// sulo-sections.jsx — Nav, Hero, Problem, BuildingBlocks, UseCases, Community, Publications, Download, Team, Tutorials const SULO_CLASSES = [ { id: 'Object', color: '#3B82F6', bg: 'rgba(59,130,246,0.12)', definition: 'Any physical or non-physical thing that exists independently.', examples: ['Patient', 'Drug', 'Pizza', 'Hospital', 'Gene'], note: 'The foundational "thing" in SULO.' }, { id: 'Process', color: '#F59E0B', bg: 'rgba(245,158,11,0.12)', definition: 'Something that unfolds over time, involving participants.', examples: ['Diagnosis', 'Drug administration', 'Baking', 'Surgery'], note: 'Connects objects through participation.' }, { id: 'Feature', color: '#10B981', bg: 'rgba(16,185,129,0.12)', definition: 'An intrinsic, contextual, or attributed characteristic.', examples: ['Blood pressure', 'Severity', 'Color', 'Temperature'], note: 'Describes properties of Objects or Processes.' }, { id: 'Role', color: '#34D399', bg: 'rgba(52,211,153,0.1)', definition: 'A contextual function an object plays in a setting. Subclass of Feature.', examples: ['Patient role', 'Prescriber role', 'Ingredient role'], note: 'Same object, different roles in different processes.' }, { id: 'Quantity', color: '#6EE7B7', bg: 'rgba(110,231,183,0.1)', definition: 'A measurable feature expressed as a value + unit. Subclass of Feature.', examples: ['500 mg dose', '37 °C temperature', '30 cm diameter'], note: 'Links measurements to their bearers.' }, { id: 'Collection', color: '#8B5CF6', bg: 'rgba(139,92,246,0.12)', definition: 'A group of things, without implying part-whole relations.', examples: ['Patient cohort', 'Dataset', 'Ingredient list'], note: 'Members can be of different types.' }, { id: 'InformationObject', color: '#06B6D4', bg: 'rgba(6,182,212,0.12)', definition: 'A representational entity — data, documents, codes, or identifiers.', examples: ['FHIR record', 'ICD-10 code', 'Lab report', 'Clinical note'], note: 'Information objects are about other entities.' }, { id: 'TimeInstant', color: '#94A3B8', bg: 'rgba(148,163,184,0.1)', definition: 'A point in time anchoring processes temporally.', examples: ['Date of birth', 'Diagnosis date', 'Timestamp'], note: 'Includes StartTime and EndTime as subclasses.' }, ]; const RELATIONS = [ { id: 'hasPart', label: 'hasPart / isPartOf', color: '#3B82F6', domain: 'Object or Process', range: 'Object or Process', definition: 'A mereological relation between wholes and their parts.' }, { id: 'hasParticipant', label: 'hasParticipant / isParticipantIn', color: '#F59E0B', domain: 'Process', range: 'Object', definition: 'Describes the participation of a (non-process) thing in a process.' }, { id: 'hasFeature', label: 'hasFeature / isFeatureOf', color: '#10B981', domain: 'Object or Process', range: 'Feature', definition: 'Relates a thing to its internal, contextual, or externally attributed characteristic.' }, { id: 'hasMember', label: 'hasMember / isItemIn', color: '#8B5CF6', domain: 'Collection', range: 'owl:Thing', definition: 'Relates a collection to an item contained therein.' }, { id: 'atTime', label: 'atTime', color: '#94A3B8', domain: 'Process', range: 'TimeInstant', definition: 'Anchors a process to a point in time.' }, ]; const USE_CASES = [ { id: 'pizza', label: 'Pizza Tutorial', emoji: '🍕', audience: 'Beginners', tagline: 'Start with something everyone knows', description: 'A Margherita pizza is an Object with parts (sauce, cheese, dough). Baking is a Process with the pizza as participant. Its 30 cm diameter is a Quantity Feature. This accessible example mirrors exactly how clinical data is modeled.', code: `:Margherita a sulo:Object ; sulo:hasPart :TomatoSauce, :Mozzarella, :Dough ; sulo:hasFeature :Diameter30cm . :Baking_Margherita a sulo:Process ; sulo:hasParticipant :Chef, :Margherita ; sulo:atTime :BakingStart . :Diameter30cm a sulo:Quantity ; qudt:unit unit:CentiMeter ; qudt:value 30 .`, color: '#F59E0B' }, { id: 'clinical', label: 'Clinical Integration', emoji: '🏥', audience: 'Data Engineers', tagline: 'FHIR · OMOP · SPHN — one shared pattern', description: 'Three standards, three ways to say "patient received drug X". SULO provides the semantic bridge. Map once, query anywhere — across institutions and borders without custom adapters.', code: `# FHIR: MedicationAdministration.subject → Patient/123 # OMOP: drug_exposure(person_id=123, drug_concept_id=...) # SPHN: :Patient123 sphn:hasAdministeredDrug :Drug456 # Unified SULO pattern with PRO design: :DrugAdmin_789 a sulo:Process ; sulo:hasParticipant :InputRole ; # direct link to role sulo:hasParticipant :OutputRole . # direct link to role # PRO pattern — role bearers :InputRole a sulo:Role . :Patient123 a sulo:Object ; sulo:hasFeature :InputRole . :OutputRole