2026 Paolo Missier: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	37	10662	10364	671	663	246	6552

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

1046
Citations
Why linked data is not enough for scientists

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

513
Citations
Why Linked Data is Not Enough for Scientists

Sean Bechhofer;John Ainsworth;Jiten Bhagat;Iain Buchan

471
Citations
Taverna, reloaded

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

250
Citations
The W3C PROV family of specifications for modelling provenance metadata

Paolo Missier;Khalid Belhajjame;James Cheney

248
Citations
Workflow-centric research objects: First class citizens in scholarly discourse.

Khalid Belhajjame;Oscar Corcho;Daniel Garijo;Jun Zhao

167
Citations
Workflow-Centric Research Objects: A First Class Citizen in the Scholarly Discourse

K Belhajjame;O Corcho;D Garijo;J Zhao

166
Citations
Data Quality at a Glance

P Missier;M Scannapieco;C Batini

154
Citations
An overview of S-OGSA: A Reference Semantic Grid Architecture

Oscar Corcho;Pinar Alper;Ioannis Kotsiopoulos;Paolo Missier

151
Citations
Taverna Workflows: Syntax and Semantics

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

135
Citations
Clustering web pages based on their structure

Valter Crescenzi;Paolo Merialdo;Paolo Missier

124
Citations
YesWorkflow: A User-Oriented, Language-Independent Tool for Recovering Workflow Information from Scripts

Timothy McPhillips;Tianhong Song;Tyler Kolisnik;Steve Aulenbach

115
Citations
PROV Model Primer

Yolanda Gil;Simon Miles;Khalid Belhajjame;Helena Deus

111
Citations
Data Lineage Model for Taverna Workflows with Lightweight Annotation Requirements

Paolo Missier;Khalid Belhajjame;Jun Zhao;Marco Roos

93
Citations
D-PROV: extending the PROV provenance model with workflow structure

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

92
Citations
Janus: From workflows to semantic provenance and linked open data

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

79
Citations
Fine-grained and efficient lineage querying of collection-based workflow provenance

Paolo Missier;Norman W. Paton;Khalid Belhajjame

79
Citations
The Open Provenance Model (v1.01)

Luc Moreau;Beth Plale;Simon Miles;Carole Goble

74
Citations
Quality views: capturing and exploiting the user perspective on data quality

Paolo Missier;Suzanne Embury;Mark Greenwood;Alun Preece

74
Citations
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

73
Citations
A formal semantics for the Taverna 2 workflow model

Jacek Sroka;Jan Hidders;Paolo Missier;Carole Goble

68
Citations

Frequent Co-Authors

Carole Goble University of Manchester

Sean Bechhofer University of Manchester

Bertram Ludäscher University of Illinois at Urbana-Champaign

Oscar Corcho Technical University of Madrid

David De Roure University of Oxford

Alun Preece Cardiff University

Ilkay Altintas University of California, San Diego

Shawn Bowers Gonzaga University

Jun Zhao University of Oxford

Norman W. Paton University of Manchester

External Links

Personal website of Paolo Missier Google Scholar page

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