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Workshop on Open-Source Software for Surgical Technologies

By m.xochicale, on 20 December 2024

To champion the creation of sustainable, robust, and equitable digital healthcare systems that prevent the perpetuation of healthcare inequalities, ARC researchers took the lead in organising the second workshop on Open-Source Software for Surgical Technologies at the Hamlyn Symposium on Medical Robotics on June 28th, 2024.

The workshop focused on a key question: how can we transform open-source software libraries into sustainable, long-term supported tools that are translatable to clinical practice? To address this, the event brought together engineers, researchers, and clinicians from academia and industry to present their work, discuss current progress, challenges, and trends, and lay the foundation for building a collaborative community around Open-Source Software Innovations in Surgical, Medical and AI Technologies.

In this post, we are excited to share recordings of our exceptional lineup of speakers and celebrate the poster awardees from the workshop, along with Zenodo links to other posters. The talks and posters spanned a variety of topics, including certification, commercialisation, and case studies of open-source software in research and industry scenarios. This workshop highlighted the profound impact of open-source software in advancing surgical technologies and medical innovation.

Speakers

Watch all the recorded talks on this YouTube Playlist.

️Poster awardees
Congratulations to all the awardees for their outstanding contributions to advancing innovation in surgical technologies!

Best Poster Award
Martin Huber et al. from King’s College London “LBR-Stack: ROS 2 and Python Integration of KUKA FRI for Med and IIWA Robots”
GitHub: https://github.com/lbr-stack/lbr_fri_ros2_stack/
arXiv: https://arxiv.org/abs/2311.12709

Runner-Up Awards (Three-Way Tie)

  • Keisuke Ueda et al. from Medical DATAWAY “Automated Surgical Report Generation Using In-context Learning with Scene Labels from Surgical Videos” Poster in Zenodo https://zenodo.org/records/12518729
  • Mikel De Iturrate Reyzabal et al. from King’s College London “PyModalSurgical. An image-space modal analysis library for surgical videos: generating haptic and visual feedback” Poster in Zenodo: https://zenodo.org/records/12204075​
  • Ewald Ury et al. from KU LEUVEN “Markerless Augmented Reality Guidance System for Maxillofacial Surgery”

See other posters Peter Kazanzides et al., dVRK-Si: The Next Generation da Vinci Research Kit, Reza Haqshenas et al., OptimUS: an open-source fast full-wave solver for calculating acoustic wave propagation with applications in biomedical ultrasound.

Get in touch

We can’t wait to see you again next year!
Warm regards, Eva, Stephen, & Miguel

 

 

 

#HSMR24 #HamlynSymposium2024 #Healthcare #OpenSource #ArtificialIntelligence #SurgTech #MedTech #AITech

Alignment of the Agile Manifesto to a Research Context

By Monika Byrne Svata, on 14 November 2024

This article proposes aligning the language of the original Agile Manifesto – written over 20 years ago, for software development in a commercial setting – with our current context of digital research projects involving research software engineering, data science, data stewardship, and research infrastructure development.

This work was inspired by discussion about the wording of the Agile Manifesto during the regular Agile Training for Research projects that we run in UCL’s Advanced Research Computing Centre (ARC) for senior staff in our Collaborations team. To gain wider input from colleagues we devoted two ARC “Collaboration Hour” sessions to this topic, with additional conversation held on Slack, some email input, and a period where a draft of this article was available for internal comment.

We hold that the core ideas behind Agile, such as responding to change, valuing people interactions, etc., are valid and beneficial in a research context. However, the specific expression of these may be able to be improved on – in true Agile fashion! Our aim is that this will make it easier to apply the Agile principles in the management of our Collaborations projects, by removing the cognitive dissonance caused by the language inspired by a different context. By publishing this article, we hope that others will see a similar benefit, and we invite feedback from the community.

 

The Original Agile Manifesto

It originated in February 2001 in a meeting of representatives from emerging ‘lightweight’ software development approaches in response to the need for an alternative to documentation driven, heavyweight software development processes.

