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ttl3d

PyPI DOI tests license: MIT python 3.10+

Turn any Turtle / RDF graph into a single self-contained HTML page with a 3D view (shaded spheres) and a 2D view (a flat canvas), permanent labels, predicate labels on the edges, a clickable legend, label search, and a detail card for every node. The page embeds all of its JavaScript, so it opens from a file, works offline, and never sends your data anywhere.

Try it in your browser: the Solar System demo (as two Turtle files, and as one TriG dataset with named graphs), FOAF, SKOS, PROV-O and the Pizza ontology, each a page ttl3d generated.

ttl3d: orbit the Solar System demo in 3D, filter by legend, open a card, switch to 2D

Why

Ontology editors show class trees. SPARQL browsers show one neighbourhood at a time. Sometimes you want the whole graph on screen at once: to see which modules actually connect, which file asserted which edge, or which node everything hangs from. ttl3d was written for exactly that while building a multi-file ontology, then generalized to any RDF input.

Install

Python 3.10 or newer.

pip install ttl3d

For the development version, pip install git+https://github.com/soheilabadifard/TTL_to_3D, or clone the repository and run pip install -e .. The dependencies are rdflib, networkx, numpy and scipy, all available on conda-forge as well.

Quick start

ttl3d examples/solar-system.ttl examples/solar-system-missions.ttl -o solar.html

Open solar.html in any browser. Pass several files and they merge into one graph; the default colouring then shows which file declared each node and which file asserted each edge. A TriG or N-Quads file works the same way: each of its named graphs is treated as a file of its own:

ttl3d examples/solar-system.trig -o solar-graphs.html

The same Solar System as one TriG dataset: the schema in the default graph, the bodies and the missions in two named graphs, one legend row each.

Without installing, run the module from a clone: python -m ttl3d ....

Python and notebooks

Open in Colab

The same pipeline is a function call (pip install "ttl3d>=0.4.0"). Sources are file paths, rdflib.Graph or rdflib.Dataset objects, ttl3d.Query objects (a CONSTRUCT against a SPARQL endpoint), (name, source) pairs or a {name: source} mapping, in any mix; the options are the command line's (focus, hops and schema included).

import rdflib, ttl3d

g = rdflib.Graph().parse("solar-system.ttl")
ttl3d.write(["solar-system.ttl", "solar-system-missions.ttl"], "solar.html", view="2d")
html = ttl3d.to_html(("planets", g), color_by="type")        # the page as a string
ttl3d.show(("planets", g), height=500)                       # last line of a notebook cell: shown inline

show returns a page that Jupyter, JupyterLab, VS Code and Colab display as a sandboxed iframe with the whole page inside, so nothing is written and no server is needed; each output stores about 1.9 MB in the notebook. Errors are raised, never printed. examples/ttl3d.ipynb is the notebook behind the badge.

Options

Option Values Meaning
- (as a file) Read standard input, parsed as --format or Turtle; the page and the default output name are called stdin. Relative IRIs resolve against the working directory (a file's resolve against its folder); declare @base to be explicit.
-o, --out path Output file. Default: <first source's name>-<view>.html in the current directory (a file's stem, stdin, a query file's stem, or the endpoint's host for inline query text).
--color-by file (default), type, namespace What node colours and the legend mean. In file mode edges also take the colour of the file asserting them. A named graph of a TriG or N-Quads file counts as a file.
--layout auto (default), stress, force stress pins every node to a precomputed Kamada-Kawai position, one layout per view (3D and 2D); force runs the live simulation. auto picks stress up to 1000 nodes.
--labels auto (default), always, hover Permanent label sprites. auto keeps node labels up to 800 nodes and edge labels up to 800 links; hover leaves tooltips only.
--view 3d (default), 2d Starting view. The page has a 3D | 2D switch either way, and each view is pinned to its own stress layout.
--title text Page title. Default: the first source's name (a file's stem, stdin, a query file's stem, or the endpoint's host for inline query text).
--lang language tag, default en Preferred language for labels and definitions. Untagged literals rank next; other languages become synonyms on the card. Matched exactly: --lang en does not select @en-GB.
--format rdflib parser name Force a parser for every input (turtle, xml, nt, json-ld, trig, nquads, ...). Default: guess from the extension, then try Turtle.
--type-links flag Draw rdf:type as an edge from each instance to its class instead of listing it on the card only.
--attribute-preds prefix:local, full IRI, or <urn:...> Predicates to keep off the picture and show on the card, e.g. foaf:homepage,rdfs:seeAlso. Repeatable; wrap a URN or mailto in angle brackets.
--focus prefix:local, full IRI, or <urn:...> Keep only this node's neighbourhood (with --hops). Repeatable or comma-separated.
--hops integer, default 1 How many link steps from a focus node to keep; 0 keeps the focus nodes only. Needs --focus.
--schema flag Keep classes and properties only: the schema, without instances.
--endpoint URL A SPARQL endpoint (http or https) to run every --query against. Credentials come from TTL3D_SPARQL_USER and TTL3D_SPARQL_PASSWORD (HTTP Basic) or TTL3D_SPARQL_TOKEN (Bearer), never from the command line; a URL carrying user:password@ is refused.
--query CONSTRUCT ... or @file.rq A CONSTRUCT or DESCRIBE query whose result is a source: a legend row named after the file, or after the endpoint's host for inline text. Repeatable. SELECT, ASK and updates are refused before anything is sent.
--timeout seconds, default 60 How long to wait for each network step (connect, read) of the endpoint's answer; one attempt, no retry.
--max-mb megabytes, default 100 The largest answer to accept; a bigger one is refused with a hint to narrow the query. Parsing needs about 35 times an N-Triples answer's size in memory, and more for Turtle.
--version flag Print ttl3d <version> and exit.

