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Oxford e-Research Centre, Department of Engineering Science at Oxford

Oxford e-Research Centre

Enabling innovation: from data science research to application

We are a multidisciplinary data science research and education institute, part of the Department of Engineering Science at the University of Oxford. We research and implement innovative digital methodologies, information and computational solutions for academic research and industrial applications. Founded in 2006, the Centre provides a world-leading environment for over 50 staff, including six academics, students, data scientists postdocs, as well as professional research software and knowledge engineers, who work together on interdisciplinary projects for the benefit of other research and society.

Our impact-driven data science projects, products and infrastructure

What we do
  • Climate services
  • Cybersecurity
  • Data management & reproducibility
  • Digital humanities
  • Energy digitisation
  • Internet of things
  • Language modelling 
  • Scholarly publishing & communication
  • Scientific computing
  • Visual analytics
How we do it
  • Cloud computing
  • Machine learning & analytics
  • High performance computing
  • Software engineering
Oxford e-Research Centre researchers at Oxford Ideas festival IF

Our expertise spans across data science domains and technologies. Via a broad range of collaborations, we deliver novel methodological, technical, social and policy advancements across disciplines: physical sciences and engineering; arts, humanities and social sciences; energy and environment; the biological and medical sciences; as well as information and library sciences.

Our work is diverse and international. Our academics advise governments and other organisations on strategic data-drive decisions, work with policy makers on open and reproducible science agendas, consult for industry and publishers, collaborate with libraries and research communities around the world. Our academic staff run courses, training modules and events, as well as host and supervise under- and post-graduates, preparing the new generation of data scientists, scholars and entrepreneurs.

Participants at Narratives Through Data Event

Unlocking Musicology event 'Narratives through Data' July 2019

Energy MSc Students at Sandford Hydro

Students on the MSc Energy Systems course visit Sandford Hydro

Photograph of Janet Pierrehumbert by Ian Wallman

Professor of Language Modelling Janet B. Pierrehumbert. Photograph by Ian Wallman

Philippe Rocca Serra at the Fairplus SME And Innovation Forum 29 January 2020 Hinxton

Dr Philippe Rocca Serra at the FAIRplus Innovation and SME Forum, Hinxton

David De Roure Keynote at Internet of Things Congress in Bangalore

Professor David De Roure gives the opening keynote talk at the Internet of Things India Congress in Bangalore (Image: David Murray-Rust)

The Lovelace musical machine at Oxford e-Research Centre

The Lovelace engine visits the Centre. This musical machine was build to celebrate the work pioneering computer scientist Ada Lovelace

SKA radio telescope arrays, South Africa

SKA radio telescope arrays in South Africa. Image courtesy of SKA Organisation

MELD application Lohengrin Time machine landing page

Music Encoding and Linked Data (MELD) framework's ‘Lohengrin TimeMachine’, a digital companion to a musicological study of leitmotifs in Wagner’s opera.

RT @cyberwatchingeu: LIVE @FIWARE▶️ @DavidWallom, Associate Professor, Department of Engineering Science @UniofOxford & @cyberwatchingeu,…

RT @FIWARE: We look forward to welcoming Prof. David Wallom to the #FIWARECybersecurityDAY. David is Associate Professor and Associate Dire…

Our researchers have contributed to version 2.0 of the Music Encoding & Linked Data framework (MELD) software platform used by projects to combine digital music representations with contextual & interpretive knowledge in the Semantic Web #digitalmusicology https://t.co/O2usat7Z26 https://t.co/VfDxmnkoyx

Dr. Saiful Khan has received a @royalsociety Early Career Investigator Award for voluntary efforts in #DataVisualization & visual analytics aimed at combating #COVID19. Award acknowledges Dr Kahn's work on RAMP: Rapid Assistance for Modelling the Pandemic https://t.co/NmRxpMuDOv https://t.co/unaJFqZMUC

RT @oxengsci: What will it take to get to #netzero ? Professor David Wallom @OxfordeResearch & Dr Wainwright @TheSmithSchool will discuss t…