Although there are many frameworks to aid the application of Agile approaches for particular settings, the manifesto emphasises that the change of culture within organisations and teams is the key element and the condition of the success of implementing Agile ways of working.

“While the Manifesto provides some specific ideas… there is a deeper theme of values based on trust and respect for each other and promoting organizational models based on people, collaboration, and building the types of organizational communities in which we would want to work.”

“So, in the final analysis, the meteoric rise of interest in – and sometimes tremendous criticism of – Agile Methodologies is about the mushy stuff of values and culture.”

For a fuller history, visit the Agile Manifesto website.

The original Agile Manifesto contains 4 Agile Values, and 12 Agile Principles.

Below we give the original text of each alongside our updated version and discuss the reasons for our proposed revisions.

 

 

Key Terms

Although the wording of each of the values and principles has been considered separately, to make sure that it reflects the best of both the original meaning and its application to research/academia, we found it useful to give an initial consideration and space for discussion to some of the repeated key terms and the reality of research projects.

 

Original wording Discussion about new wording
Customer ‘Customer’ implies negotiation and a zero-sum game, rather than a collaboration with a common goal. This also applies to the term ‘Client’.

‘End user’ is a specific term that might not correctly reflect the reality of a research project or correctly describe the collaborators.

‘Collaborators’, ‘our collaborators’, ‘all collaborators’ feel like the terms best describing this role.

Valuable software / Working Software Terms like ‘valuable software’, ‘working software’ or ‘digital artefacts’ are too limiting, as the outputs of collaborations projects are often other than software (e.g. research, teaching/education, service, etc.)

The suggested terms that felt acceptable included ‘desired outcome’, ‘academic output’, ‘the research’, ‘research outcome’.

Developers Research Technical Professionals – RTP
Business people Depending on the context of the individual principles, terms like ‘researchers’ or ‘domain experts’ felt appropriate.
Major current areas of pain for research projects The original context of the Agile Manifesto, expressed in the Agile Values, was that it was responding to the reality of rigid overplanning and over-documenting, where any change, learning, or other deviation from the original assumptions was seen as disruptive and a risk.

As the reality of research projects in 2024 carries different issues and risks, we wanted to keep these in mind, so that the values address these.

Some of the pain points of research projects highlighted in the discussion:

  • Insufficient documentation (leaving ‘breadcrumbs’ behind)
  • The scale and ambiguity of the research outcomes
  • Parallel working on multiple projects
  • Limited longevity of the projects and teams due to grant work

 

 

Revised Agile Values

Below is the original wording of Agile Values followed by the new wording that is the result of ARC-wide discussion, and in our view best represents their application to research projects.

 

Original:

  • Individuals and interactions over processes and tools.
  • Working software over comprehensive documentation.
  • Customer collaboration over contract negotiation.
  • Responding to change over following a plan. 

That is, while there is value in the items on the right, we value the items on the left more.

 

Agile Values for Research Projects:

In these statements, while there is value in the items on the right, we value the items on the left more.

  • Individuals and interactions supported by suitable processes and tools.
  • Working solutions supported by adequate documentation.
  • Collaboratively responding to change supported by agile planning.

 

Discussion Points:

  • To highlight the importance of all elements of delivery (including documentation, tools, processes, planning etc.), we agreed to move the sentence stressing this point to the start. For the same reason, we changed the word ‘over’ for ‘supported by’.
  • To denote that the processes and tools are in service of the main outcome, we added the word ‘suitable’.
  • The term ‘comprehensive’ documentation has been updated to ‘adequate’ documentation to reflect that the detail, format, and amount of documentation needs to be fit for purpose rather than a goal or outcome in its own right.
  • ‘Contract negotiation’ in research is different than in a business setting, being typically less adversarial and restricted to agreement with funders. The concept as evoked in the original values applies more to the process of requirements elicitation and jointly planning for the project delivery, so we agreed to merge the values related to contracts and to planning, with the overarching theme of collaborative work. This is to stress that the nature of scoping, planning and delivery of research projects is collaborative and evolving, rather than a fixed result of prior negotiations.

