Open in conducting research and acquiring data
Research data refers to any information collected, observed, generated, or created to support original research findings. This can include a wide variety of formats such as documents, spreadsheets, interview transcripts, images, audiotapes, databases, coding scripts, and workflows. While much of these data are digital, non-digital formats like laboratory notebooks and diaries are also considered research data. Ensuring that this data are properly documented and stored is important for validating research results and maintaining integrity.
Applying the principles of openness when conducting research and acquiring your data will promote transparency and robust methodologies. This could involve organising and sharing research materials, including study data, coding scripts, and workflows, in a way that aligns with FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Proper management ensures that data are reproducible and replicable across studies. While specific guidelines and best practice in open research differ slightly in each research field (see UKRN primer open research across disciplines), the transparency and reproducibility of research methods in most fields can be based on similar processes and systems.
What does reproducibility and replicability mean?
Putting it into practice
Explore these internal and external resources to learn how practices such as open protocols, reproducible workflows and increasing data reuse by researchers supports research integrity. The goal of this section is to empower you with the confidence to engage in at least one new open research practice.
Open protocols
Open laboratory notebooks
Finding and reusing data
Reproducible workflows
Organising, storing, and handling data
Participatory research
Training and development opportunities
Below is a curated list of resources to develop your learning in open research practices and considerations at the conducting research and acquiring data phase of a project.
Open to everyone
- Transparent and Open Social Science Research is a 5-week massive open online course (MOOC) that introduces learners to threats to research credibility and reproducibility, and tools and practices for ethical, transparent, and reproducible social science research.
- The Turing Way is an open science, open collaboration, and community-driven project. This is a comprehensive, self-paced resource is dedicated to supporting researchers make their collaborative, reusable and transparent. The resource was originally designed for data scientists, however the guiding principles and learning can be applied to any discipline.
- ReproducibiliTeach is a set of video tutorials aimed at biomedical researchers which share effective strategies to enhance the transparency and reproducibility of your research. Each video provides practical skills that viewers can directly apply to their own projects.
University of Leeds specific
- Advanced Research Computing offer a range of training courses, including version control with Git and GitHub, introductory programming and reproducible workflows.
- Contact email for more information and support: research@library.leeds.ac.uk
Examples of good practice
Data reuse stories and use cases
OpenAIRE AMKE is a non-profit organisation that promotes open scholarship and enhances the discoverability, accessibility, shareability, and reproducibility of data-driven research globally. Supported by a network of national experts in Europe, the organisation aims to accelerate the adoption of Open Science.
OpenAIRE is collecting stories, use cases, and resources on data reuse to illustrate diverse experiences and their implications, including the FAIR4Health consortium which seeks to harmonise data privacy and health research data management, and examples from the University of Edinburgh DataShare institutional research data repository.
Recipe for Reproducible Success: Open lunch recording
Open research insights from Alex Coleman, a Research Software Engineer, and Daniel Valdenegro Ibarra, a PhD researcher from the School of Politics and International Studies. They present valuable tools and concepts for organising research data to enhance personal efficiency and ensure reproducibility for others. While many of their tips cater to those already familiar with IT, there is also ample support available for researchers looking to improve their computer skills.
Not just for STEM: Open and reproducible research in the social sciences
Open Lunch webinar Dr. Viktoria Spaiser, an Associate Professor in Sustainability Research and Computational Social Sciences, highlights the importance of open and reproducible research practices in the social sciences. She provides an overview of how these practices differ across quantitative, computational, and qualitative research, along with the evolving landscape of open science.
Dr. Spaiser also addresses the specific barriers to implementing open and reproducible research in social sciences and proposed potential solutions for overcoming them. She emphasises that transparency throughout the research process— from data collection to analysis and result communication— is crucial for ensuring that findings can be replicated by researchers in the future.
Read the blog and access the webinar recording here.
Further resources and tools
There are numerous resources available to support your open research practices and the following tools have been curated to help you take them to the next level.
Resources
- Research Data Management toolkit includes a good section on how to use existing data and a list of registries for suitable data repositories.
- The FAIR Cookbook: An online, open and live resource for the Life Sciences with recipes that help you to make and keep data FAIR.
Tools
- Transdisciplinary book on open workflows: Gandrud, C. 2020. Reproducible research with R and RStudio 3rd ed. Boca Raton, FL: CRC Press.
- Open Lab Notebooks: A laboratory notebooks sharing website.
- Protocols.io: An online platform that enables researchers to create, share, and publish scientific protocols.