1 00:00:06,115 --> 00:00:08,540 (chairman) Good afternoon, everybody. Welcome back. 2 00:00:09,696 --> 00:00:14,906 We will start our last session in this room before the closing session. 3 00:00:16,225 --> 00:00:19,278 On stage is Alicia Fagerving from Wikimedia Sweden, 4 00:00:19,477 --> 00:00:23,656 who will tell us more about finding GLAMs all around the world. 5 00:00:24,393 --> 00:00:26,573 Don't forget the collaborative note taking-- 6 00:00:26,573 --> 00:00:29,723 there is a link to the Etherpads on the program, 7 00:00:29,723 --> 00:00:33,265 as you know by now, and please help us 8 00:00:33,265 --> 00:00:35,845 all for the documentation for this presentation. 9 00:00:35,845 --> 00:00:37,052 Thank you very much. 10 00:00:37,052 --> 00:00:38,062 (Alicia) Thank you. 11 00:00:38,882 --> 00:00:40,912 My name is Alicia Fagerving. 12 00:00:40,912 --> 00:00:44,231 I am a developer at Wikimedia Sverige, 13 00:00:44,231 --> 00:00:46,602 the Swedish chapter of the Wikimedia Foundation. 14 00:00:47,403 --> 00:00:51,953 And today I am going to talk about the project 15 00:00:51,953 --> 00:00:55,121 that, I know, some of you have heard about. 16 00:00:55,656 --> 00:00:59,858 It is a project that we have been working on for quite a while, 17 00:01:00,568 --> 00:01:04,758 and we've been reaching out to the global Wikimedia community 18 00:01:04,758 --> 00:01:06,610 to keep you updated. 19 00:01:07,086 --> 00:01:11,107 We have received already some very enthusiastic feedback, 20 00:01:11,579 --> 00:01:14,699 both earlier on and at this conference, 21 00:01:15,071 --> 00:01:19,757 indicating that there is indeed a lot of interest 22 00:01:20,447 --> 00:01:23,431 in the potential of Wikidata 23 00:01:23,431 --> 00:01:28,997 as the ultimate global database 24 00:01:28,997 --> 00:01:32,361 of cultural heritage institutions. 25 00:01:37,547 --> 00:01:43,594 The project that we are working on is called FindingGLAMs, 26 00:01:43,925 --> 00:01:46,911 and its goal is, in short, 27 00:01:47,293 --> 00:01:52,293 to put every museum, gallery, archive and library 28 00:01:52,293 --> 00:01:54,003 on the Wikidata map. 29 00:01:55,012 --> 00:01:57,942 Wikimedia Sweden is working on this project 30 00:01:57,942 --> 00:02:01,222 in collaboration with the Wikimedia Foundation 31 00:02:01,222 --> 00:02:03,235 and with UNESCO, 32 00:02:03,937 --> 00:02:07,836 and with financing from the Swedish Postcode Foundation, 33 00:02:08,322 --> 00:02:12,982 which is an organization that promotes positive social development. 34 00:02:14,680 --> 00:02:20,222 Originally we thought that we would end our project in November, 35 00:02:20,531 --> 00:02:23,165 which is why the title of the session, 36 00:02:23,781 --> 00:02:27,142 *All the world's GLAM institutions and how we try to find them*, 37 00:02:27,142 --> 00:02:28,951 is in the past tense. 38 00:02:29,025 --> 00:02:34,079 Because we expected that at this point we would be able take a look back 39 00:02:34,079 --> 00:02:36,378 and sum up our efforts. 40 00:02:38,633 --> 00:02:42,498 Well, it turns out we still have a lot of work to look forward to 41 00:02:42,498 --> 00:02:47,475 as the project has been extended until the end of February 2020. 42 00:02:48,194 --> 00:02:52,194 And this is great news as it means that we will be able 43 00:02:52,194 --> 00:02:55,821 to guide and support more volunteers 44 00:02:55,998 --> 00:03:00,464 who want to bring this project to their local Wikimedia communities. 45 00:03:01,015 --> 00:03:03,495 And I'll talk about that a bit later on, 46 00:03:03,495 --> 00:03:06,764 but first let's have a look at some facts 47 00:03:06,764 --> 00:03:10,562 to understand why we are even doing this. 48 00:03:12,923 --> 00:03:18,106 How many GLAMs are there on Wikidata? 49 00:03:19,051 --> 00:03:24,061 Almost 130,000 right now. 50 00:03:24,306 --> 00:03:28,142 And that is a lot, like I would be very happy 51 00:03:28,142 --> 00:03:31,935 if I had 130,000 of anything 52 00:03:32,245 --> 00:03:34,472 but that's obviously not enough. 53 00:03:35,244 --> 00:03:41,750 Now, we don't really know how many GLAMs there are in the world. 