Standorte geförderter Kultureinrichtungen (See https://daten.berlin.de/datensaetze/standorte-gef%C3%B6rderter-kultureinrichtungen)

Gist 73100dba40164b493edf7af63649a498

This map shows a guided tour of Berlin in 1947, with markers placed at historical sites like the Fasanenstrasse Synagogue and Charlottenburg Gate. Each marker includes photographic images and descriptive text retrieved from the GeoJSON data. The visualization uses d3.geoPath to render the map and d3.forceSimulation to position the markers, with the tour data loaded from a local JSON file.

Gist cd9f60b16fb12aa5693b

This example visualizes a geolocated point on a Berlin map, showing the Poststadion Football Complex with an interactive marker. The code uses d3.geoPath to render the map geometry and a custom point layer for the marker, with properties like marker-color and marker-symbol styled via SVG. The visualization embeds a popup containing three images—two photographs and a YouTube video—accessed through HTML strings in the feature properties. It relies on the GeoJSON format for data storage and d3.forceSimulation for potential layout adjustments, though the primary rendering uses standard D3 projection and path methods.

Sample Point for Mapping Berlin

This example visualizes a single sample point in Berlin, locating Friedrichstraße at coordinates 13.386978, 52.520289 within a geospatial context. It highlights a specific place of interest tied to a spring 2015 series and a 1970 tour, using a yellow medium-sized marker with a rail-metro symbol. The visualization relies on a GeoJSON Feature object, which is parsed and rendered through a mapping library such as D3’s `geoPath` for projecting coordinates, while the marker’s style properties—`marker-size`, `marker-color`, and `marker-symbol`—are applied via SVG or Canvas drawing. The source data is a raw gist file, indicating a minimal, focused point-mapping example rather than a complex thematic map.

GLAM

This map shows a collection of museums and libraries in Berlin from the GLAM tour series, with each location represented as a green marker. The visualization is built from GeoJSON data containing points with coordinates, titles, Wikidata links, and associated images. The map emphasizes the spatial distribution of cultural institutions across the city, with markers color-coded in green and labeled with museum symbols. The underlying data appears to be sourced from Wikidata and processed through a Cloudant database, suggesting a workflow for curating and displaying location-based cultural heritage data.

test

This example visualizes a single point feature from a GeoJSON file, marking the location of Friedrichstraße in Berlin. The map uses D3’s `d3.geoPath` to render geographic outlines, while the point itself is drawn with SVG markers. The feature’s properties include an image carousel with historical photos, toggled by user interaction. The code relies on D3’s data binding and event handling to update the displayed images, and the geographic coordinates are parsed from string values in the GeoJSON. The rendering approach uses a standard Canvas or SVG projection, though the specific projection library is not shown. The source is a gist by CliffordAnderson, with data embedded directly in the file.

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Stolpersteine in Berlin

A map of Berlin displays thousands of Stolpersteine memorial stones as individual points, each marking the last known residence of a Holocaust victim. The visualization uses D3.js with `d3.forceSimulation` to handle spatial collision detection, preventing markers from overlapping at dense locations while `d3.geoPath` renders the city’s street and district boundaries. Hovering a point reveals the person’s name, address, deportation date, and murder site from the embedded GeoJSON data, with a tooltip built from the properties fields. Points are colored by the deportation destination, such as Auschwitz or Theresienstadt, providing an immediate sense of historical scale across the city.

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Gist 9af806e8acc168aa10c06099d668b711

This example presents an interactive map of historical Berlin locations from 1947, using GeoJSON point features to mark sites like the Synagogue Fasanenstrasse and Charlottenburg Gate. Each marker opens a popup with period photographs and captions, rendered through a Mapbox-like interface. The visualization relies on a custom marker system with symbol and color properties, while the underlying tour.json data drives the geographic placement and content. The implementation uses standard web mapping libraries to handle GeoJSON rendering and marker interactions, showing how archival image collections can be geolocated and explored.

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Sample Berlin Point

This example maps a single point from a GeoJSON file, representing the Berlin Chancellary, onto a map. The visualization displays the point’s coordinates and associated properties, including a marker symbol, color, and an embedded image with a caption. The code uses d3.geoPath to render geographic features and relies on the GeoJSON data structure to define the point’s location and metadata. The marker is styled using the properties for size, color, and symbol, while the image is presented as an HTML string within the data. The source is a gist authored by CliffordAnderson, with the point data drawn from the Spring 2015 series and a 1970 tour reference.