we can see how we've fared with all our different EU partners as well here. But it's down for every country. But it's also down in the year before COVID hit 2019. We're also down with every country. Not a huge amount, but we are down. So that's a quick example of using the data. Now, we've got another demo here as well. So we're going to use some protected data. So we're going to use some data from the International Energy Agency. So I'm going to change my provider to International Energy Agency. And it's telling me I've got to log in. So I'll do that. And it's going to take me to a thing that says, where are you from? And everyone will get this. And it will come up. You can either search for your university. Or you can choose from a list. There's all the universities that you could ever want. That's a very long list. So you can start typing. So I'll go back to let me search. I'm in JISC. So that's really easy to find. And it is remembered where I'm from. But if you were from Sheffield, start typing Sheff. And there you go. Three options. Much easier. It's remembered me. So I'm just going to go in with my log in. And then there's a good chance it's going. I've already logged in here this morning. So it's going to remember me. So I don't even have to put my credentials in there. What it'll do with you if you've not logged in that day or that in the past few hours, it will just send you to your university or college login. And then it will send you back here. And it sends you back to a default. A default data set within the IEA, which just happens to be World CO2 emissions. Now we're going to look at oil product spot prices. We're going to see if we can see any issues caused by Putin's war in Ukraine. So I'm just going to collapse that one again. So we're looking in energy prices and taxes. And we're going to look at spot market and crude oil import costs. And we're looking at oil product spot prices. Now this is the 22.253 edition. So it's just been updated. I select that. You shall get a nice little display of prices. Now I'm going to customize this, choose all dimensions again. So I'm only interested in gasoline prices, so petrol prices. There are three markets, main markets where oil and oil products are traded. I'm going to choose the one at Rotterdam. I've looked for the data. It doesn't actually make that much difference. And I'm going to choose monthly figures. And so these are the prices in dollars. I'm going to increase the size of that text search so we can see that a bit better. So it goes all the way back to 2011, this particular one. And it comes all the way up to, still loading. It was all the way up to September, 2022. So if we start looking at the data, say 2020, we're looking at prices around $45 a barrel. It fluctuates as the market changes, goes up to 81, 84, 95 in October, 21. Then in the late winter of 2022, we get the invasion of Ukraine. And prices go through the roof up to 162. And then as measures taken by the U.S. and Saudi Arabia, things start to come down. So we can see something in almost real time. Okay, so I'll just stop that show and we'll go back to the presentation. Oh, actually, I'll go back to that. Because there's various things I didn't cover there. So that's all right for looking at the data. How do we get some use out of that? So we can export this data once we've got it. Excel files, probably the best way. If it's a huge file, text files, the best one, so comma separated variables, you can open these in Excel or in a status, PSS, whatever you want to use. If you're extremely technical and you understand Sdmx, you can download the data in Sdmx format. This binds up the metadata and the data in the same file. But it's machine readable, really. You can't really use it with the human eye. I can just show you what that looks like. That's probably the best if I don't. But we do have that data if you want and we can help you use that data if you want to. You can save your queries. So if you've got a complex view that you want to save, you can do that as well. It's trying to show me the XML. I'll just say no to that. So yeah, you can export it as Excel. For some reason, we don't know why. It sometimes gives a little error when saying you can't open this file. It's Excel being a bit strange. It can open the files, nothing more with it. The Excel files are up to 100,000 data points. So you might need to, if it's a huge query, you might have to make that slightly smaller. For some of our datasets, the very large ones, we have bulk downloads. So I have a look for World Bank World Development Indicators, which is huge. You can do a bulk download. So you can download the whole of the dataset in a zip file. And that's in commerce separator variable format. Yeah, I think that's it. So that's what we did, UK exports, and then oil product spot prices. So a few tips on using the data. If you want to compare data, try doing it from the same data bank to the whole family of data banks. If you go between data providers, there can be issues because they might use slightly different ways of creating their data. So theoretically, identical series can have slightly different values in different data banks. So here we have US GDP reported by the World Bank and the IMF, and they are almost identical until you get to 2014 and when they start to change that's because of the way that that's calculated, has changed slightly. Metadata is inside bar. So there's all sorts of useful stuff in there and guides, and these are the guides produced by the data providers themselves. In there, you can find out how they produce those statistics and the exact meanings of them. And oh yeah, documentation. That's what I've just said. And how to cite the data is in there as well. And that's just about it, really. Similarly of what we do. Oh, we do have a few data skills modules. So if you're very new to the area, we have some modules that you can work your way through and it will tell you all about how you go about a certain subsection of data use.