54 00:03:42,964 --> 00:03:47,013 But we have access to some estimates and service, 55 00:03:47,758 --> 00:03:49,884 for example, IFLA, 56 00:03:49,884 --> 00:03:54,950 the International Federation of Library Associations and Institutions, 57 00:03:55,419 --> 00:03:57,354 estimates on their website 58 00:03:57,354 --> 00:04:03,948 that there are about 2.5 million libraries 59 00:04:04,553 --> 00:04:05,944 around the world. 60 00:04:05,944 --> 00:04:10,808 If I remember correctly, most of these are school libraries. 61 00:04:12,042 --> 00:04:14,298 And on Wikidata 62 00:04:14,572 --> 00:04:19,098 there are about 57,000 items 63 00:04:19,312 --> 00:04:24,397 for different sorts of libraries around the world. 64 00:04:26,015 --> 00:04:29,945 If we look at museums in the U.S., 65 00:04:30,122 --> 00:04:35,029 we know that there are at least 30,000 museums. 66 00:04:35,444 --> 00:04:38,314 That is in the U.S. alone, 67 00:04:38,636 --> 00:04:42,563 while Wikidata only has items for a couple of thousand, 68 00:04:42,563 --> 00:04:47,403 about 4,000 museums in the U.S. 69 00:04:47,745 --> 00:04:52,685 So this shows that there is still a lot to do 70 00:04:53,298 --> 00:04:57,710 and a lot of possibilities to ingest more data. 71 00:05:00,932 --> 00:05:05,534 Obviously it's not only numbers that are interesting 72 00:05:05,904 --> 00:05:08,494 but where those GLAMs are located. 73 00:05:09,364 --> 00:05:14,298 About 60,000 of GLAMs on Wikidata have coordinates, 74 00:05:14,298 --> 00:05:16,701 which means we can show them on the map. 75 00:05:17,514 --> 00:05:20,616 And this is an interesting way of demonstrating 76 00:05:20,987 --> 00:05:25,767 not only the size of the data but also the geographical bias. 77 00:05:26,458 --> 00:05:31,942 There are a lot of GLAMs in Western and Central Europe. 78 00:05:32,292 --> 00:05:36,426 You can see that the U.K., France, Germany, also Sweden 79 00:05:36,426 --> 00:05:38,025 are well represented. 80 00:05:39,312 --> 00:05:43,863 We can see, there is quite a lot of dots in the U.S. 81 00:05:44,279 --> 00:05:47,229 and in certain parts of South America. 82 00:05:48,884 --> 00:05:53,802 If we look at Asia, we see that Japan stands out, 83 00:05:54,227 --> 00:05:58,465 but countries like India, Russia or Indonesia 84 00:05:59,133 --> 00:06:00,983 have really bad coverage, 85 00:06:00,983 --> 00:06:05,298 despite the fact that they are very, very highly populated. 86 00:06:06,732 --> 00:06:08,867 And obviously Africa-- 87 00:06:09,212 --> 00:06:11,830 I don't even have to mention 88 00:06:11,993 --> 00:06:15,429 that the coverage there is very, very bad-- 89 00:06:15,429 --> 00:06:19,314 very few GLAMs in African countries. 90 00:06:20,893 --> 00:06:24,893 And of course this distribution is not unique to just GLAMs, 91 00:06:25,653 --> 00:06:30,435 it's typical for other types of items on Wikidata. 92 00:06:30,435 --> 00:06:33,147 The global North is overrepresented 93 00:06:33,147 --> 00:06:37,272 because that's where a lot of the volunteers come from, 94 00:06:37,272 --> 00:06:40,256 and that's the areas they have a lot of interest in. 95 00:06:41,852 --> 00:06:44,517 Now, I haven't mentioned the colors yet 96 00:06:44,763 --> 00:06:48,104 but they are important as well. 97 00:06:48,762 --> 00:06:53,720 We've run the queries to find the GLAMs in Wikidata twice-- 98 00:06:54,012 --> 00:06:55,772 once back in April 99 00:06:56,362 --> 00:06:59,014 and, again, very recently in October. 100 00:06:59,833 --> 00:07:04,553 And the yellow dots are just the April coverage, 101 00:07:04,677 --> 00:07:10,939 and the purple ones are the new ones that appeared in the October results. 102 00:07:11,680 --> 00:07:17,005 This shows that a lot of new GLAMs appeared in that couple of months, 103 00:07:17,005 --> 00:07:18,549 the six months period. 104 00:07:19,454 --> 00:07:23,696 Some of this increase, not all of it but some of it, 105 00:07:23,925 --> 00:07:26,875 is thanks to our project. 106 00:07:27,485 --> 00:07:32,674 And that's specifically the U.S. and Africa coverage. 107 00:07:34,933 --> 00:07:37,083 So how has this come about? 