Since shortly after we moved in we have a temperature and humidity sensor in our garden.

This week’s heat wave is breaking records across Europe including here in the Netherlands. So I’ve kept an eye on the temperature in our garden. Our sensor is part of a city wide network of sensors, which includes two sensors nearby. Of the three sensors, ours indicates the lowest temperature at 36.8 (at 16:45), the other two hover just under 40 and at 41.8 respectively. Such differences are caused by the surroundings of the sensor. That ours is the lowest is because it’s placed in a very green garden, while the others are out on the street. In our completely paved and bricked up courtyard the temperature is 42.1 in the shade, due to the radiation heat of sun and stones. Goes to show that greenery in a city is key in lowering temperatures.

Three sensors in our neighbourhood, ours is in the middle, showing the lowest temperature. Note that the color scale is relative, for these 3 sensors running from 36.6 to 41.8.

In the past days since our return from France the temperature has been steadily rising, as per the graph below (which currently ends at the peak of 36.8 at 16:45). Staying inside is the best option, although the also increasingly higher lowest temperatures (from 15 to above 20) mean that the nights are slowly becoming more uncomfortable as the outside temperature will stay above the in house temperature during most or all of the night.

UPDATE as of 26/7 June noon, here you can see how the night minimum jumped 5 degrees in 24 hours, bringing it above the in house temperature for the entire night, except a brief moment around 6 am. At noon the maximum for the day before is already nearly reached.

The way to make this graph yourself is

  • Go to meetjestad.net/data, where you can select various data types and time frames. Our sensor is number 51, and I selected a time frame starting at July 19th at midnight. This allows me to download the data as CSV.
  • The data in that download is Tab separated, not comma,when you select a comma to be used as decimal point.
  • The file contains columns for the sensor number and its latitude and longitude, that are not needed as this is data for just one sensor. Likewise, empty columns for measurement values for which my sensor kit doesn’t contain sensors, such as particulate matter, can be removed. Finally the columns for battery level and humidity are also not needed on this occasion.
  • With the remaining columns, time and temperature it is easy to build the graph. In this case I replaced the timestamps with sequential numbers, as I intend to make a sparkline graph with it later.

Today I gave short presentation at the Citizen Science Koppelting conference in Amersfoort. Below is the transcript and the slidedeck.

I’ve worked on opening data, mainly with governments worldwide for the past decade. Since 2 years I’ve been living in Amersfoort, and since then I’ve been a participant in the Measure Your City network, with a sensor kit. I also run a LoRaWan gateway to provide additional infrastructure to people wanting to collect sensor data. Today I’d like to talk to you about using open data. What it is, what exists, where to find it, and how to get it. Because I think it can be a useful resource in citizen science.

What is open data? It is data that is published by whoever collected it in such a way, so that anyone is permitted to use it. Without any legal, technical or financial barriers.

This means an open license, such as Creative Commons 0, open standards, and machine readable formats.
Anyone can publish open data, simply by making it available on the internet. And plenty people, academics, and companies do. But mostly open data means we’re looking at government for data.

That’s because we all have a claim on our government, we are all stakeholders. We already paid for the data as well, so it’s all sunk costs, while making it available to all as infrastructure does not increase the costs a lot. And above all: governments have many different tasks, and therefore lots of different data. Usually over many years and at relatively good quality.

The legal framework for open data consists of two parts. The national access to information rules, in NL the WOB, which says everything government has is public, unless it is not.
And the EU initiated regulation on re-using, not just accessing, government material. That says everything that is public can be re-used, unless it can’t. Both these elements are passive, you need to request material.

A new law, the WOO, makes publication mandatory for more things. (For some parts publication is already mandated in laws, like in the WOB, the Cadastre law, and the Company Register)

Next to that there are other elements that play a role. Environmental data must be public (Arhus convention), and INSPIRE makes it mandatory for all EU members to publish certain geographic data. A new EU directive is in the works, making it mandatory for more organisations to publish data, and for some key data sets to be free of charge (like the company register and meteo data)

Next to the legal framework there are active Dutch policies towards more open data: the Data Agenda and the Open Government action plan.

The reason open data is important is because it allows people to do new things, and more importantly it allows new people, who did not have that access before, to do new things. It democratises data sources, that were previously only available to a select few, often those big enough to be able to pay for access. This has now been a growing movement for 10-15 years.

That new agency has visible effects. Economically and socially.In fact you probably already use open data on a daily basis without noticing. When you came here today by bike, you probably checked Buienradar. Which is based on the open data of the KNMI. Whenever in Wikipedia you find additional facts in the right hand column, that informations doesn’t come from Wikipedia but is often directly taken from government databases. The same is true for a lot of the images in Wikipedia, of monuments, historic events etc. They usually come from the open collections of national archives, etc.

When Google presents you with traffic density, like here the queues in front of the traffic lights on my way here, it’s not Google’s data. It’s government data, that is provided in near real-time from all the sensors in the roads. Google just taps into it, and anyone could do the same.You could do the same.

There are many big and small data sets that can be used for a new specific purpose. Like when you go to get gas for the car. You may have noticed at manned stations it takes a few seconds for the gas pump to start? That’s because they check your license plate against the make of the car, in the RDW’s open database. Or for small practical issues. Like when looking for a new house, how much sunshine does the garden get. Or can I wear shorts today (No!).

But more importantly for today’s discussion, It can be a powerful tool for citizen scientists as well. Such as in the public discussion about the Groningen earth quakes. Open seismological data allowed citizens to show their intuition that the strength and frequency of quakes was increasing was real. Using open data by the KNMI.Or you can use it to explore the impact of certain things or policies like analysing the usage statistics of the Utrecht bicycle parking locations.A key role open data can play is to provide context for your own questions. Core registers serve as infrastructure, key datasets on policy domains can be the source for your analysis. Or just a context or reference.

Here is a range of examples. The AHN gives you heights of everything, buildings, landscape etc.
But it also allows you to track growth of trees etc. Or estimate if your roof is suitable for solar panels.This in combination with the BAG and the TOP10NL makes the 3d image I started with possible. To construct it from multiple data sources: it is not a photograph but a constructed image.

The Sentinel satellites provide you with free high resolution data. Useful for icebreakers at sea, precision agriculture, forest management globally, flooding prevention, health of plants, and even to see if grasslands have been damaged by feeding geese or mice. Gas mains maintainer Stedin uses this to plan preventative maintenance on the grid, by looking for soil subsidence. Same is true for dams, dikes and railroads. And that goes for many other subjects. The data is all there. Use it to your advantage. To map your measurements, to provide additional proof or context, to formulate better questions or hypotheses.

It can be used to build tools that create more insigt. Here decision making docs are tied to locations. 38 Amersfoort council issues are tied to De Koppel, the area we are in now. The same is true for many other subjects. The data is all there. Use it to your advantage. To map your measurements, to provide additional proof or context, to formulate better questions or hypotheses.

Maybe the data you need isn’t public yet. But it might be. So request it. It’s your right. Think about what data you need or might be useful to you.
Be public about your data requests. Maybe we can for a Koppelting Data Team. Working with data can be hard and disappointing, doing it together goes some way to mitigate that.

[This post was created using a small hack to export the speaking notes from my slidedeck. Strangely enough, Keynote itself does not have such an option. Copying by hand takes time, by script it is just a single click. It took less than 10 minutes to clean up my notes a little bit, and then post the entire thing.]