On the afternoon of 22nd October 2025, 40 people gathered in Bentham House to celebrate the winners and honourable mentions of this year’s UCL Open Science and Scholarship Awards.

Sandy Schumann and Jessie Baldwin, the UKRN Local Network Leads at UCL, hosted the ceremony and awards were presented by David Shanks, UCL’s UKRN Institutional Lead. Sandy began by congratulating this year’s cohort – 69 applications were submitted for consideration this year, so the competition was fierce! She also thanked the judges, as well as UCL Press for sponsoring the event.

There were five categories in total, and after the awards were presented, the overall winner of each category showcased their project.

The first category was, ‘Activities Led By Non-Academic Staff’, won by Vassilis Sideropoulos (Senior Research Technical Professional, Department of Psychology and Human Development, IOE) for his work establishing an open research training programme and practice community within the IOE. Vassilis saw the need to make open research practical and relevant, and created a programme with modular training covering topics such as Data Management and Pre-Registration. Following feedback on the initial training programme delivered between 2019-2023, he spent 18 months considering how to improve it, which led to a revamped programme with more applicable guidance. Alongside this, he recognised that researchers were seeking a community, a place where they could reach out to someone who could train them and respond to their questions, which led him to establish an open research practice community.

To encourage engagement with the practice of open science, an understanding of what researchers need is vital. By listening and responding to feedback, Vassilis recognised this and has created a programme that has transformed the ways in which IOE researchers engage with and understand open science.

The winner of the second category, ‘Activities by academic staff (including post-docs) or PhD students: Open-source software/analytical tools’, was Deyu Ming (Lecturer in Mathematics and Data Analytics, School of Management, Faculty of Engineering) for the development of the open-source package ‘DGPSI’, which allows for scalable surrogate modelling of expensive computer models and model networks. In his showcase, Deyu took us on the journey of this project. From the origins of the idea in 2019, to translating it into something that others could use and publishing it on GitHub in 2020, to it subsequently appearing on the python package index and on CONDA in 2022. But it didn’t stop there. In 2023, the package started making considerable impact through the UKRI-funded projects Net Zero Plus and ADD-TREES, which support AI-enhanced tree-planting decision tools used by DEFRA, Forest Research, the National Trust, and other stakeholders to advance the UK’s Net Zero 2050 goals.

Since 2021, there have been 19 releases of the software, and it is now 60x faster than the original. As creator, lead developer, and sole maintainer of ‘DGPSI’, Deyu has worked incredibly hard on this open-source software, and with already over 100,000 downloads, it will no doubt continue to make a resounding and long-lasting impact.

The award for ‘Activities led by undergraduate or postgraduate students’ went to Yinan Chen, Eric Chen and Adelina Xie (undergraduate students at the Department of Statistical Science, Faculty of Mathematical and Physical Sciences) for developing an open peer-review system for statistical science undergraduate coding assignments as part of a UCL ChangeMakers project. The problem they set out to address was the limitation in Moodle (the learning platform used at UCL) with regard to peer review, as students could only receive general feedback on coding assignments. Since Moodle only supports the review of PDF outputs and not raw R code, there was no option for line-by-line code reviews, and they felt that collaborative learning opportunities were being missed. Their solution: GitHub and Moodle integration. This innovative hybrid approach, with GitHub’s powerful code review system and Moodle’s familiar interface, has led to a practical, accessible and scalable tool designed for students, by students.

This is a recently concluded pilot project, but it is already having significant impact. A paper is being written on it for the Journal of Open-Source Education, and it has attracted interest for presentation at the Royal Statistical Society’s education conference, which shows its potential for nation-wide statistical education – testament to Yinan, Eric and Adelina’s hard work and dedication. Alongside this, their commitment to the practice of open science at such an early stage in their academic career was inspiring to see.

For the category ‘Activities led by academic staff (including post-docs) or PhD students: Open publishing’, the award was presented to Adam Crymble (Lecturer of Digital Humanities, Department of Information Studies, Faculty of Arts and Humanities), for the open publishing initiative ‘Programming Historian’ which he co-founded. Programming Historian offers over 250 peer-reviewed tutorials for digital humanities in English, Spanish, French, and Portuguese. Adam explained how a gap in digital skills amongst humanities professionals was the motivation for the project, and from its humble beginnings as a blog, it has become a financially self-sustaining open publisher. By offering practical applications and case studies in each tutorial, as well as ensuring translations are culturally adapted, this project has had far-reaching influence and continues to do so.