108 00:07:37,668 --> 00:07:41,328 A very large part of our work 109 00:07:41,328 --> 00:07:46,110 is working with existing published datasets of GLAMs 110 00:07:46,110 --> 00:07:47,383 in different countries. 111 00:07:47,663 --> 00:07:50,283 And there are lots of them in different formats 112 00:07:50,283 --> 00:07:55,634 and published by various regional or national entities. 113 00:07:56,473 --> 00:07:58,312 For example, in the U.S. 114 00:07:58,312 --> 00:08:01,967 we have the Institute of Museum and Library Services, 115 00:08:02,694 --> 00:08:08,104 which publishes the results of its annual Public Library Survey. 116 00:08:08,375 --> 00:08:12,145 It contains data about the country's public library systems 117 00:08:12,145 --> 00:08:14,299 and public library outlets 118 00:08:14,299 --> 00:08:16,350 that are organized in those systems. 119 00:08:16,769 --> 00:08:22,683 And since this data is produced by a U.S. government agency, 120 00:08:22,683 --> 00:08:27,453 then it's in public domain and we know we can use it on Wikidata. 121 00:08:27,453 --> 00:08:31,066 So it was possible for us to import that data. 122 00:08:32,693 --> 00:08:36,111 Another example of data that we could import 123 00:08:36,742 --> 00:08:42,684 is data from the *Advancing Library Visibility in Africa* project, 124 00:08:43,223 --> 00:08:46,566 which is carried out by the University of Washington. 125 00:08:47,711 --> 00:08:49,675 And I think this project is very interesting 126 00:08:49,675 --> 00:08:53,144 because they have quite a similar goal. 127 00:08:53,385 --> 00:08:57,342 They collect data about libraries in several African countries, 128 00:08:58,032 --> 00:09:00,422 and this includes basic information, 129 00:09:00,422 --> 00:09:03,824 such as the name of the library, where it's located 130 00:09:03,824 --> 00:09:06,974 and its geographical coordinates. 131 00:09:07,768 --> 00:09:13,179 And the researchers licensed their data as CC0 132 00:09:13,658 --> 00:09:19,166 to ensure that really it can be reused as widely as possible 133 00:09:19,166 --> 00:09:21,315 and reach as many people as possible. 134 00:09:22,528 --> 00:09:24,781 So because of that we could add 135 00:09:24,781 --> 00:09:28,717 a couple of hundred new Wikidata items for libraries 136 00:09:28,717 --> 00:09:33,500 on a continent that had an extremely poor coverage 137 00:09:33,500 --> 00:09:35,941 of libraries and GLAMs in general. 138 00:09:38,878 --> 00:09:41,158 These are the positive examples 139 00:09:41,158 --> 00:09:46,498 but the truth is that most of the datasets we found 140 00:09:46,754 --> 00:09:48,404 through our research 141 00:09:48,540 --> 00:09:51,560 could not be imported into Wikidata. 142 00:09:52,147 --> 00:09:58,280 We decided to only work with datasets that are explicitly licensed 143 00:09:58,280 --> 00:10:00,956 in a way that is compatible with Wikidata, 144 00:10:00,956 --> 00:10:03,436 such as public domain or CC0. 145 00:10:04,648 --> 00:10:08,498 But we believe that even if a dataset is copyrighted, 146 00:10:08,498 --> 00:10:11,053 it's still valuable, 147 00:10:11,403 --> 00:10:13,513 it's still good for the Wikimedia community 148 00:10:13,513 --> 00:10:15,593 to know that it exists. 149 00:10:16,177 --> 00:10:20,247 And that's why one of the goals of the FindingGLAMs project 150 00:10:20,247 --> 00:10:22,861 is collating a master list 151 00:10:22,861 --> 00:10:27,586 of datasets of GLAM institutions 152 00:10:27,782 --> 00:10:32,822 which you can find on Meta, and if you know of a dataset 153 00:10:32,822 --> 00:10:35,421 from your country or region that is not there, 154 00:10:35,548 --> 00:10:38,064 you are very welcome to add it there. 155 00:10:38,515 --> 00:10:41,598 Simply knowing that it exists is very valuable. 156 00:10:42,127 --> 00:10:45,875 For example it can be used as a source to write Wikipedia articles, 157 00:10:46,544 --> 00:10:52,942 and it provides an entry point to possibly discuss with the publisher 158 00:10:53,042 --> 00:10:57,121 whether it would be possible to release it under an open license. 159 00:10:59,319 --> 00:11:01,870 And here is an example. 