Input formats are guessed from the extension (.ttl, .nt, .n3, .rdf, .owl, .jsonld, .trig, .nq, ...) through rdflib. A quad format (TriG, N-Quads, TriX, JSON-LD with named @graph blocks) loads every named graph, and each named graph is a source like a file: a legend row of its own, named by its prefixed IRI (ex:planets, or the full IRI when no prefix covers it; the IRI itself is the row's hover text and appears on the cards), while the file's default graph keeps the file's name. The same graph IRI in several files is one source.

  • A node is every IRI that is the subject of some triple or the object of a link, except IRIs of the RDF, RDFS, OWL and XSD vocabularies and ontology headers (owl:Ontology). Blank nodes are skipped.
  • A link is an IRI-to-IRI triple whose predicate is a relation. rdf:type, owl:imports, owl:versionIRI, owl:priorVersion, rdfs:isDefinedBy, prov:wasDerivedFrom and dcterms:source describe the node instead and go to its card. Parallel edges collapse into one link listing every predicate.
  • Label: rdfs:label, else skos:prefLabel, else the local name. Definition: skos:definition, else rdfs:comment, else dcterms:description. Every other literal lands in the card's property table.
  • Each node remembers the file or named graph that first declares it, in the order sources and their graphs first appear; each link remembers the files or graphs asserting it. Every source has a legend row: a file that only adds edges between other files' nodes selects those edges, and a file that only annotates (labels, comments) gets a muted row that says so, since nothing it asserts is drawable.
  • An edge asserted in both directions (:Luna :orbits :Earth and :Earth :hasMoon :Luna) is one link labelled orbits ⇄ hasMoon, without an arrowhead.
  • Labels follow --lang: the requested language first, then untagged literals, then anything else; every other label value becomes a synonym on the card, and a rdfs:comment that loses to a skos:definition still appears in the property table.
  • Namespaces follow the prefixes the inputs bind: an IRI is cut at its last / or # when that namespace is bound, otherwise at the longest bound namespace it extends without a further / or # (so urn: vocabularies shorten too), otherwise at the last / or #. Legend keys, the namespace column and local names all use this one rule.

Slicing a big graph

A knowledge graph of a million triples is not a picture. Two questions are, and both are answered at build time, before the layout runs:

ttl3d examples/solar-system.ttl examples/solar-system-missions.ttl --focus :Earth --hops 2 -o earth.html
ttl3d examples/solar-system.ttl examples/solar-system-missions.ttl --schema -o schema.html

--focus keeps a node and everything within --hops link steps of it, in both directions; rdf:type and the other card-only predicates are not steps unless --type-links makes them edges, and with --type-links every kept node's classes come along so no card loses its type. --schema keeps the classes and properties (anything typed as one, used as a type, or joined by rdfs:subClassOf, rdfs:subPropertyOf, rdfs:domain, rdfs:range, and the OWL equivalence, inverse and disjointness predicates) and drops every instance; with --focus as well, the walk stays inside the schema, and a focus that is itself an instance is kept. A kept node keeps its labels, literals, blank-node structure and card-only attributes (a dcterms:source target outside the slice shows as an IRI); an edge survives only when both ends do; a source left with nothing loses its legend row, and a node's source is the first source that still says something about it in the slice. ttl3d says what it kept on stderr: kept 12 of 41 nodes (focus :Earth, 2 hops). The same three keyword arguments exist on ttl3d.to_html, write and show.

Slicing does not skip the parse: rdflib reads about a million triples in 13 seconds and 2.3 GB (measured on a 200-class, 200,000-instance file), after which a two-hop slice builds in under 1.5 seconds and a schema slice in under 1.5 seconds. The cost of a slice follows the triples that survive, not the nodes: one subject with 200,000 literal attributes took 4 seconds at hop 0.