Since the outset, community and collaboration have been vital in the development of Programming Historian, and Adam has worked hard to expand the project’s global community and to ensure inclusivity. This approach, alongside the use of open peer review and the promotion of open data and open-source tools, epitomises the principles of open science and was fantastic to hear about.

The final category was ‘Activities by academic staff (including post-docs) or PhD students: Enhancing open science and reproducibility capacity in the academic community’, won by Martin Mokros (Lecturer in Earth Observation, Department of Geography, Faculty of Social and Historical Sciences) for his COST Action 3DForEcoTech project. Four years ago, Martin noticed the issue of scientists undertaking similar forest ecosystem research but not talking to each other about it. He wanted to standardise laser scanning technologies for forest ecology and inventory to allow for collaboration, and so launched COST Action 3DForEcoTech – the first global open-science network focused on ground-based 3D forest monitoring. With over 600 members from 50+ countries, the reach is impressive, and it is an innovative approach to scientific practice. Open science was a key motivation for the project, and it incorporates fully accessible datasets, algorithms and benchmarks results, as well as open-source software and an algorithm library.

Alongside the provision of open data and tools, this project has engaged with open science by creating equitable access to knowledge and opportunities through supporting ECRs, enforcing gender balance and ensuring participation from underrepresented regions. The idea of equitable access underpins the entire concept of open science, and by making it a central tenet to the COST Action 3DForEcoTech project, Martin has provided an excellent example of how this can be done.

Each of these award winners have advocated for, harnessed and showcased open science in various fields of research and study, and we are delighted that they have received recognition with a UCL Open Science & Scholarship Award.

We are looking forward to hearing about these projects’ ongoing impact and wonder what new initiatives they might inspire!

The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Stay connected for updates, events, and opportunities.

Follow us on Bluesky, LinkedIn, and join our mailing list to be part of the conversation!

Share this post on Bluesky

Guest post by Sheetal Saujani, Citizen Science Coordinator in the Office for Open Science & Scholarship

Citizen Science, where members of the public contribute to academic research, is reshaping how we do research. It opens new possibilities for data collection, community engagement, and impact, and at UCL, it’s increasingly seen as a key part of open and inclusive research.

In this post, we explore some of the platforms that make Citizen Science possible, including iNaturalist, and share insights from Professor Muki Haklay’s (UCL Extreme Citizen Science) blog to inspire UCL researchers to get involved.

Why Citizen Science platforms matter

Citizen Science platforms aren’t just bits of technology – they are powerful tools for bringing people and research together. They help researchers:

• Collect data on a large scale, across different locations and time periods
• Work with diverse communities in ways that feel meaningful
• Enhance the impact of their research by opening it up to the public
• Recognise and include lived experience and local knowledge as valuable data

Citizen Science platforms make it easy for anyone to take part by connecting researchers with thousands (or even millions) of contributors. Whether it’s identifying wildlife, tracking pollution, or classifying stars, Citizen Science tools make it easy for anyone to take part.

But not every platform fits every project. It’s worth considering how easy it is to use, the quality of the data, ethical considerations, and how long the platform can be supported. It’s great that there are now a wide range of tools out there to support different research areas.

Popular platforms to explore

Here are a few Citizen Science platforms worth considering:

1. Zooniverse – a platform for crowdsourced data analysis in fields ranging from climate science to history.
2. Cochrane Crowd – global community classifying health research to support systematic reviews, open to all with no prior expertise needed.
3. SciStarter – a hub connecting volunteers to projects across science, health, and the environment.
4. GLOBE Observer – a NASA app for environmental monitoring including cloud cover and mosquito habitats.

Many of these tools are open source or open access, which aligns with UCL’s Open Science approach to research.

Spotlight on iNaturalist

iNaturalist is one of the world’s leading Citizen Science platforms, built to help people record and share observations of biodiversity. With over 150 million contributions, it reflects the core values of open Citizen Science: it’s user-friendly, community-driven, and open in its data policies.

If you’re interested in tracking urban wildlife, exploring plant ecology, or examining environmental change, iNaturalist offers:

• Community-powered species ID: observations are confirmed by a global network of experts and enthusiasts.
• Open data integration: verified sightings feed directly into the Global Biodiversity Information Facility (GBIF), supporting research and conservation worldwide.
• Educational value: a powerful tool for learning about local ecosystems, supporting outreach, and involving the public in meaningful fieldwork.