160 00:11:02,189 --> 00:11:05,072 When researching GLAM data around the world, 161 00:11:05,248 --> 00:11:08,951 we found that Archives Portal Europe 162 00:11:08,951 --> 00:11:14,199 has a directory of about 2,000 archival institutions 163 00:11:14,199 --> 00:11:17,188 all around Europe, including very valuable data 164 00:11:17,188 --> 00:11:20,186 like their coordinates, addresses and collection sizes. 165 00:11:20,490 --> 00:11:22,380 When we reached out to them 166 00:11:22,380 --> 00:11:25,710 about potentially ingesting that dataset on Wikidata, 167 00:11:25,710 --> 00:11:27,434 they first said that, 168 00:11:27,434 --> 00:11:30,278 well, it's copyrighted, it's not open data. 169 00:11:30,278 --> 00:11:34,117 But we told them about Wikidata and open data, 170 00:11:34,117 --> 00:11:35,891 and about our project, 171 00:11:35,891 --> 00:11:37,992 and they were actually very positive, 172 00:11:38,488 --> 00:11:42,844 and they promised to take steps to release their dataset 173 00:11:42,844 --> 00:11:44,910 under a CC0 license. 174 00:11:45,303 --> 00:11:48,543 We are having a very positive dialog around that right now, 175 00:11:48,543 --> 00:11:55,240 and we really hope that this will become reality very soon. 176 00:11:58,799 --> 00:12:02,867 Now, using official datasets is only one way 177 00:12:02,867 --> 00:12:07,999 in which we can improve the coverage of GLAM institutions on Wikidata. 178 00:12:08,649 --> 00:12:11,806 Another one that we are developing in our project 179 00:12:12,168 --> 00:12:16,993 is making it easier for people, for new users, 180 00:12:16,993 --> 00:12:20,433 especially users within GLAM institutions, 181 00:12:20,433 --> 00:12:23,202 to add new information to Wikidata. 182 00:12:23,875 --> 00:12:28,846 We would love to see more GLAM professionals edit Wikidata 183 00:12:28,846 --> 00:12:31,881 and add information about GLAM institutions. 184 00:12:32,431 --> 00:12:35,655 And many of them have heard about Wikidata. 185 00:12:35,810 --> 00:12:38,970 Many of them are curious about how they can use it 186 00:12:38,970 --> 00:12:40,540 in their everyday work. 187 00:12:40,871 --> 00:12:45,972 And editing Wikidata is a great way to learn that. 188 00:12:48,788 --> 00:12:52,589 But anyone who has tried to introduce 189 00:12:52,850 --> 00:12:56,220 non-Wikimedians to Wikidata 190 00:12:56,220 --> 00:12:59,433 knows that there is quite a bit of a threshold 191 00:13:00,259 --> 00:13:03,937 before they can start making useful edits, 192 00:13:04,404 --> 00:13:09,024 like even if you don't want to delve into the technical details 193 00:13:09,024 --> 00:13:14,062 and the data modeling, there is still a lot to learn 194 00:13:14,235 --> 00:13:18,033 about how the data in Wikidata is structured, 195 00:13:18,467 --> 00:13:22,177 how to find whatever that interests you, 196 00:13:22,177 --> 00:13:25,265 for example how to find all libraries in a city. 197 00:13:25,959 --> 00:13:27,839 And, most importantly, 198 00:13:27,839 --> 00:13:32,670 how this particular sort of stuff normally is modeled 199 00:13:32,878 --> 00:13:37,032 because there are a lot of properties and lots of good practice 200 00:13:37,227 --> 00:13:43,579 but for a new user who just created their first blank item, 201 00:13:43,679 --> 00:13:46,779 this is very, very hard and complex, 202 00:13:46,779 --> 00:13:50,879 and it's not clear where to find this information and whom to ask. 203 00:13:51,607 --> 00:13:55,727 So they often need personal guidance to learn like 204 00:13:55,727 --> 00:13:58,713 what sort of properties you add to an item 205 00:13:58,713 --> 00:14:01,667 that represents a museum or a library. 206 00:14:05,268 --> 00:14:08,378 So that's why we are developing software 207 00:14:08,378 --> 00:14:11,143 to make it easier for absolute beginners 208 00:14:11,488 --> 00:14:16,327 in GLAM institutions to make their first Wikidata edits. 209 00:14:17,341 --> 00:14:19,696 This app is called Monumental. 210 00:14:20,161 --> 00:14:24,349 We developed a first version that was released earlier this year 211 00:14:24,349 --> 00:14:27,281 and based on the feedback we received. 