Open Source Software Design for Academia

By Kirsty, on 27 August 2024

Guest post by Julie Fabre, PhD candidate in Systems Neuroscience at UCL. 

As a neuroscientist who has designed several open source software projects, I’ve experienced firsthand both the power and pitfalls of the process. Many researchers, myself included, have learned to code on the job, and there’s often a significant gap between writing functional code and designing robust software systems. This gap becomes especially apparent when developing tools for the scientific community, where reliability, usability, and maintainability are crucial.

My journey in open source software development has led to the creation of several tools that have gained traction in the neuroscience community. One such project is bombcell: a software designed to assess the quality of recorded neural units. This tool replaces what was once a laborious manual process and is now used in over 30 labs worldwide. Additionally, I’ve developed other smaller toolboxes for neuroscience:

• YAHT: Yet Another Histology Toolbox
• prettify_matlab: MATLAB Code Formatter
• brain_street_view: Interactive Brain Mapping

These efforts were recognized last year when I received an honourable mention in the UCL Open Science and Scholarship Awards.

In this post, I’ll share insights gained from these experiences. I’ll cover, with some simplified examples from my toolboxes:

1. Core design principles
2. Open source best practices for academia

Disclaimer: I am not claiming to be an expert. Don’t view this as a definitive guide, but rather as a conversation starter.

Follow Julie’s lead: Whether you’re directly involved in open source software development or any other aspect of open science and scholarship, or if you simply know someone who has made important contributions, consider applying yourself or nominating a colleague for this year’s UCL Open Science and Scholarship Awards to gain recognition for outstanding work!

Part 1: Core Design Principles

As researchers, we often focus on getting our code to work, but good software design goes beyond just functionality. In order to maintain and build upon your software, following a few principles from the get go will elevate software from “it works” to “it’s a joy to use, maintain and contribute to”.

1. Complexity is the enemy

A primary goal of good software design is to reduce complexity. One effective way to simplify complex functions with many parameters is to use configuration objects. This approach not only reduces parameter clutter but also makes functions more flexible and maintainable. Additionally, breaking down large functions into smaller, more manageable pieces can significantly reduce overall complexity.

Example: Simplifying a data analysis function

For instance, in bombcell we run many different quality metrics, and each quality metric is associated with several other parameters. In the main function, instead of inputting all the different parameters independently:

[qMetric, unitType] = runAllQualityMetrics(plotDetails, plotGlobal, verbose, reExtractRaw, saveAsTSV, removeDuplicateSpikes, duplicateSpikeWindow_s, detrendWaveform, nRawSpikesToExtract, spikeWidth, computeSpatialDecay, probeType, waveformBaselineNoiseWindow, tauR_values, tauC, computeTimeChunks, deltaTimeChunks, presenceRatioBinSize, driftBinSize, ephys_sample_rate, nChannelsIsoDist, normalizeSpDecay, (... many many more parameters ...), rawData, savePath);

they are all stored in a ‘param’ object that is passed onto the function:

[qMetric, unitType] = runAllQualityMetrics(param, rawData, savePath);

This approach reduces parameter clutter and makes the function more flexible and maintainable.

 2. Design for change

Research software often needs to adapt to new hypotheses or methodologies. When writing a function, ask yourself “what additional functionalities might I need in the future?” and design your code accordingly. Implementing modular designs allows for easy modification and extension as research requirements evolve. Consider using dependency injection to make components more flexible and testable. This approach separates the creation of objects from their usage, making it easier to swap out implementations or add new features without affecting existing code.

Example: Modular design for a data processing pipeline

Instead of a monolithic script:

function runAllQualityMetrics(param, rawData, savePath)
% Hundreds of lines of code doing many different things
(...)
end

Create a modular pipeline that separates each quality metric into a different function:

function qMetric = runAllQualityMetrics(param, rawData, savePath)
nUnits = length(rawData);
for iUnit = 1:nUnits
% step 1: calculate percentage spikes missing
qMetric.percSpikesMissing(iUnit) = bc.qm.percSpikesMissing(param, rawData);
% step 2: calculate fraction refractory period violations
qMetric.fractionRPviolations(iUnit) = bc.qm.fractionRPviolations(param, rawData);
% step 3: calculate presence ratio
qMetric.presenceRatio(iUnit) = bc.qm.presenceRatio(param, rawData);
(...)
% step n: calculate distance metrics
qMetric.distanceMetric(iUnit) = bc.qm.getDistanceMetric(param, rawData);
end
bc.qm.saveQMetrics(qMetric, savePath)
end

This structure allows for easy modification of individual steps or addition of new steps without affecting the entire pipeline.

In addition, this structure allows us to define new parameters easily that can then modify the behavior of the subfunctions. For instance we can add different methods (such as adding the ‘gaussian’ option below) without changing how any of the functions are called!

param.percSpikesMissingMethod = 'gaussian';
qMetric.percSpikesMissing(iUnit) = bc.qm.percSpikesMissing(param, rawData);

and then, inside the function:

function percSpikesMissing = percSpikesMissing(param, rawData);
if param.percSpikesMissingMethod == 'gaussian'
(...)
else
(...)
end
end

3. Hide complexity

Expose only what’s necessary to use a module or function, hiding the complex implementation details. Use abstraction layers to separate interface from implementation, providing clear and concise public APIs while keeping complex logic private. This approach not only makes your software easier to use but also allows you to refactor and optimize internal implementations without affecting users of your code.

