World's Best Scientists 2026 revealed!
Award Badge
Computer Science
UK
2025

D-Index & Metrics

Computer Science

D-Index
69
Citations
23748
World Ranking
1943
National Ranking
113

Research.com Recognitions

  • 2025 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award
  • 2017 - Member of Academia Europaea
  • 2009 - Fellow of the Royal Society, United Kingdom
  • 2000 - ACM Fellow Leadership in: Extending databases to new data models, type systems, and languages. Complex value, functional and object-oriented database languages. Semi-structured data and heterogeneous database integration.

Overview

Peter Buneman is affiliated with the University of Edinburgh in the United Kingdom. Their research spans multiple areas within computer science, with a primary focus on data management, graph theory, and scientific computing.

Their work includes contributions to a range of subfields such as information systems, computer vision and pattern recognition, artificial intelligence, and molecular biology. This diverse reach reflects a multidisciplinary approach to data and computational problems.

Key topics in their research involve:

  • Scientific Computing and Data Management
  • Research Data Management Practices
  • Graph Theory and Algorithms
  • Biomedical Text Mining and Ontologies
  • Data Quality and Management
  • Advanced Image and Video Retrieval Techniques
  • Data Management and Algorithms

Peter Buneman has published several papers in respected venues, including:

  • "Why data citation isn't working, and what to do about it" (2020) in Database
  • "Data citation and the citation graph" (2021) in Quantitative Science Studies
  • "MITra: A Framework for Multi-Instance Graph Traversal" (2023) in Proceedings of the VLDB Endowment
  • "Can we measure the impact of a database?" (2024) in arXiv (Cornell University)
  • "Automating Vectorized Distributed Graph Computation" (2024) in Proceedings of the ACM on Management of Data

Their frequent collaborators include Dennis Dosso, Matteo Lissandrini, Gianmaria Silvello, Wenyue Zhao, and Nikos Ntarmos, each having co-authored multiple works with them. These collaborations contribute to advancements in data management and computational frameworks.

Publication venues where Peter Buneman's work appears regularly are:

  • Database
  • Quantitative Science Studies
  • Proceedings of the VLDB Endowment
  • arXiv (Cornell University)
  • Proceedings of the ACM on Management of Data

Peter Buneman's contributions have been recognized through awards and honors, including:

  • Member of Academia Europaea (2017)
  • Fellow of the Royal Society, United Kingdom (2009)
  • ACM Fellow (2000) for leadership in extending databases to new data models, type systems, and languages, and work on semi-structured data and heterogeneous database integration

This profile outlines the scope and impact of Peter Buneman's career as a researcher focused on advancing the theoretical and applied aspects of computer science, particularly within the domains of data and information systems.

Best Publications

  • Data on the Web: From Relations to Semistructured Data and XML

    Serge Abiteboul;Peter Buneman;Dan Suciu

  • Why and Where: A Characterization of Data Provenance

    Peter Buneman;Sanjeev Khanna;Wang Chiew Tan

  • Semistructured data

    Peter Buneman

  • A query language and optimization techniques for unstructured data

    Peter Buneman;Susan Davidson;Gerd Hillebrand;Dan Suciu

  • The IUPHAR/BPS Guide to PHARMACOLOGY: an expert-driven knowledgebase of drug targets and their ligands

    Adam J. Pawson;Joanna L. Sharman;Helen E. Benson;Elena Faccenda

  • The Recovery of Trees from Measures of Dissimilarity

    Peter Buneman

  • Types and persistence in database programming languages

    Malcolm P. Atkinson;O. Peter Buneman

  • Adding Structure to Unstructured Data

    Peter Buneman;Susan B. Davidson;Mary F. Fernandez;Dan Suciu

  • A characterisation of rigid circuit graphs

    Peter Buneman

  • Keys for XML

    Peter Buneman;Susan B. Davidson;Wenfei Fan;Carmem S. Hara

  • A Note on the Metric Properties of Trees

    Peter Buneman

  • THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Introduction and Other Protein Targets.

    Stephen P.H. Alexander;Eamonn Kelly;Alistair Mathie;John A. Peters

  • Provenance management in curated databases

    Peter Buneman;Adriane Chapman;James Cheney

  • Data Provenance: Some Basic Issues

    Peter Buneman;Sanjeev Khanna;Wang Chiew Tan

  • UnQL: a query language and algebra for semistructured data based on structural recursion

    Peter Buneman;Mary Fernandez;Dan Suciu

  • Principles of programming with complex objects and collection types

    Peter Buneman;Shamim Naqvi;Val Tannen;Limsoon Wong

  • Archiving scientific data

    Peter Buneman;Sanjeev Khanna;Keishi Tajima;Wang-Chiew Tan

  • Keys for XML

    Peter Buneman;Susan Davidson;Wenfei Fan;Carmem Hara

  • Comprehension syntax

    Peter Buneman;Leonid Libkin;Dan Suciu;Val Tannen

  • Reasoning about keys for XML

    Peter Buneman;Susan Davidson;Wenfei Fan;Carmem Hara

  • Proceedings of the 1993 ACM SIGMOD international conference on Management of data

    Peter Buneman;Sushil Jajodia

  • THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Introduction and Other Protein Targets.

    Stephen P H Alexander;Eamonn Kelly;Alistair Mathie;John A Peters

Frequent Co-Authors

Wang-Chiew Tan
Wang-Chiew Tan Facebook (United States)
Wenfei Fan
Wenfei Fan University of Edinburgh
Susan B. Davidson
Susan B. Davidson University of Pennsylvania
James Cheney
James Cheney University of Edinburgh
Limsoon Wong
Limsoon Wong National University of Singapore
Val Tannen
Val Tannen University of Pennsylvania
Sanjeev Khanna
Sanjeev Khanna University of Pennsylvania
Malcolm Atkinson
Malcolm Atkinson University of Edinburgh
Dan Suciu
Dan Suciu University of Washington
Jamie A. Davies
Jamie A. Davies University of Edinburgh

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

As the demand for tech-savvy professionals grows, diverse online degree options make it more accessible than ever to upskill or change careers in computer science and related fields. Choosing the right program involves weighing both educational value and cost.

For those starting out, an affordable online bachelor's degree offers a flexible start to a career in computer science, data analysis, or software development. Engineering-minded students can consider obtaining an online engineering degree; understanding online engineering degree cost is essential for informed decision-making.

Mid-career professionals seeking leadership roles in technology sectors might be interested in affordable emba programs, which blend management and technical skills for advancement. Additionally, students interested in the intersection of technology and information management can explore the pathway of a master's in library science by researching library sciences degree options.

Each pathway opens doors to innovative roles in STEM, libraries, and tech-driven industries, letting you personalize your educational journey while controlling costs.

Best Scientists Citing Peter Buneman

Trending Scientists