 Hello, this is Michael Durano. I am going to talk here about some experiences that we have had about reducing open data from various sources, especially we are very interested with Dr. Silvia Simone in gender inequality, in street names, in school names, and also in the presence of researchers in WikiData and Wikipedia. So now, I must tell you that open data are still scarce. However, there are many opportunities yet to use them, at least here in our region in Catalonia. Well, we have several sources, governmental sources especially for researchers, not many, but we know the names of all researchers, we don't have the gender because this is private data. We also have the street names. Street names are provided by the government as well, it's not pretty well maintained, but we can do something about it. And of course we can get street names from the collection of streets in OpenStreamMap, we can even compare them. As far as schools, the local government maintains a list of schools every year with all the changes, new schools, schools that are no longer there and so on, that have several data. So, about streets, well, in general, in Wikipedia you know that in general there are only streets that have heritage value. Even though there are cities like probably, for instance, that have all streets in WikiData and probably Wikipedia, at least in our regional environment, streets are not in Wikipedia and neither in Wikipedia. So, the question is, if you want to address the question of eponyms in streets, because we are interested in understanding the difference between number of females giving eponyms in streets and number of males giving numbers names in streets, we need a database, we need data in WikiData. So, what do we do? Just download, spreadsheet and count the number of streets in Catalonia that are 150,000 streets in Catalonia. These are about 30,000 unique names. Among these maybe a 2,000, 2,000 bear an eponym, like Martin Luther King Street or whatever, or John Doe Street. So, we are interested in assessing the names of streets that bear an eponym and asking us, do they deserve to be present in WikiData? Are there words unnotable to be present in Wikipedia too? Because especially for many rice languages like Catalan, for instance, it's important to know the history, it's important to know people who deserve names of streets, of schools as well and other items. So, we did some work about it. Of course, in the case of streets, we collaborate with the OpenStreetMap, okay, using the WikiData tag or even using the node ways and relation IDs as well in WikiData items. I must say that it's not an easy task because as part of street names, there are same variations in street names, just letters, misspellings, sometimes things seem the same but they are not the same and so on. So, we have to clean up to clean up data. That's not an easy task at all. But schools is slightly more simple because the government maintains the rates of schools. However, in this case, we have used several sources because what are we interested in about school? Well, we are interested probably about the name of school, discover the point which is available, but we are also interested in the number of students, about its size of course, about if there is, if it's private or public, how many jobs are at the level, how many people are about to enter university. I am a university professor, this is university group. So, of course, we get students from high schools. So, knowing whether school has a big or middle or low number of students means that we can assess how we must invest our effort in promoting our university and our studies in our case chemistry to local schools. So, for instance, are they financed by public money, which is the date of the foundation, etc., etc., and these are provided by various sources. There are several open data listings that are currently maintained by the regional government. Of course, this would be a great idea for a citizen science project. However, of course, it would be good that each school maintains their own data. However, we clash, of course, with the problem of conflict of interest, even though we might say, okay, you should be an outsider. So, that's something that should be thought on. Of course, the photo, in the previous case of streets, the photo, the image of the school, many, many ideas there. So, this is as far as school is concerned. Finally, about, of course, the relevant question of does a person having an appointment deserve a Wikipedia page? We think, yes. About researcher names, this is far more difficult. We are university, we are university researchers, and there are many, many researchers that are not getting Wiki and Wiki data, not in Wikipedia. Unfortunately, using automatic tools like Orchidator or other tools that enter names in Wiki data, we find that many researchers have several entries in Wiki data up to three or four. So, there is a huge amount of work to be done to clean up data. There is open data from our regional government. Some universities have open data as well. Websites, which I can describe, very complicated. But if you want projects like Wiki data, Wiki project chemistry, or even Scoria to be successful, you need clean data as far as the researcher names is concerned. And of course, if you want to carry out gender studies for researchers like we will see later, you need clean data. You need reliable data. So, from now on, we'll provide you some hints. This is not a complete account of our projects. For instance, we have interacted with OpenStreamMap in the sense that for streets or for schools, Wiki data answers the question, where is this? While OpenStreamMap answers the question, what is there? Okay, even there are very, very interesting tools like OSM Wiki data link that interwinkel data. So, very interesting. In Wiki data, for instance, we have the instance of street or educational center. And for eponyms, we use the name after someone that's P138 property. In the case of OpenStreamMap, we use the Manatee School, Highway Street. And for as far as upon him, we use the tag name etymology Wiki data equals the Q number in Wiki data. Of course, we can use also the Wikipedia tag. So, we import Wiki data and we map in OSM. For instance, for streets, what is a street? A street is a collection of segments. So, it has geometry. The same for schools, it has geometry. So, how do Wikipedia projects and Wiki data items account for geometry the best? And the simplest idea is to use WikiMaps and to use OpenStreamMap information. So, the same for streets, the same for schools. Okay, we enter eponyms. It's difficult because sometimes you have to go one after one. The OpenStreamMap links Wiki data on Wikipedia, of course, and OpenStreamMap, giving different colors to the source and to the type of items, whether it's a person, whether it's a wind, whether it's a geographical number or name. Here, you have the account. These are very interesting tools. As far as relevant information, as far as streets, like we have here in the Rosso and Franklin Street in the local town near Girona in Catalonia, we have realized that there are a huge number of male names and the very low numbers of female names. Here in Catalonia, the person having the most number of streets is Marie Curie with 28 streets. However, the most important, this is the most important scientist, female. The most important male scientist has 200 streets. As far as non-scientists, well, we have plenty of people who are in arts and politics and everything else, and the number of streets of non-scientists is very, very larger than the number of streets of scientists. In any case, women scientists have a double discrimination. First of all, scientists appear far less in street names and also in school names than non-scientists, and indeed, women appear far less than men. So women scientists, we must do a huge effort to provide female names to schools and streets and also to push for science names. This is in the case of, sorry, I made, okay, here. I just want to compare the scientists and stream names in Catalonia. At left, you have Marie Curie streets, there are scars. At right, you have Alexander Fleming streets. Okay, as you can see, these are the two persons having most streets in Catalonia. Well, comparison is very simple. We have a big gender issue here. As far as schools, this is just the number of female names, not only in Catalonia, but also in Valencia and the Balearic Islands. Okay, there are there are many, many females, female names that give eponymous to a street that have no Wikipedia entry, unfortunately. And this is the, in the case of schools, we have 1600 primary schools that are about 600 schools that have a person name. And well, as you can see, there are few female names. The same here, you have a plot for the number of schools and eponymous in Catalonia. And this is the number of high schools having eponymous in Catalonia. Okay, at left, female, at right, male. Comparison is almost always the same. I will skip this. And I would like to pinpoint a very interesting study in a native journal about notability. This cross-verified deprivation of that people have the reference. And well, here you have in red, the municipalities with the most notable person is a man. And in blue, municipalities whose most notable person is a woman against the comparison is for men, is men are always, promoted. And this can be done for any region in the world. By the way, we only focus in Catalonia, but we could focus in any part of the world. Just take a look at this interesting paper and you will be clear. So in the case of notability, only 197 places in Catalonia have notable scientists. So again, women are doubly discriminated as women and as scientists. Have a hard time to be notable. Women have a much harder time to be notable and so on. So I will stop here because these are three cases, repeat, streets, schools, and notability for researchers. And you can find a lot of information in our websites. And that's it. Thank you very much for everything.