Example: Complex algorithm with a simple interface

For instance, in bombcell there are many parameters. When we run the main script that calls all quality metrics, we also want to ensure all parameters are present and are in a correct format.

function qMetric = runAllQualityMetrics(param, rawData, savePath)
% Complex input validation that is hidden to the user
param_complete = bc.qm.checkParameterFields(param);

% Core function that calcvulates all quality metrics
nUnits = length(rawData);

for iUnit = 1:nUnits
% steps 1 to n
(...)
end

end

Users of this function don’t need to know about the input validation or other complex calculations. They just need to provide input and options.

4. Write clear code

Clear code reduces the need for extensive documentation and makes your software more accessible to collaborators. Use descriptive and consistent variable names throughout your codebase. When dealing with specific quantities, consider adding units to variable names (e.g., ‘time_ms’ for milliseconds) to improve clarity. You can add comments to explain non-obvious logic and to add general outlines of the steps in your code. Following consistent coding style and formatting guidelines across your project also contributes to overall clarity.

Example: Improving clarity in a data processing function

Instead of an entirely mysterious function

function [ns, sr] = ns(st, t)
ns = numel(st);
sr = ns/t;

Add more descriptive variable and function names and add function headers:

function [nSpikes, spikeRate] = numberSpikes(theseSpikeTimes, totalTime_s)
% Count the number of spikes for the current unit
% ------
% Inputs
% ------
% theseSpikeTimes: [nSpikesforThisUnit × 1 double vector] of time in seconds of each of the unit's spikes.
% totalTime_s: [double] of the total recording time, in seconds.
% ------
% Outputs
% ------
% nSpikes: [double] number of spikes for current unit.
% spikeRate_s : [double] spiking rare for current unit, in seconds.
% ------
nSpikes = numel(theseSpikeTimes);
spikeRate_s = nSpikes/totalTime_s;
end


5. Design for testing

Incorporate testing into your design process from the beginning. This not only catches bugs early but also encourages modular, well-defined components.

Example: Testable design for a data analysis function

For the simple ‘numberSpikes’ function we define above, we can have a few tests to cover various scenarios and edge cases to ensure the function works correctly. For instance, we can test a normal case with a few spikes and an empty spike times input.

function testNormalCase(testCase)
theseSpikeTimes = [0.1, 0.2, 0.3, 0.4, 0.5]; totalTime_s = 1;
[nSpikes, spikeRate] = numberSpikes(theseSpikeTimes, totalTime_s);
verifyEqual(testCase, nSpikes, 5, 'Number of spikes should be 5');
verifyEqual(testCase, spikeRate, 5, 'Spike rate should be 5 Hz');
end

function testEmptySpikeTimes(testCase)
theseSpikeTimes = [];
totalTime_s = 1;
[nSpikes, spikeRate] = numberSpikes(theseSpikeTimes, totalTime_s);
verifyEqual(testCase, nSpikes, 0, 'Number of spikes should be 0 for empty input');
verifyEqual(testCase, spikeRate, 0, 'Spike rate should be 0 for empty input');
end

This design allows for easy unit testing of individual components of the analysis pipeline.

Part 2: Open Source Best Practices for Academia

While using version control and having a README, documentation, license, and contribution guidelines are essential, I have found that these practices have the most impact:

Example Scripts and Toy Data

I have found that the most useful thing you can provide with your software are example scripts, and even better, provide toy data that loads in your example script. Users can then quickly test your software and see how to use it on their own data — and are then more likely to adopt it. If possible, package the example scripts in Jupyter notebooks/MATLAB live scripts (or equivalent) demonstrating key use cases. In bombcell, we provide a small dataset (Bombcell Toy Data on GitHub) and a MATLAB live script that runs bombcell on this small toy dataset (Getting Started with Bombcell on GitHub). 

Issue-Driven Improvement

To manage user feedback effectively, enforce the use of an issue tracker (like GitHub Issues) for all communications. This approach ensures that other users can benefit from conversations and reduces repetitive work. When addressing questions or bugs, consider if there are ways to improve documentation or add safeguards to prevent similar issues in the future. This iterative process leads to more robust and intuitive software.

Citing

Make your software citable quickly. Before (or instead) of publishing, you can generate a citable DOI using software like Zenodo. Consider also publishing in the Journal of Open Source Software (JOSS) for light peer review. Clearly outline how users should cite your software in their publications to ensure proper recognition of your work.

Conclusion

These practices can help create popular, user-friendly, and robust academic software. Remember that good software design is an iterative process, and continuously seeking feedback and improving your codebase (and sometimes entirely rewriting/refactoring parts) will lead to more robust code.

To go deeper into principles of software design, I highly recommend reading “A Philosophy of Software Design” by John Ousterhout or “The Good Research Code Handbook” by Patrick J. Mineault.

Get involved! 

