World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
6552
World Ranking
10660
National Ranking
668

Paolo Missier publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Paolo Missier sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 246 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Paolo Missier D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Paolo Missier sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Paolo Missier is affiliated with Newcastle University in the United Kingdom. Their research spans multiple disciplines, primarily focusing on computer science and medicine. They have published extensively in the intersection of these fields, contributing to topics such as artificial intelligence, epidemiology, and information systems.

The scientist's recent publications cover a range of subjects, including metabolic diseases, clinical prediction outcomes, machine learning applications in healthcare, data ecosystems, and data provenance. Notable papers include:

  • "An unbiased ranking of murine dietary models based on their proximity to human metabolic dysfunction-associated steatotic liver disease (MASLD)" (2024) published in Nature Metabolism
  • "Performance of non-invasive tests and histology for the prediction of clinical outcomes in patients with non-alcoholic fatty liver disease: an individual participant data meta-analysis" (2023) published in The Lancet. Gastroenterology & Hepatology
  • "Machine learning in predicting respiratory failure in patients with COVID-19 pneumonia-Challenges, strengths, and opportunities in a global health emergency" (2020) published in PLoS ONE
  • "Knowledge-Driven Data Ecosystems Toward Data Transparency" (2021) published in Journal of Data and Information Quality
  • "Capturing and querying fine-grained provenance of preprocessing pipelines in data science" (2020) published in Proceedings of the VLDB Endowment

Paolo Missier frequently collaborates with several researchers, among the most notable are:

  • Nick J. Reynolds
  • Michael R. Barnes
  • Quentin M. Anstee
  • Federica Mandreoli
  • Jörn M. Schattenberg

Their work appears regularly in established academic venues, with repeated publications in:

  • arXiv (Cornell University)
  • PLoS ONE
  • Journal of Data and Information Quality
  • Proceedings of the VLDB Endowment
  • Future Generation Computer Systems

Major fields of study include:

  • Computer Science
  • Medicine

Within these broader fields, their research covers subfields such as:

  • Artificial Intelligence
  • Epidemiology
  • Information Systems
  • Information Systems and Management
  • Computer Networks and Communications

Central topics of Paolo Missier's work engage with:

  • Chronic Disease Management Strategies
  • Scientific Computing and Data Management
  • Research Data Management Practices
  • Explainable Artificial Intelligence (XAI)
  • Liver Disease Diagnosis and Treatment
  • Data Quality and Management
  • Machine Learning in Healthcare

Best Publications

  • The Open Provenance Model core specification (v1.1)

    Luc Moreau;Ben Clifford;Juliana Freire;Joe Futrelle

  • Why linked data is not enough for scientists

    Sean Bechhofer;Iain Buchan;David De Roure;Paolo Missier

  • Why Linked Data is Not Enough for Scientists

    Sean Bechhofer;John Ainsworth;Jiten Bhagat;Iain Buchan

  • Taverna, reloaded

    Paolo Missier;Stian Soiland-Reyes;Stuart Owen;Wei Tan

  • The W3C PROV family of specifications for modelling provenance metadata

    Paolo Missier;Khalid Belhajjame;James Cheney

  • Workflow-centric research objects: First class citizens in scholarly discourse.

    Khalid Belhajjame;Oscar Corcho;Daniel Garijo;Jun Zhao

  • Workflow-Centric Research Objects: A First Class Citizen in the Scholarly Discourse

    K Belhajjame;O Corcho;D Garijo;J Zhao

  • Data Quality at a Glance

    P Missier;M Scannapieco;C Batini

  • An overview of S-OGSA: A Reference Semantic Grid Architecture

    Oscar Corcho;Pinar Alper;Ioannis Kotsiopoulos;Paolo Missier

  • Taverna Workflows: Syntax and Semantics

    D. Turi;P. Missier;C. Goble;D. De Roure

  • Clustering web pages based on their structure

    Valter Crescenzi;Paolo Merialdo;Paolo Missier

  • YesWorkflow: A User-Oriented, Language-Independent Tool for Recovering Workflow Information from Scripts

    Timothy McPhillips;Tianhong Song;Tyler Kolisnik;Steve Aulenbach

  • PROV Model Primer

    Yolanda Gil;Simon Miles;Khalid Belhajjame;Helena Deus

  • Data Lineage Model for Taverna Workflows with Lightweight Annotation Requirements

    Paolo Missier;Khalid Belhajjame;Jun Zhao;Marco Roos

  • D-PROV: extending the PROV provenance model with workflow structure

    Paolo Missier;Saumen Dey;Khalid Belhajjame;Víctor Cuevas-Vicenttín

  • Janus: From workflows to semantic provenance and linked open data

    Paolo Missier;Satya Sanket Sahoo;Jun Zhao;Carole A. Goble

  • Fine-grained and efficient lineage querying of collection-based workflow provenance

    Paolo Missier;Norman W. Paton;Khalid Belhajjame

  • The Open Provenance Model (v1.01)

    Luc Moreau;Beth Plale;Simon Miles;Carole Goble

  • Quality views: capturing and exploiting the user perspective on data quality

    Paolo Missier;Suzanne Embury;Mark Greenwood;Alun Preece

  • Machine learning in predicting respiratory failure in patients with COVID-19 pneumonia-Challenges, strengths, and opportunities in a global health emergency.

    Davide Ferrari;Jovana Milic;Roberto Tonelli;Francesco Ghinelli

  • A formal semantics for the Taverna 2 workflow model

    Jacek Sroka;Jan Hidders;Paolo Missier;Carole Goble

Frequent Co-Authors

Carole Goble
Carole Goble University of Manchester
Sean Bechhofer
Sean Bechhofer University of Manchester
Bertram Ludäscher
Bertram Ludäscher University of Illinois at Urbana-Champaign
Oscar Corcho
Oscar Corcho Technical University of Madrid
David De Roure
David De Roure University of Oxford
Ilkay Altintas
Ilkay Altintas University of California, San Diego
Alun Preece
Alun Preece Cardiff University
Shawn Bowers
Shawn Bowers Gonzaga University
Alexander Romanovsky
Alexander Romanovsky Newcastle University
Carlo Batini
Carlo Batini University of Milano-Bicocca

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