 

Revised Agile Principles

 

For each principle we set out the original wording followed by the new wording that is the result of the ARC-wide discussion and best represents their application to research projects.

Included are also some of the main discussion points to clarify the thought process that went into the updated wording.

 

Principle 1

 

Original:

Our highest priority is to satisfy the customer through early and continuous delivery of valuable software.

 

New Wording for Research Projects:

Our highest priority is early and continuous delivery of valuable outputs through meaningful collaboration.

 

Discussion Points:

  • How to define ‘customer’. Suggestions included ‘domain experts and users’, ‘the world, ‘collaborators’, and ‘researchers’. In the end, we agreed that highlighting a ‘customer’ in this principle is unnecessary, as the purpose of the collaboration project is not aimed only at one of the parties (regardless their name).
  • The word ‘satisfy’ implies that our contribution is to deliver someone else’s. requirements as opposed to actively collaborate on research as equal partners.
  • The words ‘early’ and ‘continuous’ carry the key point of this principle, therefore we made sure they are included in the new version.
  • The output of our projects is not necessarily ‘valuable software’ but it might be research, training, software, digital solutions or data management to enable research, or a combination of the above.

 

 

Principle 2

 

Original:

Welcome changing requirements, even late in development.  Agile processes harness change for the customer’s competitive advantage.

 

New Wording for Research Projects:

Welcome changing requirements, even late in development. Agile processes harness change for the benefit of the collaborative research outcome.

 

Discussion Points:

  • ‘Customer’ and ‘competitive advantage’ do not apply well to research projects, and it is important to define what it is we are trying to maximise.
  • The words ‘welcome changing requirement’ and ‘even late in the development’ are key in this message and we made sure they make it to the latest version. It is understood that this doesn’t mean indiscriminate implementation of any change (early or late); rather it means the ability to assess changes and deal with them appropriately being an expected part of the process.

 

 

Principle 3

 

Original:

Deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale.

 

New Wording for Research Projects:

Deliver meaningful outputs frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale.

 

Discussion Points:

  • The ‘working software’ is not the only possible output – as discussed before. The considered options for this principle were ‘research outcome’ or ‘output’.
  • The term ‘research outcome’ was found to be closer in meaning to the end result of the project, whereas ‘output’ can be a partial deliverable or result of any kind (software functionality, bug fix, result or a partial achievement of a particular research question, documentation of rules/requirements, update of data etc.). As the point of this principle is to stress frequent delivery of interim outputs, the term ‘outputs’ was found best suited.
  • ‘Meaningful’ output has been added to denote the principle of producing an output that is not only a part of the final deliverables (e.g. final documentation – valuable as it is) but crucially steers the project towards better understanding of the requirements or solution and achieving its main goals.

 

 

Principle 4

 

Original:

Businesspeople and developers must work together daily throughout the project.

 

New Wording for Research Projects:

Domain experts and research technology professionals aim to work together daily throughout the project.

 

Discussion Points:

  • ‘Businesspeople’ in research mean anyone who is bringing the knowledge of the research domain that we are collaborating on. This can be researchers, post-docs, user representatives (e.g. in cases of co-creation), business representatives (in cases of collaboration with industry), etc. ‘Domain experts’ was agreed to cover all these possibilities.
  • ‘Research Technology Professionals’ covers all professions within ARC (Research Software Engineers, Research Data Scientists, Research Data Stewards, Research Infrastructure Developers, PRISMs) and is a term used by UKRI.
  • Although the RTPs are also domain experts in their own right, the point of this principle is that the technical aspects of the project should be worked on in very close collaboration with the non-technical experts. Therefore, we kept the demarcation of the technical and non-technical experts for this principle, rather than covering them by the term ‘collaborators’ as we do in some of the other principles.
  • The ambition of working together ‘daily’ has been challenged in this discussion as it is a very challenging requirement that is rarely practicable. However, as the principles denote the recommended ideal (e.g. team members on full time on a single project, the product owner with good availability and direct accountability), it is very useful and important to have this principle stated in its ideal undiluted form. For the cases where compromises need to be found (e.g. team members on part time, low availability of collaborators etc.), it is useful to understand the reasons for these compromises and what are the most reasonable adjustments.
  • Due to the ambitious nature of ‘daily’ communication and collaboration, the word ‘must’ was viewed as too strong and was rephrased as an aim.