The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Join our mailing list, and follow us on X, formerly Twitter and LinkedIn, to stay connected for updates, events, and opportunities.

UCL Open Science & Scholarship Awards – Update from Mike and Gesche!

By Kirsty, on 21 August 2024

As part of our work at the Office this year, we’ve made it a priority to stay connected with all of our award winners. Some of them shared their experiences during our conference, and we’re already well on our way to planning another exciting Awards ceremony for this year’s winners!

You can apply now for the UCL Open Science & Scholarship Awards 2024 to celebrate UCL students and staff who are advancing and promoting open science and scholarship. The awards are open to all UCL students, PhD candidates, professional services, and academic staff across all disciplines. There’s still time to submit your applications and nominations in all categories— the deadline is 1 September!

To give you some inspiration for what’s possible in open science, Mike Fell has given us an update on the work that he and Gesche have done since receiving their award last year:

In autumn last year, we were surprised and really happy to hear we’d received the first UCL Open Scholarship Awards. Even more so when we heard at the ceremony about the great projects that others at UCL are doing in this space.

The award was for work we’d done (together with PhD colleague Nicole Watson) to improve transparency, reproducibility, and quality (TReQ) or research in applied multidisciplinary areas like energy. This included producing videos, writing papers, and delivering teaching and related resources.

Of course, it’s nice for initiatives you’ve been involved in to be recognized. But even better have been some of the doors this recognition has helped to open. Shortly after getting the award, we were invited to write an opinion piece for PLOS Climate on the role of open science in addressing the climate crisis. We also engaged with leadership at the Center for Open Science.

More broadly – although it’s always hard to draw direct connections – we feel the award has had career benefits. Gesche was recently appointed Professor of Environment & Human Health at University of Exeter, and Director the European Centre for Environment and Human Health. As well as highlighting her work on open science, and the award, in her application, this now provides an opportunity to spread the work further beyond the bounds of UCL and our existing research projects.

There’s still a lot to do, however. While teaching about open science is now a standard part of the curriculum for graduate students in our UCL department (and Gesche planning this for the ECEHH too), we don’t have a sense that this is common in energy research, other applied research fields, and education more broadly. It’s still quite rare to see tools like pre-analysis plans, reporting guidelines, and even preprints employed in energy research.

A new research centre we are both involved in, the UKRI Energy Demand Research Centre, has been up and running for a year, and with lots of the setup stage now complete and staff in place, we hope to pick up a strand of work in this area. Gesche is the data champion for the Equity theme of that centre. The new focus must be on how to better socialize open research practices and make them more a part of the culture of doing energy research. We look forward to continuing to work with UCL Open Science in achieving that goal.

Get involved!

The UCL Office for Open Science and Scholarship invites you to contribute to the open science and scholarship movement. Join our mailing list, and follow us on X, formerly Twitter and LinkedIn, to stay connected for updates, events, and opportunities.

Copyright and AI, Part 2: Perceived Challenges, Suggested Approaches and the Role of Copyright literacy

By Rafael, on 15 August 2024

Guest post by Christine Daoutis (UCL), Alex Fenlon (University of Birmingham) and Erica Levi (Coventry University).

This blog post is part of a collaborative series between the UCL Office for Open Science and Scholarship and the UCL Copyright team exploring important aspects of copyright and its implications for open research and scholarship. 

An artist’s illustration of AI by Tim West. Photo by Google DeepMind from Pexels.

A previous post outlined copyright-related questions when creating GenAI materials—questions related to ownership, protection/originality, and infringement when using GenAI. The post discussed how answers to these questions are not straightforward, largely depend on what is at stake and for whom, and are constantly shaped by court cases as they develop.

What does this uncertainty mean for students, academics, and researchers who use GenAI and, crucially, for those in roles that support them? To what extent does GenAI create new challenges, and to what extent are these uncertainties inherent in working with copyright? How can we draw on existing expertise to support and educate on using GenAI, and what new skills do we need to develop?

In this post, we summarise a discussion we led as part of our workshop for library and research support professionals at the Research Libraries UK (RLUK) annual conference in March 2024. This year’s conference title was New Frontiers: The Expanding Scope of the Modern Research Library. Unsurprisingly, when considering the expanding scope of libraries in supporting research, GenAI is one of the first things that comes to mind.

Our 16 workshop participants came from various roles, research institutions, and backgrounds. What they had in common was an appetite to understand and support copyright in the new context of AI, and a collective body of expertise that, as we will see, is very useful when tackling copyright questions in a novel context. The workshop consisted of presentations and small group discussions built around the key themes outlined below.

Perceived Challenges and Opportunities
Does the research library community overall welcome GenAI? It is undoubtedly viewed as a way to make scholarship easier and faster, offering practical solutions—for example, supporting literature reviews or facilitating draft writing by non-English speakers. Beyond that, several participants see an opportunity to experiment, perhaps becoming less risk-averse, and welcome new tools that can make research more efficient in new and unpredictable ways.

However, concerns outweigh the perceived benefits. It was repeatedly mentioned that there is a need for more transparent, reliable, sustainable, and equitable tools before adopting them in research. Crucially, users need to ask themselves what exactly they are doing when using GenAI, their intention, what sources are being used, and how reliable the outputs are.