212 00:14:27,281 --> 00:14:29,877 We are working on a new improved version 213 00:14:29,877 --> 00:14:32,000 that should be online soon. 214 00:14:32,000 --> 00:14:37,062 I don't think the usable version is released already. 215 00:14:38,034 --> 00:14:39,824 And the aim of Monumental 216 00:14:39,824 --> 00:14:45,659 is to make searching, viewing and editing GLAM items easier. 217 00:14:47,057 --> 00:14:52,617 For example the user can see all the GLAM institutions around them 218 00:14:52,617 --> 00:14:54,518 or in a selected location 219 00:14:54,725 --> 00:14:57,982 without having to write SPARQL queries. 220 00:15:02,783 --> 00:15:05,112 And when it comes to editing, 221 00:15:05,643 --> 00:15:08,396 we think this is especially important: 222 00:15:08,396 --> 00:15:12,738 The user does not have to guess which properties to use. 223 00:15:13,605 --> 00:15:18,355 The interface displays a selection of properties 224 00:15:18,421 --> 00:15:21,380 that are normally used with GLAM items, 225 00:15:22,033 --> 00:15:28,187 and the user can see that even if there are no values 226 00:15:29,213 --> 00:15:30,726 for those properties, 227 00:15:31,948 --> 00:15:34,868 then the user knows that this information is missing, 228 00:15:35,151 --> 00:15:37,753 and this is what they can add. 229 00:15:38,093 --> 00:15:41,589 And that way they can make valuable contributions 230 00:15:41,947 --> 00:15:47,107 within this very small limited model, which reduces confusion 231 00:15:47,107 --> 00:15:50,672 and reduces the fear of doing something wrong. 232 00:15:54,083 --> 00:15:56,163 And we want to promote this tool 233 00:15:56,163 --> 00:15:58,668 and get as many people as possible involved. 234 00:15:58,944 --> 00:16:01,934 So we are planning a global crowdsourcing campaign 235 00:16:01,934 --> 00:16:05,399 targeting primarily GLAM staff. 236 00:16:05,580 --> 00:16:09,115 That is the people who have the up-to-date relevant knowledge, 237 00:16:10,620 --> 00:16:15,071 hoping that we can make it as easy as possible for them 238 00:16:15,248 --> 00:16:16,558 to start editing. 239 00:16:18,496 --> 00:16:23,136 And we will be asking people in the global Wikimedia community 240 00:16:23,136 --> 00:16:27,239 to help out and spread the word about the campaign 241 00:16:27,239 --> 00:16:29,132 in their local communities. 242 00:16:30,160 --> 00:16:34,518 We imagine that there are people around the world 243 00:16:34,518 --> 00:16:37,558 who have contact with GLAM institutions 244 00:16:37,558 --> 00:16:41,149 and who have the knowledge about their local Wikimedia communities 245 00:16:41,332 --> 00:16:46,322 that can help out for example if translating informational material 246 00:16:46,322 --> 00:16:51,044 or with organizing edit-a-thons for GLAM professionals. 247 00:16:52,545 --> 00:16:55,841 And you can find more information about that 248 00:16:55,841 --> 00:16:59,234 on the Finding GLAMs site on Meta. 249 00:17:03,968 --> 00:17:06,038 And we think that what we are doing 250 00:17:06,038 --> 00:17:09,129 is obviously a great goal to pursue 251 00:17:09,129 --> 00:17:12,668 because Wikidata is a powerful platform 252 00:17:12,668 --> 00:17:15,896 which enables and encourages re-use. 253 00:17:16,279 --> 00:17:19,148 So the data that we collect will benefit 254 00:17:19,148 --> 00:17:21,837 not only us in the Wikimedia community 255 00:17:21,837 --> 00:17:26,469 but also everyone who is interested in where there are 256 00:17:26,469 --> 00:17:29,360 cultural heritage institutions in the world. 257 00:17:29,664 --> 00:17:32,994 People such as researchers, journalists 258 00:17:34,295 --> 00:17:37,429 will be able to see and re-use that information. 259 00:17:38,369 --> 00:17:42,079 The data will also be available to search engines, 260 00:17:42,294 --> 00:17:46,767 which can be especially interesting for smaller GLAMs 261 00:17:46,970 --> 00:17:50,662 that do not have a strong presence on the Web. 262 00:17:50,922 --> 00:17:54,026 In Wikidata they can become visible. 263 00:17:56,576 --> 00:17:59,256 And for us in the Wikimedia project 264 00:17:59,256 --> 00:18:02,591 getting more GLAMs on Wikidata, 265 00:18:03,026 --> 00:18:07,223 it will enable us to better work with them, 266 00:18:07,223 --> 00:18:09,260 for example on Wikipedia. 