 

 

Principle 5

 

Original:

Build projects around motivated individuals. Give them the environment and support they need and trust them to get the job done.

 

Wording for Research Projects – No Change:

Build projects around motivated individuals. Give them the environment and support they need and trust them to get the job done.

 

Discussion Points:

  • There was no challenge about the content or wording of this principle. Arguably, in the context of research, this principle is not only as relevant as in commercial setting, but also closer to the ethos of the individuals and teams working in this environment compared to business.

 

 

Principle 6

 

Original:

The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.

 

New Wording for Research Projects:

The most efficient and effective method of communication in a research team is synchronous conversation.

 

Discussion Points:

  • In our current working environment, it is not reasonable to assume that teams are physically collocated, therefore physical face-to-face conversation is frequently not feasible. Synchronous conversation (such as Teams call, Slack huddle or similar) is the next best option.
  • Synchronous conversation is not everyone’s preferred method of communication and there are situations where conveying information might be better suited to other media. However, when it comes to communication, synchronous communication enables richer and more nuanced information exchange in faster and more efficient ways than asynchronous communication and therefore is essential to establish as a regular communication channel for a team.
  • In the original principles, the ‘development’ team might imply mainly the involvement of technical professionals. However, as the outcome of research projects is often research rather than software, this principle applies to all members of the team, including the domain experts.

 

 

Principle 7

 

Original:

Working software is the primary measure of progress

 

New Wording for Research Projects:

Research outputs are the primary measure of progress.

 

Discussion Points:

  • The definition of the key output of the research projects that can be produced regularly and in the interim before the end of the project. We chose ‘research outputs’ in favour of ‘research outcome’, as the ‘research outcome’ is often reached only at the end of the project.

 

 

Principle 8

 

Original:

Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely.

 

New Wording for Research Projects:

Agile processes promote development at a sustainable pace for the whole team, without having to increase intensity to meet deadlines.

 

Discussion Points:

  • It is unreasonable and unnecessary to expect ‘indefinite’ delivery. In contrast to a commercial setting, the duration of collaboration within a research team is often limited by grants and therefore specifying ‘any duration’ is equally unnecessary. The key message of this principle is that the ways of working should be ‘sustainable’ to all members of the team, while it lasts.
  • As the term ‘sustainable’ is often associated with environmental impact, which is not the point of this principle, we have added ‘pace’ to the original wording for clarity.

 

 

Principle 9

 

Original:

Continuous attention to technical excellence and good design enhances agility.

 

Wording for Research Projects – No Change:

Continuous attention to technical excellence and good design enhances agility.

 

Discussion Points:

  • There is no obvious challenge in translating this principle from a commercial to a research setting and there were no other suggestions raised in the discussion.
  • The frequent discussion in relation to this principle is how it relates to the previous principles of embracing change and producing outputs early – but this is related to adoption of agile ways of working themselves, rather than their adaptation to research/academia.

 

 

Principle 10

 

Original:

Simplicity – the art of maximizing the amount of work not done – is essential.

 

Wording for Research Projects – No Change:

Simplicity – the art of maximizing the amount of work not done – is essential.

 

Discussion Points:

  • As the wording ‘maximising the amount of work not done’ is purposely bold and provocative, it sparked a discussion as to whether this statement is encouraging not putting sufficient effort into the project. However, it has been agreed by majority that it is clear that this statement is encouraging prioritisation and efficiency rather than avoiding doing work that is legitimate and important (whatever the nature of that work might be, including documentation, refactoring, search for efficient solutions, etc.).

 

 

Principle 11

 

Original:

The best architectures, requirements, and designs emerge from self-organizing teams.