GenAI’s concerns over copyright were seen as an opportunity to place copyright literacy at the forefront. The need for new guidance is evident, particularly around the use of different tools with varying terms and conditions, and it is also perceived as an opportunity to revive and communicate existing copyright principles in a new light.

Suggested Solutions
One of the main aims of the workshop was to address challenges imposed by GenAI. Participants were very active in putting forward ideas but expressed concerns and frustration. For example, they questioned the feasibility of shaping policy and processes when the tools themselves constantly evolve, when there is very little transparency around the sources used, and when it is challenging to reach agreement even on essential concepts. Debates on whether ‘copying’ is taking place, whether an output is a derivative of a copyrighted work, and even whether an output is protected are bound to limit the guidance we develop.

Drawing from Existing Skills and Expertise
At the same time, it was acknowledged that copyright practitioners already have expertise, guidance, and educational resources relevant to questions about GenAI and copyright. While new guidance and training are necessary, the community can draw from a wealth of resources to tackle questions that arise while using GenAI. Information literacy principles should still apply to GenAI. Perhaps the copyright knowledge and support are already available; what is missing is a thorough understanding of the new technologies, their strengths, and limitations to apply existing knowledge to new scenarios. This is where the need for collaboration arises.

Working Together
To ensure that GenAI is used ethically and creatively, the community needs to work collaboratively—with providers, creators, and users of those tools. By sharing everyday practices, decisions, guidance, and processes will be informed and shaped. It is also important to acknowledge that the onus is not just on the copyright practitioners to understand the tools but also on the developers to make them transparent and reliable. Once the models become more transparent, it should be possible to support researchers better. This is even more crucial in supporting text and data mining (TDM) practices—critical in many research areas—to limit further restrictions following the implementation of AI models.

Magic Changes
With so much excitement around AI, we felt we should ask the group to identify the one magic change that would help remove most of the concerns. Interestingly, the consensus was that clarity around the sources and processes used by GenAI models is essential. How do the models come up with their answers and outputs? Is it possible to have clearer information about the sources’ provenance and the way the models are trained, and can this inform how authorship is established? And what criteria should be put in place to ensure the models are controlled and reliable?

This brings the matter back to the need for GenAI models to be regulated—a challenging but necessary magic change that would help us develop our processes and guidance with much more confidence.

Concluding Remarks
While the community of practitioners waits for decisions and regulations that will frame their approach, it is within their power to continue to support copyright literacy, referring to new and exciting GenAI cases. Not only do those add interest, but they also highlight an old truth about copyright, namely, that copyright-related decisions always come with a degree of uncertainty, risk, and awareness of conflicting interests.

About the authors 

Christine Daoutis is the UCL Copyright Support Officer at UCL. Christine provides support, advice and training on copyright as it applies to learning, teaching and research activities, with a focus on open science practices. Resources created by Christine include the UCL Copyright Essentials tutorial and the UCL Copyright and Your Teaching online tutorial.

Alex Fenlon is the Head of Copyright and Licensing within Libraries and Learning Resources at the University of Birmingham. Alex and his team provide advice and guidance on copyright matters, including text, data mining, and AI, to ensure that all law and practice are understood by all.

Erica Levi is the Digital repository and Copyright Lead at Coventry University. Erica has created various resources to increase awareness of copyright law and open access through gamification. Her resources are available on her website.

Get involved!

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

UCL, ORCID, and RPS, oh my!

By Kirsty, on 25 July 2024

Ten years on, most of our readers will have heard of ORCID by now in one context or another. Many publishers now ask you to include an ORCID when you submit a journal article, and increasing numbers of funders, including Wellcome, require the use of an ORCID when applying for funding. The new UKRI funding service will also require ORCIDs for at least PIs.

In case you don’t know much about ORCID here are the facts:

• ORCID is a free, unique, persistent identifier for individuals to use as they engage in research, scholarship and innovation activities. ​
• Its core purpose is to distinguish individuals from one another, this means that people with identical names, or who have changed their name can be accurately attributed works.
• It also provides a portable and open profile which can collate and display your works including recognition for grant application review and peer review activity.
• ORCID profiles are independent of any institution and can remain with you throughout your career.
• This open profile also facilitates auto-population of manuscript submission and grant application systems, reducing duplication of effort.​
• The ORCID profile can also populate itself using in-built tools that pull data from the DOI registry and various publishers and aggregators.

The use of an ORCID can also make it easier to record your outputs in RPS. Connecting your ORCID to RPS can make the outputs identified more accurate and makes it much easier for you to comply with OA mandates including for the REF as well as keep your UCL profile up to date. It is also possible to set it up to automatically push data to your ORCID profile, so that when you record a publication in RPS, it is automatically sent to your ORCID profile.

There are two options for connecting an ORCID to RPS:

1. A ‘read’ connection means that RPS will find records that belong to you, using your ORCID iD, and claim them to your RPS record. This means that, unlike records that RPS finds using your name and institution, you don’t need to claim these records manually.
2. A ‘read and write’ connection will both claim publications that can be matched by ORCID iD and send publications to your ORCID record. This avoids duplication of effort when publications need to be recorded manually.