a sulo:Role . :MedicationOrder a sulo:InformationObject ; sulo:hasFeature :OutputRole ; sulo:refersTo :AmoxicillinAdministration . :AmoxicillinAdministration a sulo:Feature ; owl:sameAs rxnorm:723 . # inferred via role chain: # hasParticipant ∘ isFeatureOf⁻¹ → hasParticipant # ∴ DrugAdmin_789 hasParticipant Patient123 ✓`, color: '#3B82F6' }, { id: 'query', label: 'Semantic Query', emoji: '🔍', audience: 'Researchers', tagline: 'Write once, query everywhere', description: 'Because SULO enforces consistent modeling, a single SPARQL query works across any SULO-aligned dataset — no custom mappings, no guesswork about what "hasDiagnosis" means in each system.', code: `# Find patients who received aspirin > 200mg SELECT ?patient ?dose WHERE { ?admin a sulo:Process ; sulo:hasParticipant ?patient ; sulo:hasParticipant ?drug ; sulo:hasFeature ?doseNode . ?doseNode a sulo:Quantity ; qudt:value ?dose . ?drug owl:sameAs rxnorm:1191 . # aspirin ?patient a :Patient . FILTER(?dose > 200) }`, color: '#10B981' }, { id: 'ai', label: 'Neurosymbolic AI', emoji: '🤖', audience: 'AI Researchers', tagline: 'Grounding neural models in formal semantics', description: 'SULO-structured knowledge graphs give neural models a consistent symbolic backbone. Formal axioms act as hard constraints — preventing hallucinated relations, enabling verified inference, and improving cross-institutional generalization.', code: `# SULO enables hybrid reasoning: # 1. Neural: embed SULO graph → entity representations # Entities from different sources share the same types # → improved zero-shot transfer # 2. Symbolic: SULO axioms as hard constraints # IF x hasParticipant y THEN y is an Object # IF x hasPart y THEN x and y are same top-level type # 3. Verified: check outputs against ontology # Automated validation via OWL reasoners (HermiT, Pellet) # Inconsistencies flagged before downstream use`, color: '#8B5CF6' }, ]; const TEAM = window.TEAM_DATA; // ---- ANIMATED HERO CANVAS ---- const HeroCanvas = () => { const canvasRef = React.useRef(null); React.useEffect(() => { const canvas = canvasRef.current; if (!canvas) return; const ctx = canvas.getContext('2d'); let animId; const resize = () => { canvas.width = canvas.offsetWidth; canvas.height = canvas.offsetHeight; }; resize(); window.addEventListener('resize', resize); const NODE_COLORS = ['#3B82F6','#F59E0B','#10B981','#8B5CF6','#06B6D4','#34D399','#94A3B8']; const NODE_LABELS = ['Object','Process','Feature','Role','Collection','Quantity','InformationObject']; const nodes = Array.from({length: 22}, (_, i) => ({ x: Math.random() * canvas.width, y: Math.random() * canvas.height, vx: (Math.random() - 0.5) * 0.4, vy: (Math.random() - 0.5) * 0.4, r: 4 + Math.random() * 5, color: NODE_COLORS[i % NODE_COLORS.length], label: i < NODE_LABELS.length ? NODE_LABELS[i] : null, opacity: 0.4 + Math.random() * 0.5, })); const draw = () => { ctx.clearRect(0, 0, canvas.width, canvas.height); // Draw edges for (let i = 0; i < nodes.length; i++) { for (let j = i + 1; j < nodes.length; j++) { const dx = nodes[j].x - nodes[i].x; const dy = nodes[j].y - nodes[i].y; const dist = Math.sqrt(dx*dx + dy*dy); if (dist < 180) { const alpha = (1 - dist/180) * 0.12; ctx.beginPath(); ctx.moveTo(nodes[i].x, nodes[i].y); ctx.lineTo(nodes[j].x, nodes[j].y); ctx.strokeStyle = `rgba(0, 201, 167, ${alpha})`; ctx.lineWidth = 1; ctx.stroke(); } } } // Draw nodes nodes.forEach(n => { ctx.beginPath(); ctx.arc(n.x, n.y, n.r, 0, Math.PI * 2); ctx.fillStyle = n.color + Math.round(n.opacity * 255).toString(16).padStart(2,'0'); ctx.fill(); // glow const g = ctx.createRadialGradient(n.x, n.y, 0, n.x, n.y, n.r * 3); g.addColorStop(0, n.color + '30'); g.addColorStop(1, 'transparent'); ctx.beginPath(); ctx.arc(n.x, n.y, n.r * 3, 0, Math.PI * 2); ctx.fillStyle = g; ctx.fill(); }); // Update nodes.forEach(n => { n.x += n.vx; n.y += n.vy; if (n.x < 0 || n.x > canvas.width) n.vx *= -1; if (n.y < 0 || n.y > canvas.height) n.vy *= -1; }); animId = requestAnimationFrame(draw); }; draw(); return () => { cancelAnimationFrame(animId); window.removeEventListener('resize', resize); }; }, []); return ; }; // ---- NAV ---- const SULONav = () => { const [scrolled, setScrolled] = React.useState(false); React.useEffect(() => { const h = () => setScrolled(window.scrollY > 50); window.addEventListener('scroll', h); return () => window.removeEventListener('scroll', h); }, []); const links = [ { href: '#what', label: 'What is SULO' }, { href: '#explore', label: 'Explorer' }, { href: '#usecases', label: 'Use Cases' }, { href: '#demo', label: 'AI Demo' }, { href: '#community', label: 'Community' }, ]; return ( ); }; // ---- HERO ---- const Hero = () => (
CC0 · OWL 2 · JOWO/FOIS 2025 · Horizon Europe AIDAVA

