The software and people behind academic research
From Saul Cozens on May 21st, 2021
The use of data and computational analysis in research is increasing and it is critical in getting new insights. But how does the code that drives this research get written? What is different about writing software in a research environment? What are the challenges around data management and infrastructure? And how can visualisation technologies make the outputs of research of greater value and interest to other researchers and the public?
This event is part of the Sheffield Digital festival. After registering you'll be sent a Google Meet link before the event.
The schedule for the event will be the following three 20-minute talks followed by Q&A.
Will Furnass, Research Software Engineer: Turning ideas into code.
Much of modern research is facilitated by code that researchers have had a hand in writing. In this first talk we explore the processes through which research ideas are encapsulated as software, which often involves interactive data exploration, then how this software evolves (or not) over time. We also discuss the computational demands of research and common technologies, before concluding with a look at challenges relating to the development of coding skills in academia, the drive for reproducible research, and how funding and incentives shape the research software lifecycle.
Joe Heffer, Research Data Engineer: Supporting Coronavirus Genomics.
We provided software engineering expertise for researchers from The University of Sheffield who are participating in the COVID-19 Genomics UK (COG-UK) Consortium which provides large-scale, rapid genomic sequencing to guide the public health response to the pandemic.
Gemma Ives, Research Data Scientist: Communicating Research Through Visualisation.
More and more often researchers are openly sharing their research data and their findings, encouraging engagement and scrutiny from politicians and the public. This final talk will discuss how and why data visualisation is becoming an essential skill in academic research.