Open Research Award 2024 Shortlist

The University of Manchester is pleased to present the Open Research Award 2024 Shortlist, recognising commitment to open research principles and practices over the last year.

Lina Alaydi (a postgraduate researcher in the School of Health Sciences at the University) was commended for committed advocacy of open and transparent research dissemination and knowledge sharing.

My project focuses on smart-engineering of DNA oligonucleotides with specific recognition sequence and peptide attachment, introducing POC conjugates as a third anticancer therapeutic platform. POC target overexpressed microRNAs in various cancers to restore cell functionality with minimal side effects. Synthesizing high-yield POC and predicting their efficiency in biological systems are crucial. Post-experimentally, some POC compounds did not fully destroy the targeted RNA seed region, necessitating determination of site-selective structural demands.

Neurodivergent researchers face challenges accessing software for data visualization and reproducibility. Integrating coding of raw data can enhance accessibility and transparency. Adapting hybrid workflow would minimize bench testing, improve efficiency and reproducibility. Yet, facilitates miRNA cleavage dynamics by analyzing various supramolecular structures impact on RNA transesterification. Embracing open research principles can address these challenges.

  1. Data Sharing: Share simulation and experimental data openly for replication in a suitable repository or platform, to ensure researchers accessibility and replicate results.
  2. Transparent Methodology: Share documented methodologies used in simulations and experiments, with detailed supplementary materials for interested researchers.
  3. Open Access Publication: Publish findings in an open-access journal or platforms, to allow widespread dissemination of the research without access barriers.
  4. Open Peer Review: Opt for open peer review processes, to promote transparency and accountability in the review process.
  5. Collaborative Platforms: Encourage collaboration through collaborative platforms like GitHub or ResearchGate and ORCID, where code, data, and insights can be shared and discussed openly.
  6. Community Engagement: Engage with the broader scientific community through conferences, workshops, and online forums.
  1. Licensing and Attribution: Ensure proper licensing and attribution for shared data and code, while maintaining proper attribution to the original authors.

By adopting these practices, the research contributes to the open exchange of knowledge, fosters collaboration and reproducibility, maximizes inclusive impact approach for scientific interaction and promote community engagements.

Dr Zhonghua Zheng

Dr Zhonghua Zheng(an Assistant Professor in Data Science & Environmental Analytics) was commended for integration of open principles into Earth and Environmental Science MSc curriculum and commitment to open practices.

My research focuses on developing open-source computational (AI-driven and process-based) environmental modelling and data analytics tools. Specifically, my research interests centre on urban climates, air quality, and aerosol properties. I am currently working on projects that include improving the physical processes in urban climate models, specifically the Community Land Model - Urban (CLMU) and developing data-driven urban climate emulators. Additionally, my students and I are developing the CLMU-App to enable operating system-independent urban climate simulations.

During my time as a Data Scientist Intern at Bayer, I was assigned a research project that required using the conditioned Latin Hypercube Sampling method. Although an existing R package was available, my project necessitated an implementation in Python for specific reasons. This led me to discover a Python implementation, which was developed by a PhD student in her spare time. Since then, I have been more attentive to open research practices, although I had not yet begun to delve into the underlying principles of open research at that time.

Before joining The University of Manchester (UoM), I was actively developing open-source Python packages, such as pyEOF and pmcpy, and routinely shared the data and code associated with my publications. However, it was only after joining UoM and learning about the work of the Open Research Office (OOR) and the broader open research culture at The University that I fully appreciated how my practices were aligned with open research principles. UoM's strong commitment to open research has not only deepened my dedication to these practices but also inspired me to more fully integrate them into my work.