A shared language
for machine-readable data.

SULO is a minimal upper-level ontology — a small, formal set of building blocks that lets data from any source mean the same thing to any machine. Simple enough to adopt, rigorous enough to reason over.

{ e.currentTarget.style.transform = 'translateY(-1px)'; e.currentTarget.style.boxShadow = '0 8px 32px rgba(0,201,167,0.4)'; }} onMouseLeave={e => { e.currentTarget.style.transform = 'none'; e.currentTarget.style.boxShadow = '0 4px 24px rgba(0,201,167,0.3)'; }} >Explore the Ontology → e.currentTarget.style.background = 'rgba(0,0,0,0.12)'} onMouseLeave={e => e.currentTarget.style.background = 'rgba(0,0,0,0.08)'} >Read the Paper e.currentTarget.style.color = '#1A2236'} onMouseLeave={e => e.currentTarget.style.color = '#6B7FA3'} > GitHub
{[['8', 'Core classes'],['5', 'Object properties'],['CC0', 'License'],['OWL 2', 'Standard']].map(([v,l]) => (
{v}
{l}
))}
); // ---- PROBLEM ---- const Problem = () => { const sectionStyles = { maxWidth: 1160, margin: '0 auto', padding: '0 clamp(1rem,5vw,3rem)' }; const fragCards = [ { label: 'Database column', code: 'patient_id | diagnosis_code\n123 | E11', color: '#F59E0B' }, { label: 'JSON API', code: '{"patientId": 123,\n "hasDiagnosis": "E11"}', color: '#3B82F6' }, { label: 'Domain ontology', code: ':Patient123\n ex:diagnosedWith\n ex:T2Diabetes .', color: '#8B5CF6' }, ]; return (
The Problem

Everyone models the world differently.

