Data Analytics Team

LIDA Data Analytics Team

The Data Analytics Team (DAT) is a group of specialists in data management, data analysis and software engineering, who collaborate with LIDA researchers across all stages of their projects. The team has a central role in LIDA, managing the secure research platforms, collaborating on research projects, and offering data analytics and, in collaboration with Information Governance information security expertise to researchers. 

If you have any questions about how the DAT can support your research project or grant proposal, please contact us for a discussion about your requirements by emailing DAT@leeds.ac.uk. 

Our expertise 

The team are highly experienced at collaborating with researchers across the Research project life cycle in four key areas:  

Data management
We have supported hundreds of research projects with their database management and administration, using technologies such as SQL Server and Microsoft Azure. We manage the secure transfer, hosting and use of sensitive data in secure research environments at LIDA.

Data analytics
With years of academic experience on data-driven research projects, we collaborate with researchers on any data transformation, visualisation and analysis tasks. We can help implement all kinds of statistical and machine learning methods. We aim to be language agnostic, but with greatest support for R, Python and SQL. We can help analyse datasets that are big or small, flat or relational, structured or heterogeneous, local or cloud-hosted.

Research software engineering
We are aligned with and supported by a wider group of Research Software Engineers (RSEs) from the Research Computing Group at the University of Leeds. The RSEs work with academics to develop software and champion best practices for research software development in the university and wider academic community. Our RSEs can help if you are programming for the first time, want to improve your coding and documentation skills, discover new tools, access computing facilities, or you want to turn your code into a published software package.

Information governance
Our team includes data security experts who ensure that LIDA’s infrastructure of secure research environments and LIDA’s research management process (RMP) meets all necessary information governance and data protection requirements. We support researchers working with sensitive data to meet their regulatory requirements, such as EU GDPR, ISO27001 information security standard, the Data Security and Protection Toolkit and project specific Data Sharing Agreements.  

LIDA’s secure research platforms 

The DAT manages research projects on two platforms, the Integrated Research Campus (IRC) and SEEDThese platforms provide different levels of data protection: The IRC provides a secure Virtual Research Environment (VRE) that complies with the ISO27001 information security standard and should be used for research requiring the highest levels of data security and confidentiality. Both the IRC and SEED comply with the NHS Data and Security Protection Toolkit. LIDA is continually working to improve its platforms, including the development of cloud-based secure research environments.  

If you would like to discuss more about which platform is suitable for your research data please contact us using the email address above. You can find out more about LIDA’s infrastructure on its homepage. 

Meet the Data Analytics and Information Governance Team

Adam Keeley, Data Analytic Team Manager

Before joining the University of Leeds, Adam worked in data based Management Information roles in both public and private sector. Used to manipulating personally and commercially sensitive data in bulk he is familiar with issues surrounding both data management, quality and governance.  

His background is in harnessing database and business intelligence tools. He is proficient working with SQL Server, C#, SSAS, SSISSSRS and is comfortable using other technologies as appropriate. 

Ifeanyi Chukwu, Research Software Technician

Ifeanyi is a former data scientist within the LIDA Data Scientist Development Programme. During this time he worked on a DATA-CAN project using LTHT cancer referrals data and the national cancer referrals registry data, and participated in Alan Turing Data Study Groups.

He has worked with various supervised/unsupervised machine learning models in Python, is conversant with R, and is currently building his SQL skill.
Ifeanyi is interested in using digital technologies (such as LASER) to build a trustworthy and equitable future, where everything good is possible.