We recommend using the ‘read and write’ version of the connector as this will keep both your RPS record, UCL Profile and ORCID in sync. Take a look at our instructions on the website or download the PDF guide.​ Nearly 70% of UCL research staff have connected their ORCID to RPS but less than 40% are taking advantage of read and write. To take advantage of the full functionality, reconnect your ORCID to RPS today!

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!

From Policy to Practice: UCL Open Science Conference 2024

By Kirsty, on 11 July 2024

Last month, we hosted our 4th UCL Open Science Conference! This year, we focused inward to showcase the innovative and collaborative work of our UCL researchers in our first UCL community-centered conference. We were excited to present a strong lineup of speakers, projects, and posters dedicated to advancing open science and scholarship. The conference was a great success, with nearly 80 registrants and an engaged online audience.

If you missed any sessions or want to revisit the presentations, you can find highlights, recordings, and posters from the event below.

Session 1 – Celebrating Our Open Researchers

The conference began with a celebration of the inaugural winners of the Open Science & Scholarship Awards, recognizing researchers who have significantly contributed to open science. This session also opened nominations for next year’s awards.

Access the full recording of the session 1 on MediaCentral.

Session 2: Policies and Practice

Katherine Welch introduced an innovative approach to policy development through collaborative mosaic-making. Ilan Kelman discussed the ethical limits of open science. He reminded us of the challenges and considerations when opening up research and data to the public. David Perez Suarez introduced the concept of an Open Source Programme Office (OSPO) at UCL and, with Sam Ahern, showcased the Centre of Advanced Research Computing’s unique approach to creating and sharing open educational resources.

Access the full recording of the session 2 on MediaCentral.

Session 3: Enabling Open Science and Scholarship at UCL

This session introduced new and updated services and systems at UCL designed to support open science and scholarship. Highlights included UCL Profiles, Open Science Case Studies, the UCL Press Open Textbooks Project, UCL Citizen Science Academy, and the Open@UCL Newsletter.

Access the full recording of the session 3 on MediaCentral.

Session 4: Research Projects and Collaborations

This session featured presentations on cutting-edge research projects and collaborations transforming scholarly communication and advancing scientific integrity. Klaus Abels discussed the journey of flipping a subscription journal to diamond open-access. Banaz Jalil and Michael Heinrich presented the ConPhyMP guidelines for chemical analysis of medicinal plant extracts, improving healthcare research. Francisco Duran explored social and cultural barriers to data sharing and the role of identity and epistemic virtues in creating transparent and equitable research environments.

Access the full recording of the session 4 on Media Central.

Posters and Networking:

We also hosted a Poster Session and Networking event where attendees explored a variety of posters showcasing ongoing research across UCL’s disciplines, accompanied by drinks and snacks. This interactive session provided a platform for researchers to present their work, exchange ideas, and foster collaborations within and beyond the UCL community.

Participants engaged directly with presenters, learning about research findings and discussing potential synergies for future projects. Themes covered by the posters included innovative approaches to public engagement by UCL’s Institute of Global Prosperity and Citizen Science Academy, as well as discussions on the balance between open access and data security in the digital age.

Explore all the posters presented at the UCL Open Science Conference 2024 on the UCL Research Data Repository. This collection is under construction and will continue to grow.

Reminder for Attendees – Feedback

For those who attended, please take a minute to complete our feedback form. Your input is very important to improve future conferences. We would appreciate your thoughts and suggestions.

A Huge Thank You!

Thank you to everyone who joined us for the UCL Open Science Conference 2024. Your participation and enthusiasm made this event a great success. We appreciate your commitment to advancing open science and scholarship across UCL and beyond, and we look forward to seeing the impact of your work in the years to come.

Please watch the sessions and share your feedback with us. Your insights are invaluable in shaping future events and supporting the open science community.

We look forward to seeing you at next year’s conference!

Spotlight on Ben Watson: Champion of Digital Accessibility at UCL 

By Rafael, on 8 July 2024

This is the first instalment of our profile series, and we shine a light on Ben Watson, UCL’s Head of Digital Accessibility. Ben’s journey from teaching to digital accessibility shows his unwavering dedication to inclusivity. He works hard with the Digital Accessibility Team and together, they put in place and advocate for accessible digital practices. Below are the highlights of his conversation with the UCL Office for Open Science and Scholarship. Here, he shares his story and vision to make UCL more accessible.

Ben Watson

Current Role

Ben Watson describes his role as putting in ‘ramps and lifts’ to information. He underscores the need of making digital resources not only available but accessible to all. ‘My role is about ensuring that all UCL systems and content, and the way we design, deliver, and share information, addresses potential barriers. If digital resources aren’t accessible to everyone, their full potential remains untapped’. 

Journey to Digital Accessibility

Ben’s path began with a background in teaching and librarianship. Early in his career, he worked at a school for blind and partially sighted students, where he discovered the transformative power of digital information. This experience ignited his passion for advocating better e-resources and focusing on accessible learning design. ‘I’ve always been fascinated by how people consume information. As a teacher, I saw how digital information should be the answer to many accessibility issues’.

