Scientific Computing and Data Management
Scientific Computing and Data Management is a research topic within Information Systems and Management. Science Explorer counts 36k research works in it since 1950. 23.1% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the management, reproducibility, and provenance of scientific workflows, particularly in the fields of bioinformatics and computational research. It explores topics such as data provenance, workflow management systems, semantic web services, cyberinfrastructure, and software development for scientific applications.
- Scientific Workflows
- Reproducibility
- Data Provenance
- Workflow Management
- Bioinformatics
- Semantic Web Services
- Cyberinfrastructure
- Computational Research
- Software Development
- Ontologies
- Research works
- 36k fractional, since 1950
- In the world top 10%
- 8.4k per year above
- Top-10% rate
- 23.1% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +10% the tick is no change
Which countries lead Scientific Computing and Data Management research?
By volume, the United States and Germany publish the most (2.3k and 812 works in 2022–2025).
By volume, 2022–2025
- 1 United States 2.3k works
- 2 Germany 812 works
- 3 China 501 works
- 4 United Kingdom 408 works
- 5 India 291 works
- 6 Italy 267 works
- 7 France 240 works
- 8 Netherlands 189 works
- 9 Canada 188 works
- 10 Spain 173 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.
Shares of the rows listed above, not of the whole node.
Which institutions lead Scientific Computing and Data Management research?
By volume in 2022–2025, Oak Ridge National Laboratory publishes the most Scientific Computing and Data Management research, followed by Argonne National Laboratory and University of Illinois Urbana-Champaign.
By volume, 2022–2025
- 1 Oak Ridge National Laboratory United States 38 works
- 2 Argonne National Laboratory United States 32 works
- 3 University of Illinois Urbana-Champaign United States 31 works
- 4 Karlsruhe Institute of Technology Germany 31 works
- 5 RWTH Aachen University Germany 27 works
- 6 Sandia National Laboratories United States 26 works
- 7 University of Chicago United States 24 works
- 8 University of Washington United States 24 works
- 9 Carnegie Mellon University United States 23 works
- 10 Optima Neuroscience (United States) United States 23 works
Who are the leading researchers in Scientific Computing and Data Management?
The most-cited researchers publishing on Scientific Computing and Data Management include Michael S. Bernstein.
- 1 Michael S. Bernstein 10k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Scientific Computing and Data Management research done?
The largest centres of Scientific Computing and Data Management research in 2022–2025 are Beijing (China), London (United Kingdom), Berlin (Germany) and Paris (France). Among places with at least 20 works in it, it is an unusually large share of all research in Alachua, Lemont and Oak Ridge.
Largest cities, 2022–2025
Where it is the local speciality
- AlachuaUS · 23.3 works274×
- LemontUS · 31.8 works23×
- Oak RidgeUS · 38.8 works16×
- MannheimDE · 23.6 works14×
Location quotient: how much more of its research is in Scientific Computing and Data Management than the world average.
Where is the best place to study Scientific Computing and Data Management?
Among universities, judged by research, University of Idaho, Carnegie Mellon University and University of Luxembourg 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.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | University of Idaho United States | 60.7 | 38.6% | 10.7× | 9 | +145.0% |
| 2 | Carnegie Mellon University United States | 59.1 | 32.8% | 8.1× | 23 | +21.0% |
| 3 | University of Luxembourg Luxembourg | 59.1 | 34.6% | 6.4× | 10 | +285.5% |
| 4 | Utrecht University Netherlands | 58.0 | 45.9% | 3.6× | 13 | +163.7% |
| 5 | Karlsruhe Institute of Technology Germany | 56.9 | 22.4% | 8.2× | 31 | -0.6% |
| 6 | University of Stuttgart Germany | 53.3 | 33.2% | 7.5× | 19 | +9.6% |
| 7 | ETH Zurich Switzerland | 53.2 | 42.4% | 3.8× | 18 | +9.4% |
| 8 | TU Wien Austria | 50.5 | 27.6% | 7.7× | 17 | -25.2% |
| 9 | University of Illinois Urbana-Champaign United States | 50.3 | 24.0% | 5.1× | 31 | +37.2% |
| 10 | Delft University of Technology Netherlands | 49.1 | 30.8% | 3.6× | 17 | +101.0% |
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 Scientific Computing and Data Management research growing?
Output in 2018–2022 was 10% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Scientific Computing and Data Management.
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.