From a SPARQL endpoint

A triple store is drawn without exporting it: a CONSTRUCT (or DESCRIBE) query is a source like a file, fetched at build time with one POST and never from the page.

ttl3d --endpoint https://query.wikidata.org/sparql --query @examples/wikidata-moons.rq -o moons.html
# fetched 916 triples from query.wikidata.org in 0.7 s
# computing stress layouts (3D and 2D) for 308 nodes...
# 308 nodes, 300 links -> moons.html (view: 3d, layout: stress, labels: node+edge)

--query repeats, each result its own legend row, and files and queries mix in one page. The query's PREFIX lines name the page's namespaces, so an endpoint that answers in N-Triples still gets short names; relative IRIs in an answer resolve against the endpoint. Protected endpoints take TTL3D_SPARQL_USER/TTL3D_SPARQL_PASSWORD or TTL3D_SPARQL_TOKEN from the environment, and nothing ttl3d prints shows them. ttl3d sends them to whatever endpoint the command names, so set them for one command (TTL3D_SPARQL_TOKEN=... ttl3d ...) rather than exporting them; the fetch line on stderr says when credentials went out, and when they went over plain http. Errors are one line: a query that is not CONSTRUCT or DESCRIBE is refused before anything is sent, an HTTP error quotes the endpoint's first line, a slow endpoint stops at --timeout (60 s per network step by default), a redirect is refused with the URL to use, and an answer that is not RDF (Turtle, N-Triples, RDF/XML, N3 or a quad format; JSON-LD is refused too), is larger than --max-mb (100 MB) or breaks off midway is refused rather than drawn in part. In Python the same source is ttl3d.Query:

import ttl3d

query = open("examples/wikidata-moons.rq", encoding="utf-8").read()
moons = ttl3d.Query("https://query.wikidata.org/sparql", query)
ttl3d.write(("moons", moons), "moons.html", color_by="type")
ttl3d.show(["examples/solar-system.ttl", ("moons", moons)], focus=["wd:Q2"], hops=1)   # Earth and its moons, sliced

A namespace is named by the first source that binds it, so list a file first when you focus with its prefixes. The answer parses like a file (about 13 s and 2.3 GB per million triples), so let the query select the piece: a VALUES list or a LIMIT keeps an answer small, and --focus/--schema trim further.

In the page

  • Legend rows filter inclusively: a selected group keeps its own nodes, their direct neighbours, and the endpoints of every edge it asserts, whether or not another source asserted that edge first.
  • The 3D | 2D switch rebuilds the picture in the other view. Legend filters, the search text and the open card carry over, and in pinned mode each view has its own precomputed stress layout. A browser without WebGL opens in 2D and says so.
  • Search dims everything whose label does not match.
  • Click a node for its card: types, source (the file, or the named graph with its IRI), namespace, definition, synonyms, properties, incoming and outgoing relations (clickable), and sources.
  • The label toggles rebuild the scene, so a big graph can start without sprites and switch them on later.
  • "Free-float physics" releases pinned nodes into the live force layout and pins them back where they were.
  • No fog: white fog made distant nodes vanish on zoom-out.
  • Past twelve groups only the eleven largest keep a colour; the rest share one grey "other" row that filters them together.

Scale

The stress layout is quadratic in the number of nodes and label sprites are scene objects, so the automatic modes degrade instead of freezing:

Graph size Layout Labels
up to 800 nodes / 800 links pinned stress layout nodes and edges
up to 1000 nodes pinned stress layout tooltips for the layer over its threshold
larger live force simulation tooltips; switch sprites on from the panel

For inputs far beyond these sizes, slice them first: see "Slicing a big graph". A store behind a SPARQL endpoint answers with the piece you ask for: see "From a SPARQL endpoint".

The stress layout is computed twice, once per view, so a pinned page takes about twice the layout time of 0.1.0.

Force the behaviour you want with --layout and --labels.

Limitations

  • Blank nodes are skipped, so OWL restrictions and RDF lists do not appear.
  • No reasoning: only asserted triples are drawn.
  • One page holds one graph; there is no incremental loading.
  • The stress layout is quadratic: --layout stress on graphs far beyond 1000 nodes can take minutes, and the CLI says so on stderr.

Development

pip install -e .[test]
python -m pytest -q

The tests cover the loader, the node and link rules, the layout, the generated page, the vendored bundle's pins and licence notices, and the command line. The viewer's CSS and JavaScript live in ttl3d/viewer.css, ttl3d/viewer.js (shared by both views), ttl3d/viewer-3d.js and ttl3d/viewer-2d.js (one renderer per view) and are inlined into every page; when node is installed the suite syntax-checks the JavaScript. pip install -e .[browser] && playwright install chromium enables the headless browser tests that load the demo pages, switch views and assert zero console errors (TTL3D_BROWSER=firefox or webkit picks another engine). CI runs the suite on Linux, Windows and macOS, the browser tests on Chromium, Firefox and WebKit, and checks that the demo pages built on the three systems are identical apart from the pinned layout's last digits. The vendored JavaScript in ttl3d/vendor/ bundles 3d-force-graph, force-graph, three-spritetext and one shared three.js; VENDOR.md there has the rebuild recipe and LICENSES.md the upstream notices.

Citing

If ttl3d helped your work, cite it: CITATION.cff holds the reference and GitHub's "Cite this repository" button renders it as BibTeX or APA. Every release is archived on Zenodo; the DOI 10.5281/zenodo.22716060 always resolves to the latest one.

License

MIT. The vendored JavaScript is under permissive licences (MIT, ISC and others); ttl3d/vendor/LICENSES.md lists every bundled package with its licence and copyright line.

Metadata

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