Teaching Experience and Advocacy 

His teaching background provided him with insights into diverse learning styles and the adverse impact of inaccessible materials. Now at UCL, the Digital Accessibility team assists research and teaching staff in meeting accessibility standards, promoting the idea that highly accessible digital experiences can only benefit students, staff, and institutions. ‘One of the really lovely things about digital accessibility and promoting it is that genuinely it’s one of those things that benefits everyone’.

Addressing Challenges and Organisational Change 

Ben acknowledges the complexities of ensuring digital accessibility at a large institution like UCL. He emphasises the need to influence content creators to prioritise accessibility and integrate inclusive design from the outset. ‘To make UCL more digitally accessible, we must influence the entire information cycle. We need to support content creators to excel at what they are experts in while giving them confidence to deliver this accessibly. UCL can lead by example in many areas, including accessibility’. 

Progress, Not Perfection 

Ben champions the idea of progress over perfection in the evolving field of digital accessibility. ‘I always talk about progress, not perfection. In such a dynamic landscape, expecting 100% perfection is unrealistic, but we can certainly achieve significant, long-lasting positive progress’ 

Simple Steps for Digital Accessibility

Making digital content accessible can be straightforward with built-in tools in software applications such as Microsoft’s Accessibility Checker. Ben also highlights the importance of structured headings, alternative text descriptions, and other features to make documents navigable for all users. ‘Simple steps like using headings, alternative text and accessibility checkers can greatly enhance accessibility. UCL Accessibility pages offer extensive guidance on this to support UCL staff’

Accessibility and Open Science: Benefits for All

We asked Ben how accessibility principles can advance Open Science and Scholarship. He advocates for making research accessible to everyone. This involves adding accessibility standards to open science publishing. ‘Publishers need to meet these standards for Open Access to reach its full potential. This helps everyone by boosting the reach and impact of research.’ Challenges exist, but the benefits of accessibility are broad. Accessibility improves research impact, openness, and discoverability. ‘At the end of the day, this isn’t just about legal mandates for public sector bodies, although that’s a compelling reason. It’s about fulfilling ethical obligations to ensure that everyone can fully engage. Why should we prevent anyone from being inspired and affected by our work? With some effort, but not a huge amount, we could make our work future-proof and accessible to everyone’

European Accessibility Regulations 

Ben is enthusiastic about the European Accessibility Act, which extends obligations to commercial suppliers beyond existing legislation. He views this as a significant advancement for the education sector, making it easier to ensure accessibility compliance from the design stage. ‘The European Accessibility Act is a powerful addition to existing legislation. It mandates accessibility by default, simplifying our work to ensure compliance’

Proactive Accessibility and Legacy Content  

It’s much more challenging to retrofit accessibility into already published content, that’s why proactive measures are key. ‘It’s much more difficult to make something accessible after it’s been published. UCL collaborates with partners like the Royal National Institute for Blind People to review legacy content. We aim to integrate accessibility from the start and have clear processes for addressing older content’

Envisioning the Future 

Ben hopes for a future where digital accessibility is an integral part of everyday life and education. He highlights UCL’s research initiatives, like the Global Disability Innovation Hub, and the work of the Institute of Education at UCL (with telepresence robot projects like the one led by Jennifer Rode)  as examples of a commitment to global outreach and inclusive design. ‘I’d love the field of digital accessibility to become everyone’s business as usual. It should be included in standard training, teacher qualifications, and even the school curriculum because it’s really that important’

Accessibility is Not Just About Compliance

We should advocate for a holistic approach to accessibility, considering diverse needs, including those of neurodiverse individuals. Ben stresses the importance of inclusive design in education, promoting flexible assessment methods and delivery modes. ‘Accessibility isn’t just about compliance; it’s about creating inclusive experiences that anticipate diverse needs. By embedding accessibility into every aspect of education, we enable everyone to reach their full potential’

Librarians are Awesome 

Ben’s transition from librarianship to digital accessibility was one of the focal points of his career. Working as a librarian provided him with a unique perspective on accessibility and understanding on how people engage with information. ‘I think about information like a librarian—considering how people find and use it. This perspective is essential for ensuring digital content is accessible’. As a librarian, his involvement in e-book accessibility campaigns solidified his dedication to making digital resources accessible to all. ‘Librarians play a crucial, often underappreciated role in advocating for accessible information. It’s no wonder Michael Moore calls them the most important public servants in a democracy’

Accessibility Can Make a Difference 

He explains that his commitment to accessibility comes from a deep belief in equitable information access. He is driven by a desire to remove barriers to inclusion and citizenship. ‘I’ve seen firsthand the impact of inaccessible information—it can hinder potential and make people feel excluded. My motivation is to remove barriers and ensure everyone feels included and respected. Information is vital for education and broader citizenship. Accessible design, is good design, and ensures no one is excluded and that information is adaptable for new technologies like AI’.

Inspirations  

Ben draws inspiration from key figures in disability studies, such as British sociologist and activist Mike Oliver, a founding theorist of the social model of disability. ‘Meeting Professor Mike Oliver at the University of Kent profoundly influenced my work. His theories on disability have been foundational.’ He also acknowledges the contributions of colleagues like Kirsty Wallis in raising accessibility awareness in open science. ‘Kirsty’s work in promoting accessibility in open science has been outstanding.’

