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Unofficial web viewer for the Roman Roads Research Association's Digital Britannia v1 dataset: Roman roads, forts, camps, settlements and milestones over LiDAR, historic OS maps and aerial imagery.
DataPythonGitHub @adriancoOnlineOwner unconfirmed
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Visualiser for the RRRA's roman road dataset
Taken from the repository README
Loading the full README.
Read the full README ↗Visualiser for the RRRA's Roman road dataset.
An unofficial web map viewer for Digital Britannia v1 from the Roman Roads Research Association. It shows the dataset's engineered Roman roads, forts, temporary camps, settlements, milestones and Hadrian's / Antonine Wall features over LiDAR hillshade, historic OS maps and aerial imagery.
Data: Digital Britannia v1, © Roman Roads Research Association / Mike Haken. CC BY-NC 4.0, non-commercial use only. This viewer is not endorsed by the RRRA.
The map is live at https://adrianco.github.io/romanroads/, served by
GitHub Pages from the docs/ folder of main. Each push to main redeploys
it within a minute or two.
The viewer fetches its GeoJSON over HTTP, so opening docs/index.html straight
from disk (file://) won't work. Serve the docs/ folder instead:
python3 -m http.server 8765 --directory docs
Then open http://localhost:8765.
Housesteads), a Roman
name (Vercovicium) or a road number (RR2, 2a). Road results zoom to the
whole route.#zoom/lat/lon), so you can share a link to
a specific spot.scripts/process.py). The GeoPackage's layers are
reprojected from British National Grid (EPSG:27700) to WGS84 (EPSG:4326) and
written as one GeoJSON file per layer.
Legionary Fortress / Legionary fortress), one garbled settlement
type, NULL text glued onto values (which broke some links), and padding
whitespace. The GeoPackage itself is never modified.layer_styles table. Roads are solid / dashed / dotted by
confidence; sites are coloured by type, as in the author's project.docs/index.html). A single page using MapLibre GL JS, with no
build step and no API keys. The full-fidelity data is 4.19 MiB in total,
under the 5 MB budget for a single page, so no vector-tile pipeline was
needed.docs/ERRATA.md). Every data issue found along the way, with
counts and examples, written up for the RRRA's next release.docs/adr/.Segment Confidence: solid = certain ±30 m,
dashed = probable ±200 m, dotted = conjectured. "No evidence" segments are
hidden by default. Margary RR number labels. Roads get a white halo so they
stay readable over the underlays.Why each source was chosen, and why others were rejected, is in ADR 0012.
data/digital-britannia_v1.gpkg source GeoPackage (EPSG:27700)
scripts/process.py GeoPackage -> per-layer GeoJSON (EPSG:4326)
requirements.txt pinned Python dependencies
docs/index.html the viewer (single page, MapLibre GL JS)
docs/data/*.geojson processed layers + manifest.json (itinere.geojson = Britain subset)
data/external/ third-party downloads (gitignored)
docs/ERRATA.md data issues to report back to the RRRA
docs/adr/ architecture decision records
python3 -m venv .venv
.venv/bin/pip install -r requirements.txt
.venv/bin/python scripts/process.py
The Itiner-e comparison layer comes from a 33.6 MB empire-wide file that isn't
committed. Only the Britain subset (docs/data/itinere.geojson) is. To rebuild
it, download itinere_roads.gpkg from
Zenodo record 17122148 into
data/external/ (gitignored) and rerun the script. Without the file, the
script keeps the committed subset.
Pleiades matching works the same way. Download pleiades-places-latest.csv.gz
and pleiades-names-latest.csv.gz from
the Pleiades dumps into
data/external/pleiades/, and the script re-matches and rewrites
data/pleiades_matches.csv and data/unmatched_pleiades.csv. Without
them, it reuses the committed match table.
A blog post records the development process over two days. Dev.to blog
data/unmatched_pleiades.csvVERCOVICIVMDurnovariaDVROVARIA