Three systems express the same fact — a patient's diabetes diagnosis — in three incompatible ways. Machines can't reliably tell they mean the same thing.

{fragCards.map(c => (
{c.label.toUpperCase()}
{c.code}
))}
{[ { icon: '⚡', title: 'Interoperability is manual', body: 'Data integration becomes a patchwork of one-off mappings. Expensive, slow, error-prone.' }, { icon: '🧩', title: 'Ontologies are too weak or too complex', body: 'Simple schemas lack semantics. Heavy upper ontologies have low adoption due to complexity.' }, { icon: '🤖', title: 'AI inherits the confusion', body: 'Models trained on inconsistent data learn inconsistent patterns — poor generalization, limited trust.' }, ].map(item => (
{item.icon}
{item.title}
{item.body}
))}
THE SULO APPROACH

Same diagnosis, one shared pattern.

SULO provides a minimal, formal "grammar of meaning" — simple enough to adopt correctly, rigorous enough for machines to reason over. Instead of inventing new relations, everyone reuses the same small vocabulary. 

:Diagnosis_event a sulo:Process ;{'\n'}{'  '}sulo:hasParticipant :InputRole ;{'   '}# direct link to role{'\n'}{'  '}sulo:hasParticipant :OutputRole .{'  '}# direct link to role{'\n'}{'\n'}# PRO pattern — role bearers{'\n'}:InputRole a sulo:Role .{'\n'}:Patient123 a sulo:Object ;{'\n'}{'  '}sulo:hasFeature :InputRole .{'\n'}{'\n'}:OutputRole a sulo:Role .{'\n'}:DiagnosisStatement a sulo:InformationObject ;{'\n'}{'  '}sulo:hasFeature :OutputRole ;{'\n'}{'  '}sulo:refersTo :DiabetesType2Condition .{'\n'}{'\n'}# inferred via role chain:{'\n'}# hasParticipant ∘ isFeatureOf⁻¹ → hasParticipant{'\n'}# ∴ Diagnosis_event hasParticipant Patient123 ✓
); }; // ---- CLASS HIERARCHY TREE DATA ---- const TREE_LIST = [ { id: 'owl:Thing', color: '#64748B', indent: 0, def: 'The universal top-level OWL class. Every SULO class is a subclass of owl:Thing.', examples: ['Any entity'] }, { id: 'Process', color: '#F59E0B', indent: 1, parent: 'owl:Thing', def: 'Something that unfolds over time, with participants.', examples: ['Diagnosis', 'Drug administration', 'Baking'] }, { id: 'Object', color: '#3B82F6', indent: 1, parent: 'owl:Thing', def: 'Any physical or non-physical thing that exists independently.', examples: ['Patient', 'Drug', 'Pizza', 'Gene'] }, { id: 'SpatialObject', color: '#60A5FA', indent: 2, parent: 'Object', def: 'An object that occupies space. Subclass of Object.', examples: ['Organ', 'Building', 'Region'] }, { id: 'Feature', color: '#10B981', indent: 2, parent: 'Object', def: 'An intrinsic, contextual, or attributed characteristic of an object or process. Subclass of Object.', examples: ['Severity', 'Color', 'Blood pressure'] }, { id: 'Role', color: '#34D399', indent: 3, parent: 'Feature', def: 'A contextual function played by an object. Subclass of Feature.', examples: ['Patient role', 'Prescriber role'] }, { id: 'Quality', color: '#6EE7B7', indent: 3, parent: 'Feature', def: 'An intrinsic property of an object. Subclass of Feature.', examples: ['Color', 'Mass', 'Charge'] }, { id: 'Capability', color: '#A7F3D0', indent: 3, parent: 'Feature', def: 'A disposition or power of an object. Subclass of Feature.', examples: ['Solubility', 'Drug resistance'] }, { id: 'InformationObject', color: '#06B6D4', indent: 3, parent: 'Feature', def: 'A representational entity — data, codes, documents. Subclass of Feature.', examples: ['ICD-10 code', 'FHIR record', 'Lab report'] }, { id: 'Collection', color: '#8B5CF6', indent: 4, parent: 'InformationObject', def: 'A group of things without implying part-whole relations. Subclass of InformationObject.', examples: ['Cohort', 'Dataset', 'Ingredient list'] }, { id: 'Quantity', color: '#C4B5FD', indent: 4, parent: 'InformationObject', def: 'A measurable amount expressed as a value and unit. Subclass of InformationObject.', examples: ['500 mg', '37 °C', '30 cm'] }, { id: 'Unit', color: '#DDD6FE', indent: 5, parent: 'Quantity', def: 'A unit of measurement. Subclass of Quantity.', examples: ['mg', 'kg', 'mL', 'mmHg'] }, { id: 'Time', color: '#94A3B8', indent: 5, parent: 'Quantity', def: 'A temporal entity anchoring processes. Subclass of Quantity.', examples: ['Date of birth', 'Diagnosis date', 'Duration'] }, { id: 'Duration', color: '#94A3B8', indent: 6, parent: 'Time', def: 'A span of time between two instants. Subclass of Time.', examples: ['Length of hospital stay', 'Treatment duration'] }, { id: 'TimeInterval', color: '#CBD5E1', indent: 6, parent: 'Time', def: 'A time interval with hasPart self-loop. Subclass of Time.', examples: ['Hospital stay', 'Treatment period'] }, { id: 'TimeInstant', color: '#E2E8F0', indent: 6, parent: 'Time', def: 'A point in time. Subclass of Time.', examples: ['Date of birth', 'Diagnosis date'] }, { id: 'StartTime', color: '#F8FAFC', indent: 7, parent: 'TimeInstant', def: 'The start of a time interval or process.', examples: ['Admission date', 'Treatment start'] }, { id: 'EndTime', color: '#F8FAFC', indent: 7, parent: 'TimeInstant', def: 'The end of a time interval or process.', examples: ['Discharge date', 'Treatment end'] }, ]; const TREE_CROSS_EDGES = [ { from: 'Process', to: 'Object', label: 'hasParticipant', color: '#3B82F6' }, { from: 'Object', to: 'Feature', label: 'hasFeature', color: '#10B981' }, { from: 'Process', to: 'Feature', label: 'hasFeature', color: '#10B981' }, { from: 'InformationObject', to: 'owl:Thing',label: 'refersTo', color: '#06B6D4' }, { from: 'Collection', to: 'owl:Thing', label: 'hasItem', color: '#8B5CF6' }, { from: 'Process', to: 'Time', label: 'atTime', color: '#94A3B8' }, ]; // ---- BUILDING BLOCKS ---- const BuildingBlocks = () => { const [sel, setSel] = React.useState(null); const selNode = sel ? TREE_LIST.find(n => n.id === sel) : null; const relatedEdges = sel ? TREE_CROSS_EDGES.filter(e => e.from === sel || e.to === sel) : []; return (
Class Hierarchy