267 00:18:10,058 --> 00:18:15,069 It would provide material for example for writing articles 268 00:18:16,244 --> 00:18:22,008 and it can benefit especially Wikipedias in languages 269 00:18:22,008 --> 00:18:24,256 with smaller communities 270 00:18:24,749 --> 00:18:29,719 which rely more and more on data from Wikidata 271 00:18:29,719 --> 00:18:33,294 in order to create and enrich articles. 272 00:18:34,047 --> 00:18:38,862 And this will bring more information about GLAMs 273 00:18:39,625 --> 00:18:43,655 to Wikipedias that have smaller communities 274 00:18:43,655 --> 00:18:48,304 and not enough resources to write and maintain those articles. 275 00:18:50,836 --> 00:18:52,594 And, as I said, you can find 276 00:18:52,594 --> 00:18:56,644 more information about our project in general 277 00:18:56,644 --> 00:18:59,392 and about the campaign that we are planning 278 00:19:00,224 --> 00:19:01,874 on Meta. 279 00:19:03,727 --> 00:19:04,954 Thank you. 280 00:19:06,088 --> 00:19:08,786 (applause) 281 00:19:12,643 --> 00:19:14,586 (chairman) Thank you very much. 282 00:19:14,713 --> 00:19:18,773 Does somebody have any questions? Yeah. 283 00:19:18,773 --> 00:19:19,910 (Alicia) Yes. 284 00:19:22,077 --> 00:19:23,317 (man 1) Thank you. 285 00:19:24,392 --> 00:19:25,538 Just kind of looking 286 00:19:25,538 --> 00:19:28,714 at the the number of libraries you've gotten, 287 00:19:28,807 --> 00:19:31,767 there are more libraries than are galleries. 288 00:19:31,767 --> 00:19:34,423 I'm going to make the wild assumption that there are. 289 00:19:34,423 --> 00:19:36,147 (Alicia) On Wikidata or in general? 290 00:19:36,147 --> 00:19:38,027 - (man 1) In the world. - (Alicia) In the world? 291 00:19:38,027 --> 00:19:41,871 Oh yeah. That's also a very... it's a bit of a weird number from IFLA. 292 00:19:42,112 --> 00:19:47,292 If you got their website, they have like "a map of coverage of libraries," 293 00:19:47,697 --> 00:19:50,782 and I do think that most of those 2.5 million, 294 00:19:50,782 --> 00:19:52,396 they are school libraries. 295 00:19:52,396 --> 00:19:53,428 (man 1) Right. 296 00:19:53,428 --> 00:19:55,711 (Alicia) They do show like how, what types... 297 00:19:55,912 --> 00:19:59,390 There are significantly more school libraries than public libraries. 298 00:19:59,390 --> 00:20:00,906 (man 1) But I was thinking 299 00:20:00,906 --> 00:20:02,896 because there are so many more libraries 300 00:20:02,896 --> 00:20:04,406 than there are, say, art galleries... 301 00:20:04,406 --> 00:20:05,446 Yes. 302 00:20:05,446 --> 00:20:07,927 (man 1) Like why did you limit the project to...? 303 00:20:07,927 --> 00:20:10,306 So why is it not a libraries project, 304 00:20:10,306 --> 00:20:12,326 for a start, or why is it a GLAM project 305 00:20:12,326 --> 00:20:14,316 and where does GLAM end because-- 306 00:20:14,316 --> 00:20:15,333 Oh yeah. 307 00:20:15,333 --> 00:20:18,019 (man 1) So you've got galleries, archives and museums, and stuff, 308 00:20:18,019 --> 00:20:21,068 but in terms of what we consider GLAM, 309 00:20:21,068 --> 00:20:22,958 like it's a bit more expansive than that, 310 00:20:22,958 --> 00:20:26,918 so is there kind of... would there be any ambition 311 00:20:26,918 --> 00:20:30,428 to perhaps, add another letter to the acronym or something? 312 00:20:30,428 --> 00:20:33,784 Well, we are not not working with expanding the acronym 313 00:20:33,784 --> 00:20:37,200 like we are officially sticking to the acronym 314 00:20:37,200 --> 00:20:39,137 because, well, that's the easiest. 315 00:20:40,134 --> 00:20:42,855 We got financing for that, 316 00:20:42,855 --> 00:20:45,448 and this is the easiest way of explaining this 317 00:20:45,448 --> 00:20:47,611 to non-Wikimedians, honestly. 318 00:20:48,520 --> 00:20:53,108 But we also use the term *cultural heritage institution*. 319 00:20:53,580 --> 00:20:55,406 And that is a bit broader. 