{"id":6303,"date":"2026-04-27T09:06:54","date_gmt":"2026-04-27T07:06:54","guid":{"rendered":"https:\/\/weblearning.co.za\/blog\/?p=6303"},"modified":"2026-09-14T10:47:27","modified_gmt":"2026-09-14T08:47:27","slug":"spatial-lens-part-3","status":"publish","type":"post","link":"https:\/\/weblearning.co.za\/blog\/spatial-lens-part-3\/","title":{"rendered":"Spatial lens (part 3)"},"content":{"rendered":"\n
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Field Notes by @visualthinkery<\/a> is licensed under CC-BY-SA<\/a>.

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The third post is about maps personal cartography and my (fr) “g\u00e9omatique” attempts with geodata. I’ll explore a data centred \u201cmap\u201d, generated “automatically” with spatial data infrastructure. <\/p>\n\n\n\n

Instead of a \u201cnormal\u201d hand drawn map (see the map of the 19th arrondissement of Paris below), or a map with a particular boundary with labels (see the Parc de la Villette<\/a> map on Codepen and the corresponding 19th Arrondissement.geojson<\/a> on Github). I’ll generate an Arts Festival query and compare Arts festivals in two countries and make it possible to download available information.

Firstly – how many ARTs Festivals are on Wikidata? Look at https:\/\/w.wiki\/MHP7<\/a> or visit query.wikidata.org<\/a>. You’ll see instructions to answer the question. “Count the instances (P31) of arts festivals (Q4801521)”. <\/p>\n\n\n\n

title: Number of Arts Festivals on Wikidata\nSELECT (COUNT(*) AS ?count)\nWHERE {\n?item wdt:P31\/wdt:P279*   wd:Q4801521\n}<\/code><\/pre>\n\n\n\n
The answer to this numbers question will vary as it depends on the available data and how well I constructed the query.<\/p>\n\n\n\n
Resources Used <\/h4>\n\n\n\n
Sites like  Geojson<\/a> \/ Wikidata<\/a> \/ Wikimedia Commons<\/a> \/Leaflet<\/a>\/ SPARQL<\/a>\/ Overpass Turbo<\/a> offer access to openly licensed data, which allowes me to remix and re-use materials under stated conditions. I can combine these resources, to make  layers of information visible. Sounds complicated? Yup! Demonstrable? I think so. Can others do this. Absolutely Yes! Please feel free to copy and paste.

Disclosure:<\/strong> I used chat GPT  <\/p>\n\n\n\n
Paris and Clarens<\/h4>\n\n\n\n
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Anonyme, graveur, CC0, via Wikimedia Commons<\/figcaption><\/figure>\n\n\n\n
I am off to Paris in July on a scholarship. As part of my preparation, I have been looking at Parisian maps and plotting out places \/ events that I want to visit \/attend. There’s Bastille Day on the 14th (I’ll just miss that one) and the Paris-Plages<\/a> (how cool, fake beaches on the Seine).<\/p>\n\n\n\n
I’\u2019m not only mapping small parts of Paris. The Clarens Arts Festival<\/a> is on Wikipedia and I made a key locations map<\/a> for Nicola Martins.    <\/p>\n\n\n\n
With my data driven spatial specs on, I\u2019m going to make an arts festivals map. I\u2019ll show you how to\u2026.<\/p>\n\n\n\n
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  1. make a map base layer<\/strong> which will contain markers to arts<\/strong> festival locations<\/strong> in South Africa and in France<\/li>\n\n\n\n
  2. position the festivals and each location on the base layer map. When clicked, a label  will appear with a corresponding image (if it exists). Each festival will have a Wikidata number (for update purposes).  <\/li>\n\n\n\n
  3. build the base layer map and marker on Leaflet and on a table. Data will be supplied by an openly licensed GeoJSON file generated by the SPARQL and formatted for the chart.<\/li>\n<\/ol>\n<\/div><\/div>\n\n\n\n
    Wikidata, Commons, Wikipedia and OpenStreetmaps have been extremely useful as resources. They often contain co-ordinates, included map modules<\/a>, OSM templates<\/a> that pull in openstreetmap data or geoshapes (P3896). These worked exemplars have permitted me see how map shapes are generated and stored as points, lines or polygons. I\u2019ve also started a collection of GeoJSON files<\/a> on GitHub. Yes, Chat GPT, Leaflet<\/a> and CodePen have shown how a static GeoJSON file can be turned into a visual. You can do the same (and change the parameters quickly using SPARQL). The generated file could then be archived on Wikimedia commons, built into the map itself, or uploaded as a raw file to GitHub or be included in a spreadsheet. These GeoJSON files can also be generated by using https:\/\/overpass-turbo.eu\/<\/a>  I’m very sure that there are more options. Its always helpful to have plan B.<\/p>\n\n\n\n
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    Beads and baskets and SPARQL<\/h3>\n\n\n\n
    So, we are exploring some abstract concepts. To help me pull vague abstractions together into a clear explanation, I like think about something physical and concrete. Instead of festivals, I’ll use beads and think about \u201ctrays\u201d,  “baskets” and “weaves”. You might have to think of your own.<\/p>\n\n\n\n
    Why physical and concrete? Let’s use another abstract concept. Time! By itself, time is hard to imagine.  When you picture a clock with numbers, long and short hands,  a clock face and a seconds hand ticking loudly as it passes these numbers. Then time’s passage becomes easier to notice and comprehend. <\/p>\n\n\n\n
    Querying SPARQL is also quite vague. So I’d like you to imagine you have scooped up some pretty beads and sorted them by colour. You need to store these beads somewhere, so you pop them into different baskets. Now assume that you have a range of beads and baskets. It gets quite difficult to remember which basket you placed which colour beads in. So you give the basket a label which links these basket and the beads in your mind. Now lets also assume that beads represent different things. Status, wealth, spiritual values. The basket label becomes is a “memory location” and the beads therein are arranged and categorized around that memory location. Now lets say that beads are not only about colours. Beads could also a way of communicating emotions in different languages. Our basket labels become more complicated. There are more variables introduced, or \u201cmemory locations\u201d and the beads (when seen in relation to other beads) hold multiple meanings.<\/p>\n\n\n\n
    A Query Service<\/a> called SPARQL allows me to locate beads (stored entities ) in baskets (memory locations). These beads and baskets are on Wikidata (a sister project of Wikipedia) and I can combine them in different permuatations . In this case SPARQL is going to help us identify Arts Festivals in South Africa and in Arts Festivals France. Each SPARQL query is an instruction. Go into a room that contain a wide mixture and assortment of beads. Use the baskets and sorting trays.  Press play to execute a query and extract the desired beads from identified baskets. Then fill a tray with a particular collection of those beads. 
    After that, you will string the beads together and attempt to make meaning. Drawn from matching colours or perhaps it through a Zulu love letter. The meaning could be stitched into a an image grid, a map or a graph.<\/p>\n\n\n\n
    Making sense of variables<\/h4>\n\n\n\n