 Hello, welcome to my lightning talk on Finnish Personal Identity Codes and an R-Package that handles them, Hetu. My name is Pyrrugandanen and I come from R-OpenGov, a collective of R-Package developers on open government data and related topics. First, to put things in context, here you can see numbers from all five Nordic countries. Sweden was the first Nordic country to introduce its national identification number system in 1947 and this influenced other countries in the following decades. You can probably notice similarities even at a quick glance. Today we will concentrate on Finnish national identification numbers and here are two imaginary examples that we will go through in the following slides. The Finnish Personal Identity Code consists of four parts, the birth date in short format, a sensory character, a personal number and a control character. The sensory character has three valid options, a dash for 1900s, a for 2000s and a plus sign for 1800s. The personal number indicates the individual sex, even numbers for females and odd numbers for males. The control or checksum character is calculated by dividing the date an individual number put together with the number 31 and using the remainder value to look up the correct character from a separate table. Here is what the package output looks like but we will use a more prettier version of this table. So, as we can see here, this person is born in the beginning of the 1900s because of the sensory marker tells us. The individual number which is an even number tells us that the person is a female and here is the checksum number one. This person in turn is born in the 2000s as the sensory marker indicates and the person is a male because this number is an odd number. The checksum is a letter C so it doesn't have to be a number all the time. Motivation for this package comes from the fact that Finnish personal identity codes are widely used in both public and private institutions, linking individuals from public registries to private customer information systems. In academic research, for example, data from surveys can be combined to registry data by using the identity code as a key, making early validation of codes crucial for further data gathering. Information extracted from personal data can furthermore be less prone to input errors as the calculation method for checksum characters is sensitive for mistyped information. The future prospects of this package are twofold. The first is technical. The package functions could always be a bit more speedy, especially the random personal identification number generator. Also, the package could easily support more national identification numbers, for example, from other Nordic countries. Then again, generally speaking, the package functions are quite speedy as they are as they utilize ours built in vectorized operations as of now. And adding support for more countries would go against the UNIX philosophy of doing one thing and doing it well. The political prospects are probably a bit more pressing. In many countries, national identification numbers have been or are in the process of being reformed due to running out of unique numbers and due to privacy concerns. There are differences between different countries. In Iceland, for instance, identity numbers are more or less public information, whereas in Finland they are thought to contain sensitive personal information. Some experts have suggested that birth date and sex should be removed from future iterations. We will closely monitor these developments and readjust the package accordingly. Thank you for your time. Here are some links through which you can contact us.