 

Wording for Research Projects – No Change:

The best architectures, requirements, and designs emerge from self-organizing teams.

 

Discussion Points:

  • The principle feels congruent with our understanding of the best ways of working for research projects and didn’t raise any challenge in the discussion.
  • Although not brought up in the discussion, one of the relevant points might be a discussion how to include the role of ARC Project Manager to the construct of the flat Agile team (especially for Scrum).

 

 

Principle 12

 

Original:

At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behaviour accordingly.

 

Wording for Research Projects – No Change:

At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behaviour accordingly.

 

Discussion Points:

  • There was general agreement and no challenge to this principle in the discussion. Everyone in the team is familiar with team or sprint retrospectives and broadly in agreement about their usefulness.
  • The challenge in this space might be in details of the practice of retrospectives (or similar techniques) – their frequency, who runs this meeting, who attends the meeting – to make sure that it brings the intended benefits, and in the ways the learnings are actively fed back into the working practices of the team.

 

 

 

 

 

 

 

RSE Initiatives – 6 months in

By Amanda Ho-Lyn, on 7 June 2024

What?

At ARC I think it would be fair to say we strive to develop and improve not only on an individual level, but also on a group level. One of the ways we are doing this is through our RSE (Research Software Engineer) Initiatives – aiming to advance/evolve the RSE team to improve collaboration and delivery of the best possible software. They involve taking a more objective look at the current processes within our department and determining, by consensus, whether some of these processes need to be updated, or if a new solution should be devised. These are not overnight quick-fixes but rather, slow & steady progressions in the right direction.

We’ve focussed on 3 main areas: Professional DevelopmentGood Practices and Knowledge Sharing.

As we’ve recently reached the 6 month mark of embarking on this journey, I thought I’d share an overview of each initiative’s aim and how we’re doing.


Professional Development

Notable people: Connor Aird, Stef Piatek & soon to be Paul Smith

This is about understanding how we currently decide to upskill (soft and technical) ourselves, what opportunities there are and how we can enable and support more/better opportunities.

The way we decided to figure out what people are doing regarding their professional (and to some degree personal) development was by interviewing them.

At the time of writing almost all the interviews have been completed and data gathered, being prepared for analysis.

Good Practices

Notable people: Haroon Chughtai, Kimberly Meechan & Emily Dubrovska

This looks at how much we engage with establishing and following best practices with technologies, languages and tools. We also want to determine whether there are areas where we could formalise/document this for future RSEs – a notable example is within the Python Tooling Community.

We decided it would be worth modelling the approaches of the Python Tooling Community and seeing whether there are other language/technology communities within ARC that don’t have best practice guidance but would benefit from it. This was done through a survey.

At the time of writing, the next groups of interest are Web Development and DevOps – both in the stages of requirements gathering/gaining an idea of what guidance could be documented or be built on, as well as looking into how it could best be delivered. 

Knowledge Sharing

Notable people: George Svarovsky & Amanda Ho-Lyn

This is about understanding how we currently share knowledge across the group – particularly project information – and how we can improve our current systems to be more usable and make information more accessible.

We decided to do a survey to see how people felt about how information is currently shared and also how much they actually felt they knew about different aspects. There were also some mentions of discontent about where information was posted and shared across a plethora of platforms.

At the time of writing, we have added a mini landing page to the ARC GitHub (note that you must be part of the org to see it) in an attempt to centralise relevant links to various places – this is a living thing and can be updated as necessary. We have also sent out a survey (thank you to those who took the time to complete it) and have plans to act on the results – see my post with more details about this (coming soon).

 

Thanks to everyone who’s been a part of this and continues to help us improve – especially to Asif who is forging the way ahead. And keep an eye out for more surveys! 😁

 

Research Integrity in an AI-Enabled World

By Samantha Ahern, on 5 April 2024

Over the last 15 months there has been much debate, hype and concern relating to capabilities of tools and platforms leveraging Large Language Models (LLMs) and media generators. Broadly termed Generative AI. The predominant narrative in Higher Education has been around the perceived threat to academic integirty and associated value to degrees. As such a lot of focus and discussion has focused on taught students, assessment design and “AI-proof” assessment. This has been coupled with concerns relating to the inability to reliably detect generated content, and the disproportionate number of false positives related to non-native English speakers text submitted to various platforms.