320 00:20:55,770 --> 00:20:58,190 We use that in communication as well. 321 00:20:58,190 --> 00:20:59,860 For example we ingested some data 322 00:20:59,860 --> 00:21:05,245 about Swedish local cultural heritage associations 323 00:21:05,481 --> 00:21:06,821 that are technically... 324 00:21:06,821 --> 00:21:10,661 well, they are kind of like archives/museums/associations 325 00:21:10,661 --> 00:21:12,705 of people working in cultural heritage. 326 00:21:12,920 --> 00:21:17,216 And we decided that yes, this comes under our umbrella. 327 00:21:19,632 --> 00:21:21,732 [chairman] Can you pass him the microphone? 328 00:21:22,451 --> 00:21:23,591 (man 2) Hello. 329 00:21:24,451 --> 00:21:27,930 As I come from a community where we have the technical excuse 330 00:21:27,930 --> 00:21:30,690 but not like this organizing... 331 00:21:30,690 --> 00:21:35,784 Do you have any support from like your international team? 332 00:21:36,068 --> 00:21:41,488 Would you like materials or some press releases 333 00:21:41,488 --> 00:21:44,528 or letters to send through some contacts 334 00:21:44,528 --> 00:21:49,438 to engage more local institutions? 335 00:21:49,438 --> 00:21:51,133 They can join us 336 00:21:51,133 --> 00:21:55,713 but we can actually make all technical stuff ourselves. 337 00:21:56,833 --> 00:21:58,086 Yeah, this is a great question, 338 00:21:58,086 --> 00:22:02,671 and like if you check out the FindingGLAMs page on Meta, 339 00:22:02,671 --> 00:22:06,422 there is a section with information for regional coordinators 340 00:22:06,422 --> 00:22:11,622 where the point we are hoping to develop like an information toolkit 341 00:22:12,152 --> 00:22:15,724 that people can translate into their languages and use 342 00:22:16,814 --> 00:22:22,828 and something that we would really like to see from other local communities 343 00:22:23,013 --> 00:22:26,333 is communication about the datasets they have 344 00:22:26,333 --> 00:22:30,507 and the institutions that can help us out. 345 00:22:33,172 --> 00:22:34,632 (chairman) Anybody else? 346 00:22:37,151 --> 00:22:41,991 (woman) Well, I'm just thinking because I come from the library world 347 00:22:41,991 --> 00:22:46,021 and of course the IFLA statistics, 348 00:22:46,021 --> 00:22:48,987 they come from the different IFLA sections 349 00:22:48,987 --> 00:22:51,901 that feed up information to IFLA. 350 00:22:51,901 --> 00:22:57,355 But, anyway, in our respective countries 351 00:22:57,718 --> 00:23:02,798 we are interested in establishing repositories 352 00:23:02,798 --> 00:23:08,558 about up-to-date data about libraries and other GLAMs 353 00:23:08,661 --> 00:23:14,742 to end... well, the issues are of different kinds. 354 00:23:15,109 --> 00:23:17,629 There is gathering data, first of all, 355 00:23:17,629 --> 00:23:21,386 keeping them up-to-date, normalizing those data 356 00:23:21,386 --> 00:23:25,268 because it goes to the acronyms and things like that. 357 00:23:25,490 --> 00:23:30,498 So then it's also another issue-- 358 00:23:31,341 --> 00:23:35,985 the difference between the institution as corporate body inside 359 00:23:36,311 --> 00:23:39,920 that occupies or where the collections are. 360 00:23:40,334 --> 00:23:42,334 And just as an additional information, 361 00:23:42,334 --> 00:23:47,039 you mentioned the Archives Portal Europe, but Europeana is doing also 362 00:23:48,231 --> 00:23:51,221 work on this, that identifying their providers. 363 00:23:51,221 --> 00:23:52,562 - Exactly. - So they have more 364 00:23:52,562 --> 00:23:57,694 than 3,000 data providers, 365 00:23:57,694 --> 00:24:00,304 and they at some point, at the beginning, 366 00:24:00,304 --> 00:24:04,642 they didn't deal with the identification of the data providers. 367 00:24:05,183 --> 00:24:10,993 But the name that each of the data providers gave for itself 368 00:24:10,993 --> 00:24:12,797 or that Europeana 369 00:24:13,823 --> 00:24:18,344 associated the provider to the collection that was given to it 370 00:24:18,494 --> 00:24:21,704 was in different forms. 371 00:24:21,704 --> 00:24:26,214 At some point they found the need to normalize it, 372 00:24:26,214 --> 00:24:29,154 and so they get one back to the data providers 373 00:24:29,154 --> 00:24:32,763 asking them for the name and variant name 374 00:24:32,763 --> 00:24:38,771 so that it's disambiguation issues, identification issues 375 00:24:38,771 --> 00:24:43,105 so it's not a trivial problem. 