The SULO class tree.

Indented rows show subClassOf. Click any class to see its definition, examples, and object property connections.

{/* Tree list + panel: panel LEFT, tree RIGHT */}
{/* Detail panel — sticky left */}
{selNode ? ( <>
{selNode.id}
{selNode.parent && (
subClassOf {selNode.parent}
)}

{selNode.def}

EXAMPLES
{selNode.examples.map(ex => ( {ex} ))}
{relatedEdges.length > 0 && ( <>
PROPERTIES
{relatedEdges.map((e, i) => (
{e.from} —{e.label}→ {e.to}
))} )} ) : (
◉
Click any class
to explore
)}
{/* Indented tree */}
{TREE_LIST.map((node, i) => { const isSel = sel === node.id; const isDim = sel && !isSel; const prevIndent = i > 0 ? (TREE_LIST[i-1].indent || 0) : 0; const nextIndent = i < TREE_LIST.length - 1 ? (TREE_LIST[i+1].indent || 0) : 0; return (
0 ? 6 : 0, cursor: 'pointer', opacity: isDim ? 0.4 : 1, transition: 'opacity 0.2s' }} onClick={() => setSel(isSel ? null : node.id)}> {node.indent > 0 && (
)}
{ if (!isSel) { e.currentTarget.style.background = node.color + '12'; e.currentTarget.style.borderColor = node.color + '40'; }}} onMouseLeave={e => { if (!isSel) { e.currentTarget.style.background = 'rgba(0,0,0,0.04)'; e.currentTarget.style.borderColor = node.color + '22'; }}}>
{node.id}
{node.parent && ( ⊂ {node.parent} )}
); })}
{/* Object Properties */}
Object Properties
{RELATIONS.map(rel => (
{rel.label}
{rel.definition}
{rel.domain} → {rel.range}
))}
); }; // ---- USE CASES ---- const UseCases = () => { const [tab, setTab] = React.useState('pizza'); const uc = USE_CASES.find(u => u.id === tab); const sectionStyles = { maxWidth: 1160, margin: '0 auto', padding: '0 clamp(1rem,5vw,3rem)' }; return (
Use Cases

