Unleash Your Data and Software 2024 - funded projects announced

Promotional banner for the unleash your data 2024 competition

We are delighted to announce the successful recipients of funding from Unleash Your Data and Software 2024, a funding competition for research students and staff at the University of Sheffield to apply for an award of up to £5000 for a project to make their research data or software more visible and reusable.

The funding competition was open to all researchers at the University of Sheffield, including postgraduate research students and those in research-related roles.

What data and/or software were eligible?

Data and/or software projects eligible for the competition included:

  • Legacy research data currently unavailable for reuse, that could be made available through ORDA or another data repository with the use of the funds. 
  • Innovative projects for promotion of existing datasets in ORDA (or other data repositories) using visualisations or events (such as symposia/expos) that increase the profile of the dataset and increase understanding of its potential for reuse.
  • Holistic approaches to making entire research projects more FAIR (Findable, Accessible, Interoperable and Reusable) and, where appropriate, open.
  • Enhancing the visibility, reproducibility, and reusability of research code & software by: making it open source and publicly contributable; adding documentation, tests and citation metadata; refactoring to aid in usability.

The successful projects

The competition received a high standard of applications from across different Faculties and career stages, making the judging process extremely competitive. The successful projects, which will take place between 1st January and 31st July 2024, are:

Development of a TopoStats training program for improved user accessibility

Laura Wiggins (Materials Science and Engineering)

Our team has created TopoStats, an open-source Python toolkit for automated processing and analysis of Atomic Force Microscopy (AFM) images. TopoStats equips researchers with tools to quantify observations from AFM images, from analysis of altered DNA shape upon interaction with protein through to characterisation of nanomaterials. As a result, it holds the potential to advance a broad range of biophysical research applications. The Unleash Your Data and Software funding will enable us to develop and deliver a training program that covers basic requirements for TopoStats installation such as the Command Line Interface and virtual environments through to practical biological examples, demonstrating how users can customise the code and workflow for their specific research applications. Our proposed training resources and courses will be available online to enhance visibility and accessibility among international research groups utilising AFM, promoting wider adoption of TopoStats and encouraging international research collaborations.

EA National Database of River Traces and Temporal Concentration Profile Analysis Tool

Ian Guymer (Civil Engineering)

The management of water quality in river networks is essential for ecological and human well-being. The Environment Agency National Database of River Traces is the single largest dataset and is typically used to support river water quality modelling. This project will modernise this dataset, which was originally formatted as a Microsoft Access 2000 database, making it more easily accessible and more widely available. At the same time, this project will make available the Temporal Concentration Profile Analysis Tool, for analysing solute trace data, including a suite of software routines to quantify travel time and various mixing parameters used in numerical models. These data and tools will support the management of river water quality.

Making stroboPY FAIR for Accelerated Advances in Green Energy Technology

Robert Oliver (Materials Science and Engineering)

We have developed stroboPY, a piece of python software that allows us to control a brand new microscopy technique and analyse the data in real-time. This technique, stroboscopic scattering microscopy, allows us to 'see' electrons moving within our materials which is vital information to help my team improve the next generation of solar panels. The Unleash Your Data & Software award will enable us to collaborate closely with the Research Software Engineering team to refine stroboPY, making it as robust, open and accessible as possible. Our goal is for stroboPY to remove a crucial barrier to entry to this microscopy technique and its analysis so as many researchers as possible around the world can benefit from this tool, accelerating the development of next generation materials for a clean energy solution.

PyHYPER: Bridging Expertise with Open-Source Solutions for Sustainable Hydropower Design

Veysel Yildiz (Civil and Structural Engineering)

Hydropower is clean renewable energy technology that is key to the transition to a carbon-free future. HYPER, currently attracting attention from researchers and hydropower designers, is software that optimises small hydropower plant designs, considering parameters for energy production and economic profitability based on project-specific characteristics. This project involves converting HYPER’s existing state-of-the-art MATLAB toolbox into an open-source Python version. This aligns with the demand for accessible research tools, following the FAIR principles (Findable, Accessible, Interoperable, and Reusable). By creating a freely accessible and efficient Python version, the project aims to maximise HYPER’s impact, ensuring broader accessibility, adaptability, and usability. The refined and open source HYPER will serve as a bridge between technical expertise and practical application, facilitating more informed decision making in hydropower plant design and contributing to the advancement of sustainable energy solutions. 

Walking again: improving on sensory feedback platforms aimed at neuroprosthetics

Rodrigo Siqueira de Souza (AMRC, INSIGNEO and The Neuroscience Institute)

The Active Touch Laboratory is revolutionising real-time feedback neuroprosthetics with two Python packages that mimic tactile receptors in the hand and foot. Despite initial success, our journey uncovered hurdles like complex installations, visualisation glitches, and integration ambiguities with other packages. This project will untangle these challenges, paving the way for wider adoption. It will aim at a smoother, more accessible experience that ensures these platforms are widely available and operational for a longer period. 


We look forward to reporting the outcomes of these projects at OpenFest 2024.

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