Within the Data Science Institute, our aim is to improve the reproducibility and replicability of research by improving the reusability, sustainability and quality of research software developed across the University. We are currently funded by the N8CIR, and work closely with our partner institutions across N8 Research.
The recent growth of data scientific methods into all academic disciplines has created an unprecedented demand for research computing support. This is particularly so in fields which may be regarded as “non-traditional” users of research computing techniques.
Moreover, the pervasiveness of digital methods across these disciplines offers the opportunity to accelerate the research translation pipeline by wrapping up intellectual property in innovative digital solutions.
Lancaster University has researchers who:
- Need cross-departmental collaborations to develop data-scientific solutions for application-focused research questions [LMS];
- Need to accelerate their impact by translating innovative new ideas into robust and reliable software solutions for others to use [Psychology, LUMS];
- Wish to explore data-infrastructure techniques and solutions to accelerate their research [FASS, Mathematical Sciences].
In addition, Lancaster has a nascent Research Software Engineer community currently backed by N8CIR, but which needs to grow into a self-sustaining community of specialist
individuals filling the gap between corporate IT support (ISS) and the academic research community.
Aims
The recent growth of data scientific methods into all academic disciplines has created an unprecedented demand for research computing support. This is particularly so in fields which may be regarded as “non-traditional” users of research computing techniques. The pervasiveness of digital methods across campus offers the opportunity to explore how we can accelerate our research translation pipeline, wrapping up our research outputs in innovative digital solutions to benefit our target audiences.
The Data Engineering Theme supports researchers who:
- Need cross-departmental collaborations to develop data-scientific solutions for application-focused research questions;
- Need to accelerate their impact by translating innovative new ideas into robust and reliable software solutions for others to use;
- Wish to explore data-infrastructure techniques and solutions to accelerate their research.
The Data Engineering Theme has a growing Research Software Engineer community currently backed by N8CIR, aiming to develop a self-sustaining community of specialist individuals to fill the gap between corporate IT support (ISS) and the academic research community.
Theme Functions
The proposed functions of the DSI Data Engineering Theme are:
Members
Professor Christopher Jewell
Professor in StatisticsBayesian and Computational Statistics, Biostatistics , CHICAS, DSI - Health, STOR-i Centre for Doctoral Training