For UCL researchers in ecology, conservation, education, or public engagement, iNaturalist offers a ready-made platform for collaborative projects, supporting both academic outcomes and community impact.

Reflections on iNaturalist from Prof. Muki Haklay

At the CAPS25 conference, iNaturalist’s Executive Director, Scott Loarie, delivered the opening keynote sharing five key lessons from the platform’s 17-year evolution – from an MSc project to a global biodiversity tool.

In a follow-up blog post, Professor Muki Haklay (UCL Extreme Citizen Science) reflects on these insights, highlighting iNaturalist’s focus on a pressing challenge: documenting species before they disappear. With one in three species at risk, the platform’s mission is urgent.

Prof. Haklay praises iNaturalist for making participation fun and not too complicated, empowering people to contribute meaningfully – from spotting rare birds to discovering new butterflies. He also emphasises the social side of Citizen Science, where events like the City Nature Challenge become global celebrations of biodiversity.

He describes iNaturalist as “a new kind of scientific instrument” – open, scalable, and powered by AI. Millions of photos help track species distribution, detect invasive spread, and even reveal behavioural patterns. AI/computer vision is “providing a new journey,” he notes, with tools that link images to DNA and uncover new species.

For UCL researchers, Prof. Haklay’s reflections remind us to think beyond data collection. How can we design Citizen Science that’s inclusive, engaging, and makes a difference in the world?

Next steps

Citizen Science can enhance public engagement, enable large-scale data collection, and support the co-production of knowledge – especially when linked with Open Science values. To get started:

• Choose a platform that fits your research needs
• Pilot a small-scale activity or join an existing project
• Reflect on inclusion, ethics, and sustainability from the outset
• Connect with UCL’s Citizen Science community for guidance and support

Let’s collaborate

Have you used a Citizen Science platform in your research or teaching? Or are you just getting started and curious about the possibilities?

Platforms like iNaturalist show how Citizen Science can be rigorous, inclusive and impactful – offering new ways to collaborate, engage communities and produce knowledge. As UCL advances its Open Science agenda, now is a great time to consider how Citizen Science can enhance your work across disciplines.

The UCL Office for Open Science & Scholarship is here to support you. Our Citizen Science Support and Training resources include guidance on integrating Citizen Science into your projects, information on key platforms, and our favourite Citizen Science initiatives from around the world. You can also explore the Principles of Citizen Science at UCL to shape your approach from the outset.

Whether you’re starting a project or exploring ideas, we’d love to hear from you. Visit the UCL Citizen Science website to learn more – and let’s work together to make research more open, inclusive, and collaborative.

Share this post on Bluesky

Back at the end of April, UCL hosted its first-ever Replication Games thanks to a grant from the Research Culture Seed Fund awarded to Kirsty Wallis, Head of Research Liaison at UCL Library Services, and Sandy Schumann, Lecturer in Security and Crime Science and local network lead for the UK Reproducibility Network. The event was facilitated by Derek Mikola from the Institute for Replication (I4R).

Three teams worked together to try to reproduce the analysis and results of a published paper – all in one day. They used only the information provided by the authors’ descriptions of the methodology and analytical approach, as well as public datasets and, to the extent that this was available, code. The groups consisted of a mix of researchers at different career levels and from altogether nine different disciplines.

The day kicked off early with an introduction by Derek, who got everyone set up in their groups, well provisioned with coffee and snacks. The groups had already been working together in the lead up to the event itself, selecting a paper from a list compiled by the I4R and familiarising themselves with the materials the authors had shared. Throughout the day, the teams encountered several challenges. Some discovered that packages that were used to run the analysis were no longer supported, meaning, ultimately, that the core analysis could not be conducted. Others identified questionable procedures to re-code variables, which meant that once variables were treated appropriately, results were not reproduced. Only one of the teams came to the conclusion that the published findings were largely reproducible.

Overall, the replication games were a roaring success. Participants were able to connect with researchers from other disciplines and gain hands-on experience in the workflow of reproducing published work. They also reported that they developed a better understanding of how to present their own work in a manner such that it is detailed enough to be reproduced.

All teams will document their analyses in reports that will be published by I4R soon, so watch this space and we will share the final product!

Share this post on Bluesky

Get involved!

The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Stay connected for updates, events, and opportunities. Follow us on Bluesky, and join our mailing list to be part of the conversation!

Guest post by Christine Daoutis, UCL Copyright Support Officer. 

This the third blog post of the collaborative series between the UCL Office for Open Science and Scholarship and the UCL Copyright team. Here, we continue our exploration of important aspects of copyright and its implications for open research and scholarship.

In a previous post we introduced questions that arise when using and creating materials protected by copyright. What options are available to you if you want to reuse others’ work (e.g. articles, theses, images, film, code) in your research? And what do you need to consider before you share your own research with others? Issues around copyright protection, permissions, exceptions, licences, and ownership need to be examined when creating new works and including others’ materials. These questions are also relevant when we think about works that are created with the use of GenAI tools, such as ChatGPT. However, with the use of these technologies still being relatively new and the legal aspects being shaped as we speak, answers are not always straightforward.

GenAI Training Data: GenAI models are trained on a large number of materials, usually protected by copyright (unless copyright has expired or been waived). Does this mean AI companies are infringing copyright by using these materials? How would copyright exceptions and fair dealing/fair use apply in different countries? How would licence terms – including the terms of open licences – be respected? Answers will come both from legislation and codes of practice introduced by governments and regulatory bodies (such as the EU AI Act) and from the outcomes of court cases (see, for example, Getty Images vs Stability AI, the Authors’ Guild against OpenAI and Microsoft.

User Prompts: The prompts a user provides to the model (instructions, text, images) may also be protected. You should also consider whether the prompts you enter include any confidential/commercially sensitive information that should not be shared. Please see UCL’s IP policy for guidance on this.

AI-Generated Work: Is the AI-generated work an original work protected by copyright? Is it a derivative of other original works, and therefore, possibly infringing? If it is protected, who owns the copyright? The answer to this will vary by case and jurisdiction. In the US, a court ruled that AI-generated images in a comic book were not protected, although the whole comic book and story were. In China, it was ruled that images generated with the use of GenAI tools would be protected, with the owner being the person who provided the prompts. The UK’s CDPA (9.3) states that ‘in the case of a literary, dramatic, musical or artistic work which is computer-generated, the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken’.

In short, GenAI raises questions about what constitutes an original work, what constitutes infringement, how copyright exceptions and fair dealing/fair use are applied, and how authorship is established. While these questions are still being shaped, here are three things you can do:

1. Consider any limitations in using GenAI besides copyright (e.g., confidentiality, biases, publishers’ policies). See UCL’s Generative AI hub for guidance.
2. Be transparent about how you use GenAI. See UCL Library guidance on acknowledging the use of AI and referencing AI.
3. If you have any copyright-related questions on the use of GenAI, contact the copyright support service.

 While GenAI has opened up more questions than answers around copyright, it also offers an opportunity to think about copyright critically. Stay connected with us for Part 2 of this blog post, which will discuss how new technologies, including GenAI, are changing our understanding of copyright. We look forward to continuing this important conversation with you.

Get involved!

The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Stay connected for updates, events, and opportunities. Follow us on X, formerly Twitter, LinkedIn, and join our mailing list to be part of the conversation!

 

 

Guest post by Christine Daoutis, Copyright Support Officer

Welcome to the inaugural blog post of a collaborative series between the UCL Office for Open Science and Scholarship and the UCL Copyright team. In this series, we will explore important aspects of copyright and its implications for open research and scholarship.

Research ideas, projects, and their outcomes often involve using and producing materials that may be protected by copyright. Copyright protects a range of creative works, whether we are talking about a couple of notes in a notebook, a draft thesis chapter, the rough write-up of a data, a full monograph and the content of this very blog. While a basic knowledge of copyright is essential, particularly to stay within the law, there is much more to copyright than compliance. Understanding certain aspects of copyright can help you use copyright materials with more confidence, make use of your own rights and overall, enhance the openness of your research.

This first post in our series is dedicated to exploring common questions that arise during research projects. In future posts, we will explore some of these questions further, providing guidance, linking to new resources, and signposting relevant workshops. Copyright-related enquiries often arise in the following areas:

Reusing other people’s materials: How do you GET permission to reuse someone else’s images, figures, software, questionnaires, or research data? Do you always need permission? Is use for ‘non-commercial, research’ purposes always permitted, or are there other factors to consider? How do licenses work, and what can you do when a license does not cover your use? It’s easy to be overconfident when using others’ materials, for example, by assuming that images found on the internet can be reused without permission. It’s equally easy to be too cautious, ending up not making use of valuable resources for fear of infringing someone’s rights. Understanding permissions, licenses, and copyright exceptions – what may be within your rights to do as a user – can help you.

