Daniel, A few other research projects that have used Wikipedia/Wikidata to generate "maps" of concepts that are not explicitly spatial and might be relevant to your thinking. I'm only aware of a live demo for the second one ( Frankenplace <http://frankenplace.com/>) but the papers have good figures to illustrate:
- Hecht, Brent, et al. "Explanatory semantic relatedness and explicit spatialization for exploratory search." Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval. 2012. <https://www.brenthecht.com/publications/bhecht_sigir2012_ExpSpatialization_SRplusE.pdf> - Adams, Benjamin, Grant McKenzie, and Mark Gahegan. "Frankenplace: interactive thematic mapping for ad hoc exploratory search." Proceedings of the 24th international conference on world wide web. 2015. <http://www2015.thewebconf.org/documents/proceedings/proceedings/p12.pdf> - Sen, Shilad, et al. "Toward Universal Spatialization Through Wikipedia-Based Semantic Enhancement." ACM Transactions on Interactive Intelligent Systems (TiiS) 9.2-3 (2019): 1-29. <https://dl.acm.org/doi/fullHtml/10.1145/3213769> Best, Isaac On Mon, Dec 19, 2022 at 5:37 PM Daniel Mietchen via Wikidata < wikidata@lists.wikimedia.org> wrote: > Dear Tassos, > > thanks for the example - that map is interesting but still arranged in > terms of geocoordinates, and based on Wikipedia data. > What I had in mind is a map that positions Wikidata items generically > (i.e. without the need for geolocation statements via P625) but > somewhat reliably (for a given query and reasonably stable data) in a > 2D or 3D space (perhaps even as a function of some additional > parameters) and then allows the user to zoom around inside this system > to explore spatial relationships just as they can explore geospatial > relationships in your gelocated wiki atlases. > The closest thing to this that I have at hand right now is > https://galaxy.opensyllabus.org/ , which clusters syllabi by topic and > allows zooming but is not based on Wikidata. > The Wikidata Query Service has some visualizations that do part of > that but these (i) do not provide zooming, (ii) often time out and > have other problems, e.g. (iii) no reliable position of a given node > or (iv) little to no meaning in adjacency. > > Another thing relevant here are Wikidata maps as per > https://commons.wikimedia.org/wiki/Wikidata_map > with their bright and dark areas and in particular their evolution over > time > All of these provide for fertile ground to engage relevant > communities, and It would be very helpful to have similar > visualizations (e.g. change as a function of some parameter) for any > part of Wikidata, including but not limited to geodata. > > Best, > > Daniel > > > > On Sat, Dec 17, 2022 at 10:57 PM Tassos Noulas <tnou...@gmail.com> wrote: > > > > Hi Daniel, > > > > The project described here may be in line with what you are suggesting: > > > https://www.theverge.com/2022/7/29/23283701/wikipediate-notable-people-ranking-map-search-scroll-zoom > > > > But could I be asking: what use case you had in mind? Why would I want > to see a bunch of non geo entities on a map and what value would I extract > from this aside from pure fun? I am not saying that fun is not worth it btw > :), but one of the challenges we have been having with the tool is > narrowing down to specific use cases that empower users and hopefully the > Wikipedia ecosystem (you can imagine users crowdsourcing info through a > cartographic/mobile platform in the future). > > > > The idea of parameterized url has been somewhat developed: > > > https://wiki-atlas.org/?wikipage=Stuyvesant_Town%E2%80%93Peter_Cooper_Village&lon=-73.97778153419495&lat=40.731669455258725&lang=en > > > > But it is not serving all purposes in its current form and I think > connecting entities based on QIDs as you suggest is a great idea. In > addition to linking better the wiki entities with a map, and vice versa, we > could exploit Wikidata’s querying functionality to allow for way more > complex filtering approaches to those the tool currently offers (based on > popularity, categories, keywords). > > > > Best, > > Tassos > > > > On Sat, 17 Dec 2022 at 19:43, Daniel Mietchen < > daniel.mietc...@googlemail.com> wrote: > >> > >> Dear Diego, Aidan and Benjamin, > >> thanks for working on such functionality - both tools seem to be quite > >> useful already. > >> One way to abstract things out further would be to facilitate a > >> mapping (e.g. heatmaps) of non-geo things - for example basketball > >> players by number of points, perhaps with filters per season or club. > >> Is anyone here thinking in such directions? > >> Another request would be to have parametrized URLs based on QID and > >> perhaps type or language, e.g. > >> http://www.wiki-atlas.org/English/museums/Q7877613 or some such. > >> Best, > >> Daniel > >> > >> On Sat, Dec 17, 2022 at 2:36 AM Aidan Hogan <aid...@gmail.com> wrote: > >> > > >> > Hi Diego, > >> > > >> > Thanks for the pointer; this is very cool! We would be happy to share > >> > experiences. (It's very impressive how many points you are able to > >> > render, and how these resize at different scales!) > >> > > >> > Indeed it seems we were not so original with the name. :) > >> > > >> > It seems both systems offer two different functionalities: one focuses > >> > on the "what's close to here" functionality, while the other focuses > on > >> > the "where in the world are there X" functionality, like "where in the > >> > world are there lighthouses [1]", but generalised to all the types in > >> > Wikidata. It would be interesting to see how these two modalities > could > >> > be combined in future maybe? > >> > > >> > Best, > >> > Aidan > >> > > >> > [1] https://www.lightphotos.net/photos/map_all.php > >> > > >> > On 2022-12-16 21:45, Diego Saez-Trumper wrote: > >> > > Hi Aidan, > >> > > > >> > > With Tassos and Rossano, we have a similar project (same name in > fact). > >> > > You can check-it out here: www.wiki-atlas.org > >> > > <http://www.wiki-atlas.org>, maybe we could exchange some > experiences > >> > > about it. > >> > > > >> > > Best, > >> > > Diego > >> > > > >> > > _______________________________________________ > >> > > Wikidata mailing list -- wikidata@lists.wikimedia.org > >> > > Public archives at > https://lists.wikimedia.org/hyperkitty/list/wikidata@lists.wikimedia.org/message/4ZE6CWFNHOYQH47DEXJKT7J4P2ASSQVN/ > >> > > To unsubscribe send an email to wikidata-le...@lists.wikimedia.org > >> > _______________________________________________ > >> > Wikidata mailing list -- wikidata@lists.wikimedia.org > >> > Public archives at > https://lists.wikimedia.org/hyperkitty/list/wikidata@lists.wikimedia.org/message/H2JPDXIET5I2ZXZOUXQNJDCAF4FXJAOP/ > >> > To unsubscribe send an email to wikidata-le...@lists.wikimedia.org > _______________________________________________ > Wikidata mailing list -- wikidata@lists.wikimedia.org > Public archives at > https://lists.wikimedia.org/hyperkitty/list/wikidata@lists.wikimedia.org/message/KGWYQFWIXXGJWRTS7UGQYSUOZPFCBYS7/ > To unsubscribe send an email to wikidata-le...@lists.wikimedia.org > -- Isaac Johnson (he/him/his) -- Senior Research Scientist -- Wikimedia Foundation
_______________________________________________ Wikidata mailing list -- wikidata@lists.wikimedia.org Public archives at https://lists.wikimedia.org/hyperkitty/list/wikidata@lists.wikimedia.org/message/D7ZPZKVG5FK72YFZDNNSN6RI63EQRKSD/ To unsubscribe send an email to wikidata-le...@lists.wikimedia.org
