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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. 10.1% 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%
3.7k
per year above
Top-10% rate
10.1%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+22%
the tick is no change
Largest producer
United States
42% of the 10 largest, 2022-now
Scientific Computing and Data Management

Which countries lead Scientific Computing and Data Management research?

By volume, the United States and Germany publish the most (2.9k and 1.1k works in 2022-now).

By volume, 2022-now

  1. 1 United States 2.9k works
  2. 2 Germany 1.1k works
  3. 3 China 627 works
  4. 4 United Kingdom 601 works
  5. 5 India 360 works
  6. 6 Italy 332 works
  7. 7 France 306 works
  8. 8 Netherlands 275 works
  9. 9 Canada 231 works
  10. 10 Spain 221 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: 41.7%Germany: 16.3%China: 8.9%United Kingdom: 8.6%6 others listed: 24.5%42%largest
United States2,931 · 41.7%Germany1,142 · 16.3%China627 · 8.9%United Kingdom601 · 8.6%6 others listed1,724 · 24.5%

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

Which institutions lead Scientific Computing and Data Management research?

By volume in 2022-now, Helmholtz Association of German Research Centres publishes the most Scientific Computing and Data Management research, followed by Centre National de la Recherche Scientifique and Leibniz Association.

By volume, 2022-now

  1. 1 Helmholtz Association of German Research CentresGermany 183 works
  2. 2 Centre National de la Recherche ScientifiqueFrance 92 works
  3. 3 Leibniz AssociationGermany 88 works
  4. 4 Chinese Academy of SciencesChina 53 works
  5. 5 Max Planck SocietyGermany 44 works
  6. 6 University of Illinois Urbana-ChampaignUnited States 43 works
  7. 7 Oak Ridge National LaboratoryUnited States 42 works
  8. 8 Russian Academy of SciencesRussia 40 works
  9. 9 RWTH Aachen UniversityGermany 39 works
  10. 10 Film IndependentUnited States 38 works

Who are the leading researchers in Scientific Computing and Data Management?

The most-cited researchers publishing on Scientific Computing and Data Management include David Moher, Yoshua Bengio and Rob Knight.

  1. 1 David Moher Canada 898k citations
  2. 2 Yoshua Bengio Canada 476k citations
  3. 3 Rob Knight United States 468k citations
  4. 4 Peer Bork Germany 396k citations
  5. 5 Julian P. T. Higgins United Kingdom 390k citations
  6. 6 Gad A. Getz United States 364k citations
  7. 7 John P. A. Ioannidis United States 317k citations
  8. 8 Elie A. Akl Canada 313k citations
  9. 9 Karl John Friston United Kingdom 310k citations

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

What are the most cited papers in Scientific Computing and Data Management?

The most cited paper in Scientific Computing and Data Management is "UCSF Chimera—A visualization system for exploratory research and analysis" (Eric F. Pettersen, Thomas D. Goddard, Conrad C. Huang et al., 2004), with 48,801 citations. Next come "SciPy 1.0: fundamental algorithms for scientific computing in Python" (40,161) and "Clustal W and Clustal X version 2.0" (29,302).

Most cited papers
#PaperReleasedCitations
1 UCSF Chimera—A visualization system for exploratory research and analysis Eric F. Pettersen, Thomas D. Goddard, Conrad C. Huang et al. · Journal of Computational Chemistry Jul 2004 48,801
2 SciPy 1.0: fundamental algorithms for scientific computing in Python Pauli Virtanen et al. · Nature Methods Open access112 authors 3 Feb 2020 40,161
3 Clustal W and Clustal X version 2.0 Mark Larkin, Gordon Blackshields, Nigel P. Brown et al. · Bioinformatics 10 Sep 2007 29,302
4 The REDCap consortium: Building an international community of software platform partners Paul A. Harris, Robert J. Taylor, Brenda L. Minor et al. · Journal of Biomedical Informatics Open access 9 May 2019 25,189
5 Array programming with NumPy Charles R. Harris et al. · Nature Open access 16 Sep 2020 23,885
All 100 most cited papers, with filters and sorting

Where is Scientific Computing and Data Management research done?

The largest centres of Scientific Computing and Data Management research in 2022-now 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, Sharon and Lemont.

Largest cities, 2022-now

  1. 1 BeijingChina 168 works
  2. 2 LondonUnited Kingdom 154 works
  3. 3 BerlinGermany 125 works
  4. 4 ParisFrance 112 works
  5. 5 New YorkUnited States 84 works
  6. 6 Los AngelesUnited States 81 works
  7. 7 AmsterdamNetherlands 76 works
  8. 8 TokyoJapan 68 works
  9. 9 MunichGermany 63 works
  10. 10 RomeItaly 63 works

Where it is the local speciality

  1. AlachuaUS · 27.3 works231×
  2. SharonUS · 20.0 works20×
  3. LemontUS · 34.5 works20×
  4. SalzburgAT · 33.6 works16×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Scientific Computing and Data Management than the world average.

See Scientific Computing and Data Management on the map

Where is the best place to study Scientific Computing and Data Management?

Among universities, judged by research, ETH Zurich, Harvard University and Carnegie Mellon University 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%10%20%30%mean 19.48%fractional works in this field (log) →share of work in the world top 10% →ETH ZurichUniversity of TorontoCarnegie Mellon Univ…Harvard University
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1ETH ZurichSwitzerland 78.221.4%4.3×24 +51.2%
2Harvard UniversityUnited States 71.917.3%1.1×28 +10.5%
3Carnegie Mellon UniversityUnited States 71.717.7%8.8×30 +3.7%
4University of TorontoCanada 71.719.6%1.3×21 +32.2%
5Technical University of MunichGermany 71.121.7%3.0×22 +27.6%
6University of CambridgeUnited Kingdom 70.723.8%1.9×18 +17.3%
7University of ChicagoUnited States 70.313.4%4.3×30 +39.0%
8Nanyang Technological UniversitySingapore 69.125.9%2.0×13 +105.1%
9University of WashingtonUnited States 67.713.9%3.3×31 -5.3%
10Stanford UniversityUnited States 65.820.1%2.3×28 -26.7%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Scientific Computing and Data Management, country by country

Is Scientific Computing and Data Management research growing?

Output in 2022-2025 was 22% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Scientific Computing and Data Management.

still counting19801990200020102020
grewheldshrank

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

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Scientific Computing and Data Management as a percentage of every work published that year, 0.034% in 2024.

still counting0.020%0.040%0.060%Scientific Computing and Data Management0.045% in 202519801990200020102020

Fractional works of Scientific Computing and Data Management over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Scientific Computing and Data Management9.8% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

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.

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