AI generated image of a researches using AI in front of the UCL porticoHowever, despite the proliferation of Generative AI enabled research tools and platforms, numerous workshops offering increased research output productivity and publications asking authors to declare whether or not these tools were used in producing outputs there has been limited discussion with relation to staff and research integrity.

Coupled with the publication of initial findings from a study on staff use of these tools by Watermayer, Lanclos and Phipps that included use to complete “little things like health and safety stuff, or ethics, or summarizing reports” and potential safety risks from fine-tuning models as reported in the Stanford Univeristy published policy briefing Safety Risks from Customizing Foundation Models via Fine-Tuning a workshop focusing on the interplay of Generative AI and research integrity and ethics was proposed as an AIUK Fringe event.

Research Integrity in an AI-Enabled World took place on Monday 25th March 2024. The aim was to explore how we think Generative AI enabled tools and platforms, could and should impact on the research process, and what the integrity and ethics implication are. Eventually aim would be to produce a policy white paper.

The event was organised so that there was a series of thought provoking talks in the morning, followed by a world-cafe style session in the afternoon. The event was held under the Chatham House Rule to enable open and frank discussion of the topic and arising issues.

The first set of talks predominantly focused on ethical issues. There were discussions on authorship, and the nature of authorship where multiple actors are involved e.g. training data creators, platform developers and prompters.  Bias in image generation, reinforcing misconceptions and stereotypes. Culminating in a talk on the University of Salfords evolving approach to Generative AI and research ethics.

The second set of talks was focused on current capabilities, limitations and implications of using Generative AI enabled tools in the research pipeline, predomintly focusing on qualitative analysis. This session included a discussion around evidence synthesis and the need to find more efficient methods whilst maintaining reliability and a breadth of knowledge, and different approaches using “traditional” machine learning approaches versus use of large language models. Enhanced capabilities of Computer Aided Qualitative Data Analysis Systems and implications for methodological approaches were also introduced and discussed. The session concluded with a talk from Prof Jeremy Watson about the work currently being undertaken by the UK Committee on Research Integrity’s AI working group, of which he is member. Key themes currently under consideration by UKCORI are:

  • Governance
  • Roles and Responsibilities
  • Skills and Training
  • Public Understanding and Expectations
  • Attribution and Ownership – IP, etc.
  • Understanding Data Inputs and Models
  • Need for Research in AI and Integrity

During the world-cafe session participants addressed the following questions:

  • What do we mean by Research Integrity in an AI-Enabled Research Environment?
  • Are there degrees of Research Integrity based on discipline and how embedded AI use is in the research process?
  • What are the key ethical and legal considerations?

Including the following participant proposed questions:

  • Generative AI is extremely good at in-filling uncertainty, where details of images become filled with bias. Should the responsibility of bias be equally on a prompter who enables this by omission?
  • Recalibration of government and private funded RI in AI? Isn’t this the foundation of biases for RI?

Outputs from the world cafe session will be analysed over the next few weeks, and workshop participants were invited to contribute to the development of workshop outputs.

Key themes that emerged from the event include:

  • Transparency
  • Criticality
  • Responsibility
  • Fitness for purpose
  • Data protection and privacy
  • Digital divide – privilege and harms
  • Training – education

Social media post about the workshopThe workshop was well received by participants, with the participants rate their overall experience of the event as 4.71 out of 5.

The speaker sessions were rated as very good by over 70% of participants. With the world cafe being mentioned as a highlight of the event.

 

 

 

As the proposer, organising and the host of the event I can’t help but still wonder:

  • Can we ethically and with genuine integrity use tools which are fundamentally ethically flawed?
  • Why are we accepting of these issues?
  • How should we be pushing back?

I will leave you with these words from Arudhati Roy with which I opened the event: