Theoretical foundations of databases and research into data management systems, distributed information management and query languages.

This strategy recognises that this is a relatively small but high-quality research area in the UK.

By the end of the current Delivery Plan, we aim to have:

  • Databases researchers contributing to the ongoing challenges posed by data science. This should include new ways of developing scalable data management systems that can manage high volumes of complex data in infrastructures on which data analytics can then be performed
  • A portfolio of Databases research and research training that complements related activity in the Alan Turing Institute and helps to achieve the aims set out in EPSRC's Data Enabled Decision Making priority for the Information and Communication Technologies (ICT) Theme. This will require the strengthening of existing links with other researchers in the data science landscape, including research areas such as Artificial Intelligence Technologies and Information Systems
  • Increased translation of theoretical work into practice and improved links with users of database technology. There are opportunities for researchers to take advantage of datasets acquired by other sectors (e.g. medicine, retail and automotive). Consideration of users of database technology should occur from the outset; this should be in line with the ethos of EPSRC's People at the Heart cross-ICT priority

Although concentrated in a small number of groups, UK work in this research area is high quality and has strong international standing, with UK researchers well-represented at top international conferences such as VLDB (Very Large Data Bases) and SIGMOD/PODS (Special Interest Group on Management of Data / Principles of Database Systems), (Evidence source 1). The community in the UK is cohesive and well-placed to take advantage of any opportunities provided by the Alan Turing Institute. The EPSRC portfolio in this area has doubled over the period of the last Delivery Plan and this investment continues to be concentrated at the leading groups (Evidence source 2). In recent years, however, new researchers based at other groups and institutions have started to come into the area (Evidence source 1).

The research supported in the Databases area has clear relevance to nationally important challenges related to data science, particularly around managing and structuring data prior to performing analytics (sometimes termed ‘data wrangling’), (Evidence source 3,4). This is especially relevant in complex, large or distributed architectures and systems. The recent establishment of the Alan Turing Institute demonstrates a clear aspiration for the UK to be a leader in data science (Evidence source 5) and Databases research should contribute to the foundations of this effort.

There is a small training portfolio but it is well-balanced between individual studentships and cohort-based training. This should be maintained to ensure a ‘people pipeline’ into academia and industry (Evidence source 2).

Some strong industrial links exist to work ongoing in this area (Evidence source 2) and across sectors demand is growing for maintenance of and access to data at scale.

This research area will contribute most strongly to the Connected, Productive and Healthy Nation Outcomes, and especially to the following Ambitions:

C1: Enable a competitive, data-driven economy

This research area is expected to be a key contributor as it can improve data management and data wrangling prior to analytics.

P4: Drive business innovation through digital transformation

This area could maximise the impact of data and information on business models and service delivery.

H3: Optimise diagnosis and treatment

This area could develop new ways of managing clinical data for analysis and feedback.

  1. Community engagement (individual input, group feedback and team visits) and input from the ICT Strategic Advisory Team, the UK Computing Research Council (UKCRC) Executive Committee and Research Excellence Framework (REF) 2014 panellists (sub-panel 11)
  2. Analysis of EPSRC application and student data
  3. EPSRC, ICT Perspectives on Big Data Analytics Workshop (PDF), (2015)
  4. ACM, The Beckman Report on Database Research, (2016)
  5. The Alan Turing Institute, Shaping our Strategy (PDF), (2016)

Research area connections

This diagram shows the top 10 connections between Research Areas within the EPSRC research portfolio. The depth of the segment relates to value of grants and the width of the segment relates to the number of grants shared by those two Research Areas. Please click to see the related Research Area rationale.

Visualising our Portfolio (VoP)
Visualising our portfolio (VoP) is a tool for users to visually interact with the EPSRC portfolio and data relationships.

EPSRC support by research area in Databases (GoW)
Search EPSRC's research and training grants.

Contact Details

In the following table, contact information relevant to the page. The first column is for visual reference only. Data is in the right column.

Name: Liam Boyle
Job title: Portfolio Manager
Organisation: EPSRC
Telephone: 01793 444364