376 00:24:43,105 --> 00:24:46,648 And I'm bringing that my experience from France 377 00:24:46,648 --> 00:24:53,170 that we have at least three repositories, three places 378 00:24:53,170 --> 00:24:55,808 because I saw the link to the French 379 00:24:55,808 --> 00:25:00,718 and I was wondering where did you get data from. 380 00:25:00,718 --> 00:25:03,899 There is an observatory of public lecture 381 00:25:04,106 --> 00:25:06,996 held by the Ministry of Culture-- 382 00:25:06,996 --> 00:25:08,916 I have not yet seen it 383 00:25:08,916 --> 00:25:10,620 There is another repository 384 00:25:10,620 --> 00:25:16,580 held by the Union Catalog of France 385 00:25:16,580 --> 00:25:23,388 that identifies all the libraries that hold collections with information 386 00:25:23,491 --> 00:25:28,401 extended beyond the identification of the institution as such 387 00:25:28,401 --> 00:25:33,155 but with opening hours and the collections that they hold. 388 00:25:33,155 --> 00:25:34,385 And there is another-- 389 00:25:34,385 --> 00:25:35,681 (chairman) Quick question. 390 00:25:35,681 --> 00:25:39,297 (woman) Well, I'm just wondering about, 391 00:25:40,423 --> 00:25:43,880 first of all, the best data model 392 00:25:43,880 --> 00:25:49,340 to identify these institutions, 393 00:25:49,671 --> 00:25:55,025 and the best way to communicate 394 00:25:55,025 --> 00:25:59,065 with the communities that do have those data 395 00:25:59,065 --> 00:26:01,519 and keep them up-to-date 396 00:26:01,519 --> 00:26:04,619 so that there is no gap between what you have 397 00:26:04,619 --> 00:26:09,950 and where the information routes from. 398 00:26:10,155 --> 00:26:11,215 (Alicia) Thank you. 399 00:26:11,215 --> 00:26:12,635 Data modeling that you mentioned, 400 00:26:12,635 --> 00:26:15,275 the distinction between institution and physical place, 401 00:26:15,275 --> 00:26:18,548 this is a discussion that we have taken up 402 00:26:18,548 --> 00:26:21,775 in the community discussion on Wikidata. 403 00:26:21,775 --> 00:26:25,244 This is something that is definitely within the interest of the community. 404 00:26:25,244 --> 00:26:27,184 It is being actively discussed. 405 00:26:27,911 --> 00:26:29,431 (woman) Thank you. 406 00:26:29,431 --> 00:26:30,551 Yes. 407 00:26:30,551 --> 00:26:35,271 (chairman) One last very short question before we have to end here? 408 00:26:36,991 --> 00:26:38,391 (man 3) Excuse me. 409 00:26:39,288 --> 00:26:42,068 Museums and archives exist on a continuum-- 410 00:26:42,068 --> 00:26:43,945 at the big end you have the British Museum 411 00:26:43,945 --> 00:26:45,308 and the Hermitage, and so on, 412 00:26:45,308 --> 00:26:46,351 but at the other end 413 00:26:46,351 --> 00:26:49,181 you have a garden shed with a few objects in 414 00:26:49,181 --> 00:26:52,620 or you have glass cases in the foyer of a company 415 00:26:52,620 --> 00:26:54,502 with some historical artifacts. 416 00:26:54,730 --> 00:26:57,870 Have you a cut off point? And if so, where is it? 417 00:26:57,870 --> 00:27:01,160 We don't have so much free available data 418 00:27:01,160 --> 00:27:04,380 that we really need to have a cut off point. 419 00:27:04,380 --> 00:27:06,790 It's rather the exact opposite. 420 00:27:06,790 --> 00:27:10,681 If we get a nice, beautiful free dataset 421 00:27:10,923 --> 00:27:14,588 that has this sort of very, very granular distinction, 422 00:27:14,588 --> 00:27:16,078 then we will worry about it, 423 00:27:16,078 --> 00:27:19,975 but it's not a problem that we have encountered yet practically. 424 00:27:20,821 --> 00:27:22,781 (chairman) Okay, thanks a lot for your questions 425 00:27:22,781 --> 00:27:24,611 and your reactions and answers. 426 00:27:24,611 --> 00:27:26,349 We have to end here 427 00:27:26,349 --> 00:27:31,611 and invite you to the classroom next to this one for the final session. 428 00:27:31,611 --> 00:27:32,749 Thank you very much. 429 00:27:32,749 --> 00:27:35,399 (applause)