Disseminating your research throughout the research cycle: There are open access options for your publications and theses, supporting access to and often, reuse of your work. How do you license your work for reuse? What do the different licenses mean, and which one is most suitable? What about materials produced early on in your research: study preregistrations, research data, preprints? How can you make data FAIR through licensing? What do you need to consider when making software and other materials open source?

Is your work protected in the first place? Documents, images, video and other materials are usually protected by copyright. Facts are not. For a work to be protected it needs to be ‘original’. What does ‘original’ mean in this context? Are data protected by copyright? What other rights may apply to a work?

Who owns your research? We are raising questions about licensing and disseminating your research, but is it yours to license? What does the law say, and what is the default position for staff and students at UCL? How do contracts, including publisher copyright transfer agreements and data sharing agreements, affect how you can share your research?

‘Text and data mining’. Many research projects involve computational analysis of large amounts of data. This involves copying and processing materials protected by copyright, and often publishing the outcomes of this analysis. In which cases is this lawful? How do licences permit you to do, exactly, and what can you do under exceptions to copyright? How are your text and data mining activities limited if you are collaborating with others, across institutions and countries?

The use of AI. Speaking of accessing large amounts of data, what is the current situation on intellectual property and generative AI? What do you need to know about legal implications where use of AI is involved?

These questions are not here to overwhelm you but to highlight areas where we can offer you support, training, and opportunities for discussion. To know more:

• Follow future posts on this blog.
• Register for an upcoming copyright session. If you cannot make those dates, please contact copyright@ucl.ac.uk to arrange a bespoke session.
• Visit our training and resources page for more ideas and links to online tutorials.
• Have a head start: visit our guidance on copyright and publications, copyright and research data and look out for upcoming guidance on text and data mining.

Get involved!

The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Stay connected for updates, events, and opportunities. Follow us on X, formerly Twitter, LinkedIn, and join our mailing list to be part of the conversation!

 

Guest post by Sheetal Saujani, Citizen Science Coordinator

We are pleased to launch our new and improved Citizen Science web pages on UCL’s Office for Open Science and Scholarship website. You can now access the updated content and browse what UCL is doing in this fast-growing and exciting area!

Citizen science includes a wide range of activities, and it is gaining increasing recognition among the public and within the area of research. UCL recognises citizen science as a diverse practice, encompassing various forms, depths and aims of collaboration between academic and community researchers and various disciplines.

Check out our new website pages:

• Defining Citizen Science: whether you call it participatory research, community action, crowdsourcing, public engagement, or anything else, have a look at our word cloud showing various activities and practices falling under one umbrella. UCL teams are collaborating on different projects and working together under a joint mission to strengthen UCL’s activities. This fosters stronger connections and more collaborative solutions.
• Citizen Science projects: discover the broad range of innovative projects at UCL (grouped by discipline) showcasing various ways to use a citizen science approach in research. If you have a citizen science project to feature or have any questions, please contact us.
• History of Citizen Science: explore the exciting history of citizen science, early definitions, and three relevant periods in modern science. Learn about one of the longest-running citizen science projects!
• Types and levels of Citizen Science: read about the growth of citizen science, which has led to the development of three broad categories: ‘long-running citizen science’, ‘citizen cyberscience’, and ‘community science’. Citizen science practices can be categorised into a continuum using the ‘Doing It Together Science’ escalator model. This model focuses on individual participation levels, allowing individuals to choose the best level for their needs, interests, and free time.
• UCL Citizen Science Certificate: find out about this high-quality, non-academic certification awarded to individuals who complete a training programme as part of the UCL Citizen Science Academy. The Certificate recognises research abilities through participation in active projects, enabling citizen scientists to influence local decisions.

The Office for Open Science and Scholarship is working to raise awareness of citizen science approaches and activities to build a support service and a community around citizen science.  We are bringing together colleagues who have run or are currently running citizen science projects, to share experiences and encourage others to do the same.

If you are interested in citizen science, we would like to hear from you, so please get in touch by email openscience@ucl.ac.uk and tell us what you need.