SULO in practice.

{USE_CASES.map(u => ( ))}
{uc && (
{uc.audience.toUpperCase()}

{uc.tagline}

{uc.description}

{uc.id === 'pizza' && ( Try the notebook tutorial → )}
turtle SULO pattern 
{uc.code}
)}
); }; // ---- TUTORIALS ---- const Tutorials = () => { const sectionStyles = { maxWidth: 1160, margin: '0 auto', padding: '0 clamp(1rem,5vw,3rem)' }; const tutorials = [ { title: 'SULO Introduction', desc: 'What SULO is, its design principles, and the minimal vocabulary. Start here.', tag: 'Beginner', nb: '01_sulo_intro.ipynb' }, { title: 'Pizza Knowledge Graph', desc: 'Build a Margherita pizza KG from scratch using SULO classes and relations.', tag: 'Beginner', nb: '02_pizza_kg.ipynb' }, { title: 'Clinical Data Modeling', desc: 'Map FHIR and OMOP patient data to SULO patterns. Integrate two datasets.', tag: 'Intermediate', nb: '03_clinical_kg.ipynb' }, { title: 'SPARQL Queries over SULO', desc: 'Write semantic queries that work across SULO-aligned datasets.', tag: 'Intermediate', nb: '04_sparql_queries.ipynb' }, ]; return (
Tutorials

Learn by doing.

Interactive Jupyter notebooks — run in your browser, no setup needed.

All Tutorials on GitHub
{tutorials.map((t, i) => ( { e.currentTarget.style.borderColor = 'rgba(0,201,167,0.3)'; e.currentTarget.style.transform = 'translateY(-2px)'; }} onMouseLeave={e => { e.currentTarget.style.borderColor = 'rgba(0,0,0,0.1)'; e.currentTarget.style.transform = 'none'; }} >
0{i+1} {t.tag}
{t.title}
{t.desc}
 ))}
); }; // ---- COUNTDOWN ---- const Countdown = () => { const getNextFirstWed = () => { const now = new Date(); let d = new Date(now.getFullYear(), now.getMonth(), 1); while (d.getDay() !== 3) d.setDate(d.getDate() + 1); d.setHours(15, 0, 0, 0); // 15:00 local if (d <= now) { d = new Date(now.getFullYear(), now.getMonth() + 1, 1); while (d.getDay() !== 3) d.setDate(d.getDate() + 1); d.setHours(15, 0, 0, 0); } return d; }; const [timeLeft, setTimeLeft] = React.useState({ d: '--', h: '--', m: '--', s: '--' }); const [nextDate, setNextDate] = React.useState(''); React.useEffect(() => { const target = getNextFirstWed(); setNextDate(target.toLocaleDateString('en-US', { weekday: 'long', year: 'numeric', month: 'long', day: 'numeric' })); const tick = () => { const diff = target - new Date(); if (diff <= 0) { setTimeLeft({ d: 0, h: 0, m: 0, s: 0 }); return; } setTimeLeft({ d: Math.floor(diff / 86400000), h: Math.floor((diff % 86400000) / 3600000), m: Math.floor((diff % 3600000) / 60000), s: Math.floor((diff % 60000) / 1000), }); }; tick(); const id = setInterval(tick, 1000); return () => clearInterval(id); }, []); return (
NEXT MONTHLY MEETING
{nextDate}
{[['d','Days'],['h','Hrs'],['m','Min'],['s','Sec']].map(([k, l]) => (
{String(timeLeft[k]).padStart(2, '0')}
{l}
))}
); }; // ---- COMMUNITY ---- const Community = () => { const sectionStyles = { maxWidth: 1160, margin: '0 auto', padding: '0 clamp(1rem,5vw,3rem)' }; return (
Community

Get involved.