Passions  

Outside of his professional life, Ben takes greater pride in his daughters’ kindness: ‘I’m incredibly proud of my two daughters. They are kind, caring, and thoughtful young people who genuinely put the feelings of others before their own’. He also has a passion that takes him on quite a ride: ‘I love motorbikes. Riding them, fixing them, and generally thinking about them!’

UCL’s Vision: We Should Lead by Example  

Ben advocates for UCL to be a leader in digital accessibility and inclusive design. ‘UCL can lead by example, ensuring accessibility is integral to everything we do. Accessibility is not extra work; it’s about completing what was left unfinished. Embracing this ethos across UCL would ensure no work is deemed complete until it’s accessible to all’. 

UCL Digital Accessibility Team.

Ben Watson’s work at UCL shows he is strongly committed to making information and education open and inclusive. He invites everyone to embrace inclusive design at UCL with the Digital Accessibility Team. Through a collaborative effort, we can pave the way for a better future.  

Follow Ben’s lead. Integrate accessibility into your work by following the steps provided on the UCL Accessibility Pages. You could also attend a Digital Skills training course, or join the Accessibility Champions Network. 

 For more information or help, check out the Digital Accessibility Services, or contact the Digital Accessibility Team. 

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!

UCL Discovery reaches 50 million downloads!

By Rafael, on 27 June 2024

Guest Post by Dominic Allington-Smith (Open Access Publications Manager)

Photo by Erwan Hesry on Unsplash

UCL Publications Board and the Open Access Team are delighted to announce that on Monday 24 June, UCL’s institutional repository, UCL Discovery, reached the milestone of 50 million downloads! UCL Discovery is UCL’s open access repository, showcasing and providing access to UCL research outputs from all UCL disciplines. UCL authors currently deposit around 1,675 outputs in the repository every month (average figure for the current academic year).

The 50 millionth download was of the paper ‘Replenishing IRAK-M expression in retinal pigment epithelium attenuates outer retinal degeneration’ originally published in Science Translational Medicine by a team of researchers including UCL co-lead author Professor Andrew Dick.  This paper found that increasing the levels of a key protein in the cells at the back of the eye could help protect against the age-related macular degeneration, the leading cause of vision loss among older adults.

UCL Discovery hosts over 178,500 open access publications at the time of writing, comprising mostly self-archived copies of research outputs published elsewhere to bypass publisher paywalls, but also including doctoral and research master’s theses (contemporary submissions and historic digitisations), and books published by UCL Press.  This variety of resources is displayed when viewing the highest-downloaded publication within the UCL hierarchy:

• Faculty of Arts and Humanities: A Connected Curriculum for Higher Education (UCL Press book, 2017)
• Faculty of Laws: Confessions, illegally/improperly obtained evidence and entrapment under the Police and Criminal Evidence Act 1984: changing judicial and public attitudes to the police and criminal investigations (thesis, 1999)
• School of Slavonic and Eastern European Studies: The Gesta Hungarorum of Anonymus, the Anonymous Notary of King Béla: A Translation (journal article, 2009)
• Faculty of Social and Historical Sciences: How the World Changed Social Media (UCL Press book, 2016)
• Faculty of the Built Environment (Bartlett): Why are most buildings rectangular? (journal article, 2006)
• Faculty of Engineering Sciences: Semi-structured qualitative studies (book chapter, 2013)
• Faculty of Maths and Physical Sciences: The Traditional Four Steps Transportation Modeling Using a Simplified Transport Network: A Case Study of Dhaka City, Bangladesh (journal article, 2012)
• Faculty of Brain Sciences: What is mentalization? The concept and its foundations in developmental research (book chapter, 2012)
• Faculty of Life Sciences: Evaluation of the scale, causes and costs of waste medicines. Report of DH funded national project (report, 2010)
• Faculty of Medical Sciences: Textbook of Plastic and Reconstructive Surgery (UCL Press book, 2016)
• Faculty of Population Health Sciences: Food, Nutrition, Physical Activity, and the Prevention of Cancer: a Global Perspective (report, 2006)
• Institute of Education: Teaching at a distance in a digital age: perspectives from the Philippines (thesis, 2013)

This amazing milestone shows the scope and reach that sharing research through UCL Discovery has. There are a number of ways you can share your research at UCL, and we encourage you to continue sharing your research publications via UCL RPS and Profiles. Additionally, consider sharing other types of outputs such as data, code and software to further enhance the visibility and reproducibility of your work. The Research Data Management team maintain a guide on best practice for software sustainability, preservation and sharing, and can give further support to UCL researchers as required.

Congratulations to everyone involved in reaching this incredible milestone, and let’s continue to push the boundaries of open access and research sharing at UCL!

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!

Copyright and AI, Part 1: How Does Copyright Apply to AI-Generated Works?

By Rafael, on 21 June 2024

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.

Photo by Google DeepMind.

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.

Image Credit: Kris Kashtanova using Midjourney AI, Public domain, via Wikimedia Commons.

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!

UCL Open Science & Scholarship Conference 2024: Programme Now Available!

