 The most basic use of pairs is as a data service that is to ask questions such as what is the temperature or the temperature of forecast at some location. In this sample query, we're going to simply request the temperature of forecast for Kyoto. To do so, we create a new query. We select the data we're interested in, namely this is weather. We pick the weather forecast from the global forecast system. We are interested in the ground temperature, so we select this. Subsequently, we have to specify the location, so this is a point query. And we select Kyoto simply from the map, which is here. Now finally, we have to select the time interval we're interested in. And to do so, you can see here that pairs gives you a hint. Essentially, it tells you for what time there is data available from the specific data layer. Since this is a temperature forecast, you see that this actually goes somewhat into the future. So just so you know, today is March the 5th. There's roughly two weeks of forecast range for this forecast. So we can select something up to March 17. At the same time, there's actually historical forecast data available, which is why this goes back all the way to 2015. And we can simply select the complete time series like this. So finally, we have to give this query a name and then we can submit it. Now point queries are actually very fast, so this doesn't take very long. You can see here immediately after submitting, this is at 95%. So it only takes a few seconds to wait for this to be finished. And now we can take a look at this. So in this window, we see at the bottom the temperature time series. Now if we hover over it, it basically highlights the temperature at this point. We are hovering over units for temperature here and Kelvin. If we wonder, we can just change the map into standard maps for our political map. And the neat thing is, since point queries are very fast, we can simply click somewhere else in the map, such as Tokyo here. And now get the time series for Tokyo. Okay, this is requested in real time from the system. So this launches another query. And now we can see and compare the time series for Tokyo. If we wanted to, we can also change the time interval to zoom in on some aspects. So if we're just interested in the last year, we could select 2017 like this. So now we have the 2017 cycle here. And finally, you notice there's a button at the top bottom right corner here to download the data.