📅

Monthly Working Sessions

Every first Wednesday of the month, the SULO community meets to work through use cases, discuss modeling patterns, and shape the ontology together. All levels welcome.

Join on Microsoft Teams →
💬

Slack Community

Ask questions, share modeling patterns, and connect with others building with SULO. Active discussion across healthcare, research, and AI communities.

sulotalk.slack.com →
🔧

Contribute on GitHub

Open issues, propose new modeling patterns, submit use cases, or improve the tutorials. SULO is built by the community, for the community.

Open an Issue
); }; // ---- PUBLICATIONS ---- const Publications = () => { const sectionStyles = { maxWidth: 1160, margin: '0 auto', padding: '0 clamp(1rem,5vw,3rem)' }; return (
Publication

Cite SULO.

Dumontier, M., Çelebi, R., Gilani, K., de Zegher, I., Serafimova, K., Martínez Costa, C., & Schulz, S.
SULO - a simplified upper-level ontology.
Proceedings of the Joint Ontology Workshops (JOWO) — Episode XI: The Sicilian Summer under the Etna, co-located with the 15th International Conference on Formal Ontology in Information Systems (FOIS 2025), September 8–9, 2025, Catania, Italy.
Read the Paper Auto-generated Docs
); }; // ---- DOWNLOAD ---- const Download = () => { const sectionStyles = { maxWidth: 1160, margin: '0 auto', padding: '0 clamp(1rem,5vw,3rem)' }; const formats = [ { fmt: 'Turtle', ext: '.ttl', mime: 'text/turtle', color: '#10B981', desc: 'Most readable. Recommended.' }, { fmt: 'JSON-LD', ext: '.jsonld', mime: 'application/ld+json', color: '#F59E0B', desc: 'For web & REST APIs.' }, { fmt: 'RDF/XML', ext: '.rdf', mime: 'application/rdf+xml', color: '#3B82F6', desc: 'Legacy tooling.' }, { fmt: 'N-Triples', ext: '.nt', mime: 'application/n-triples', color: '#8B5CF6', desc: 'Streaming & large datasets.' }, ]; return (
Get SULO

Download the ontology.

{formats.map(f => ( { e.currentTarget.style.borderColor = f.color + '60'; e.currentTarget.style.transform = 'translateY(-2px)'; }} onMouseLeave={e => { e.currentTarget.style.borderColor = f.color + '25'; e.currentTarget.style.transform = 'none'; }} >
{f.ext}
{f.fmt}
{f.desc}
 ))}
CONTENT NEGOTIATION
            {`curl -L -H "Accept: text/turtle" https://w3id.org/sulo\ncurl -L -H "Accept: application/ld+json" https://w3id.org/sulo`}
); }; // ---- TEAM ---- const Team = () => { const sectionStyles = { maxWidth: 1160, margin: '0 auto', padding: '0 clamp(1rem,5vw,3rem)' }; return (
Team

The people behind SULO.

Supported by the AIDAVA project (GA 101057062), European Union Horizon Europe.

{TEAM.map((m, i) => (
e.currentTarget.style.borderColor = 'rgba(0,0,0,0.18)'} onMouseLeave={e => e.currentTarget.style.borderColor = 'rgba(0,0,0,0.08)'} >
{m.name.split(' ').map(n => n[0]).slice(0,2).join('')}
{m.name}
{m.affil}
{m.role}
{m.orcid && ( e.currentTarget.style.background = 'rgba(0,201,167,0.16)'} onMouseLeave={e => e.currentTarget.style.background = 'rgba(0,201,167,0.08)'} > {m.orcid} )}
))}
); }; // ---- FOOTER ---- const Footer = () => ( ); Object.assign(window, { SULONav, Hero, Problem, BuildingBlocks, UseCases, Tutorials, Community, Publications, Download, Team, Footer, SULO_CLASSES, Countdown });