By Rafael, on 13 June 2024

With less than a week until this year’s UCL Open Science Conference, anticipation is building! We are thrilled to announce that the programme for the UCL Open Science & Scholarship Conference 2024 is now ready. Scheduled for Thursday, June 20, 2024, from 1:00 pm to 5:00 pm BST, both onsite at UCL and online, this year’s conference promises to be an exciting opportunity to explore how the UCL community is leading Open Science and Scholarship initiatives across the university and beyond.

Programme Outline:

1:00-1:05 pm
Welcome and Introductions
Join us as we kick off the conference with a warm welcome and set the stage for the afternoon.

1:05-1:45 pm
Session 1: Celebrating our Open Researchers
Learn about the outstanding contributions of our Open Science champions and their work recognised at the UCL Open Science & Scholarship Awards last year.

1:45-2:45 pm
Session 2: Policies and Practice
Explore discussions on policy development and ethical considerations in Open Science, including talks on collaborative policy-making and the role of Open Source Programme Offices (OSPOs).

2:45-3:15 pm
Coffee Break
Network and engage with our fellow attendees over coffee, tea, and biscuits.

3:15-4:00 pm
Session 3: Enabling Open Science and Scholarship at UCL
Check out services and initiatives that empower UCL researchers to embrace Open Science, including updates on UCL Profiles, UCL Citizen Science Academy, and Open Science Case Studies.

4:00-4:45 pm
Session 4: Research Projects and Collaborations
Discover cutting-edge research projects and collaborations across UCL, including case studies involving the transition to Open Access publishing, reproducible research using medicinal plants, and social and cultural barriers to data sharing.

4:45-5:00 pm
Summary and Close of Main Conference
Reflect on key insights from the day’s discussions and wrap up the main conference.

5:00-6:30 pm
Evening Session: Poster Viewing and Networking Event
Engage with our presenters and attendees over drinks and nibbles, while exploring posters showcasing research and discussions in Open Science and Scholarship through diverse perspectives.

For the complete programme details, please access the full document uploaded on the UCL Research Data Repository, or access the QR code.

Join us – Tickets are still available!
Whether you’re attending in person or joining us virtually, we invite you to participate in discussions that shape the future of Open Science and Scholarship at UCL. Sales will close on Monday. Secure your spot now! Register here.

Thank you!
Thank you once more to everyone who submitted their ideas to the Call for Papers and Posters. We received brilliant contributions and are grateful for our packed programme of insightful discussions and projects from our community.

We look forward to welcoming you to the UCL Open Science & Scholarship Conference 2024!

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!

Understanding Research Metrics: UCL’s New LibGuide

By Rafael, on 29 May 2024

Guest post by Andrew Gray, UCL Bibliometrics Support Officer

The UCL Research Support team has recently launched a comprehensive new LibGuide on Research Metrics. This resource covers a range of topics, from how to use and understand bibliometrics (citation metrics and altmetrics) to guidance on specific tools and advice on handling publications data. Learn more about this guide to enhance your research impact and better understand the world of research metrics!

Image by Calvinius (own work), CC BY-SA 3.0

Bibliometrics

The core of the new guide is focusing on guidance for using and understanding research metrics, such as bibliometrics, citation metrics, and altmetrics. It explains how to access citation counts through Scopus and Web of Science, and more complex normalised metrics through InCites. It also gives guidance on how to best interpret and understand those metrics, and advice on metrics to avoid using. The guide also covers the UCL Bibliometrics Policy, which governs the use of bibliometric data for internal assessments at UCL, and sets some limits on what should be used.

Guidance for Tools

Within the LibGuide, you will also find guidance pages for how to use specialised services like InCites, Altmetric, and Overton to measure research impact. Additionally, the guide offers advice on using other tools that UCL does not subscribe to but may be beneficial for research support. This includes three freely available large bibliographic databases—Lens, Dimensions, and OpenAlex—which provide broader coverage than Web of Science and Scopus. It also outlines how to use a range of tools for citation-network based searching like Research Rabbit, Connected Papers, and Litmaps, as well as modern AI-supported search and summarising tools such as Scite, Keenious, and Consensus.

These are of course not the only tools available – especially with AI-supported tools, there are frequently tools being released – but these are ones we have been asked to investigate by students and researchers. If you would like feedback on another tool you are considering using, please get in touch.

Publications data

The LibGuide also addresses broader questions about using publications data. It outlines how to download publication and metrics datasets from Web of Science, Scopus, InCites, and Altmetric, and gives some guidance on how to link datasets from different sources together. Learn more about using publications data.

Additionally, the guide also explains how best to interpret data drawn from UCL-specific sources such as RPS, data ensuring you can make the most of the data available to you.

This new LibGuide is an important resource for anyone looking to expand their understanding of research metrics and manage their publications data. Visit the guide today to explore these tools and resources in detail.

Further support

We offer regular online or in-person training sessions as part of the Library Skills program. Please see the Library Skills calendar for dates and bookings. There are also three self-paced online sessions available through the Library Skills Moodle.

For any enquiries about bibliometrics, please contact us on bibliometrics@ucl.ac.uk 

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!