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Topic · Artificial Intelligence

Semantic Web and Ontologies

Semantic Web and Ontologies is a research topic within Artificial Intelligence. Science Explorer counts 72k research works in it since 1950. 20.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the Semantic Web, ontology development, and related technologies such as Linked Data, RDF, OWL, schema matching, SPARQL, and knowledge representation. It covers topics like data integration, description logics, and the use of ontologies for information retrieval and knowledge management.

  • Semantic Web
  • Ontology
  • Linked Data
  • RDF
  • OWL
  • Schema Matching
  • SPARQL
  • Knowledge Representation
  • Data Integration
  • Description Logics
Research works
72k
fractional, since 1950
In the world top 10%
15k
per year above
Top-10% rate
20.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-30%
the tick is no change

Which countries lead Semantic Web and Ontologies research?

By volume, the United States and China publish the most (1.1k and 1k works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 1.1k works
  2. 2 China 1k works
  3. 3 Germany 714 works
  4. 4 France 435 works
  5. 5 Italy 380 works
  6. 6 India 344 works
  7. 7 United Kingdom 297 works
  8. 8 Brazil 194 works
  9. 9 Spain 169 works
  10. 10 Russia 151 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 22.6%China: 21.6%Germany: 14.9%France: 9.1%6 others listed: 32.0%23%largest
United States1,083 · 22.6%China1,035 · 21.6%Germany714 · 14.9%France435 · 9.1%6 others listed1,535 · 32.0%

Shares of the rows listed above, not of the whole node.

Which institutions lead Semantic Web and Ontologies research?

By volume in 2022–2025, Centre National de la Recherche Scientifique publishes the most Semantic Web and Ontologies research, followed by RWTH Aachen University and TU Wien.

By volume, 2022–2025

  1. 1 Centre National de la Recherche ScientifiqueFrance 37 works
  2. 2 RWTH Aachen UniversityGermany 37 works
  3. 3 TU WienAustria 31 works
  4. 4 National University of Defense TechnologyChina 27 works
  5. 5 University of BolognaItaly 26 works
  6. 6 Tsinghua UniversityChina 26 works
  7. 7 Technische Universität DresdenGermany 23 works
  8. 8 Technische Informationsbibliothek (TIB)Germany 23 works
  9. 9 Peking UniversityChina 22 works
  10. 10 Sapienza University of RomeItaly 22 works

Who are the leading researchers in Semantic Web and Ontologies?

The most-cited researchers publishing on Semantic Web and Ontologies include Wei Liu, Wei Liu and Philip S. Yu.

  1. 1 Wei Liu China 9.7k citations
  2. 2 Wei Liu Australia 9.7k citations
  3. 3 Philip S. Yu United States 6.6k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Semantic Web and Ontologies research done?

The largest centres of Semantic Web and Ontologies research in 2022–2025 are Beijing (China), Paris (France), Shanghai (China) and London (United Kingdom). Among places with at least 20 works in it, it is an unusually large share of all research in Mannheim.

Largest cities, 2022–2025

  1. 1 Beijing China 297 works
  2. 2 Paris France 107 works
  3. 3 Shanghai China 81 works
  4. 4 London United Kingdom 73 works
  5. 5 Moscow Russia 65 works
  6. 6 Tokyo Japan 64 works
  7. 7 Wuhan China 62 works
  8. 8 Vienna Austria 60 works
  9. 9 Nanjing China 59 works
  10. 10 Rome Italy 58 works

Where it is the local speciality

  1. MannheimDE · 20.1 works12×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Semantic Web and Ontologies than the world average.

See Semantic Web and Ontologies on the map

Where is the best place to study Semantic Web and Ontologies?

Among universities, judged by research, Free University of Bozen-Bolzano, RWTH Aachen University and Eindhoven University of Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 26.13%fractional works in this node (log) →share in the world top 10% →Free University of Bozen-Bolzano: 19, 32.3%RWTH Aachen University: 37, 28.9%Eindhoven University of Technology: 16, 37.3%University of Mannheim: 15, 23.6%TU Wien: 31, 10.3%Hong Kong University of Science and Technology: 14, 31.0%University of Twente: 13, 28.1%FernUniversität in Hagen: 17, 10.2%University of Bologna: 26, 22.1%Nanyang Technological University: 12, 37.5%Eindhoven University…Free University of B…RWTH Aachen UniversityUniversity of Mannheim
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Free University of Bozen-BolzanoItaly 68.432.3%27.6×19 -8.9%
2 RWTH Aachen UniversityGermany 68.028.9%7.6×37 +30.6%
3 Eindhoven University of TechnologyNetherlands 60.237.3%6.7×16 -34.9%
4 University of MannheimGermany 56.523.6%23.3×15 -14.2%
5 TU WienAustria 56.010.3%14.2×31 -31.3%
6 Hong Kong University of Science and TechnologyHong Kong 53.431.0%5.4×14 -55.8%
7 University of TwenteNetherlands 49.828.1%6.4×13 -34.1%
8 FernUniversität in HagenGermany 47.710.2%32.0×17 +26.2%
9 University of BolognaItaly 47.622.1%4.8×26 -35.9%
10 Nanyang Technological UniversitySingapore 46.537.5%2.1×12 -46.2%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Semantic Web and Ontologies research growing?

Output in 2018–2022 was 30% lower than in 2013–2017, peaking in 2011.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.