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Record of Contributions

The contributors.md file and the contributors table in the README file together form the record of contributions in The Turing Way.

Contributions to The Turing Way may include but are not limited to, bug fixing, chapter planning, writing, editing, reviewing, idea generation, presentation, project management, and maintenance. We recognise all these contributions and acknowledge our community members fairly. For example, using all contributors bot we update the contributors table with each person’s name, where the emoji keys indicate the different tasks they have done (see the README file). We understand that different contributions mean different things to people and may translate differently towards their personal interest, skill development, value exchange and advancement of their careers. Therefore, we also offer the contributors.md file as a dedicated location to capture personal highlights from The Turing Way community members.

Individual contributors are welcome to provide their details under the section “Personal Highlights from The Turing Way Contributors”. Organisational support and collaborations are listed in the section, “Collaborating Organisations”. Each organisation name and details will be listed separately followed by contribution details of each individual contributor from that organisation.

Please see the community handbook for details on how you can be fairly acknowledged for your work.

Personal Highlights from The Turing Way Contributors

Please use this section to highlight your personal experiences in The Turing Way project and community. You can also describe the impact The Turing Way may have on you or your team members such as in promoting reproducible, ethical, collaborative and inclusive research practices.

This record can be used in your personal or professional portfolio (profile, CV, resume) by describing features you have enhanced, goals you have accomplished, skills you gain, opportunities you receive, personal connections you make, individuals you support and values you create through your involvement in The Turing Way.

See this entry as an example by Kirstie Whitaker, the project lead:

Kirstie Whitaker

I’m the lead of Tools, Practices and Systems research Programme at the Alan Turing Institute. I have a PhD in Neuroscience from the University of California at Berkeley and conducted my postdoctoral research at the University of Cambridge in the Brain Mapping Unit. I am a Mozilla fellowship (2016) and Fulbright scholarship (2007) alumna.

  • Personal highlights:

I am the lead of The Turing Way. I’ve done a lot of advocacy for changing research culture to make our work more efficient and effective, and I’ve noticed that we need to address the power structures in academia if we are to truly make research reproducible by default. I’m excited to build the Turing Way to both inspire the people who DO the research to make all their outputs as accessible as possible, and to nudge everyone else in the ecosystem to care about the work required to do so.

  • More information:

I’m really passionate about the concept of making science “open for all”. I take that to mean we should share all of our outputs - the data, code and protocols that we develop - whether they’re “significant” or not. But it also includes making those outputs FAIR - findable, accessible, interoperable and reusable. I am an advocate for greater diversity in STEM and in data science and particularly passionate about improving the ways we reward collaborative and supportive working. Finally, I’d like to pivot to having data science project be developed in the open from the beginning and with a decision making governance processs that is inclusive and community-lead.

Contributors names should be added alphabetically

Alexander Morley

  • Role: Infrastructure Maintainer (2018 - 2019)

  • GitHub id: alexmorley

  • ORCID: TBA

  • Short bio:

I am a Mozilla Fellow (2018-) and a PhD Candidate at the MRC Brain Network Dynamics Unit at the University of Oxford (2015-). I also receive support from the Software Sustainability Institute Fellowship programme (2018) and Microsoft/Research Software England Cloud Computing Fellowship programme (2018). My undergraduate degree was in Medicine at the University of Oxford (2012-2015).

  • Personal highlights:

TBA

  • More information:

I really want research to be accessible, but in a much broader sense than the word is often used. I would love to see a world where re-mixing research is a common thing, whether that be re-mixing figures to make them easier to understand, re-using data to generate new insights, or testing new methods to see how our theories might need to change. Slightly less on topic, but just as important, I am also passionate about the development and adoption of best-practices in governance. Safe and inclusive spaces are all too rare in acedemia, and I think some part of that can be solved by doing away with our laissez-faire attitude towards governance and management.

Why do you care about the Turing Way?

When people don’t use best practices in data science its almost always because they either don’t know about them, or feel they don’t have time. Advocates will tell people that the time is saved in the long-term, but it’s a hard sell. By providing concrete, incremental, but authoratitve, guidance I believe the Turing Way could provide the nudge that allows people to realise the benefits for themselves, and lowers the barrier for more researchers to acquire these highly valued skills.

Anna Krystalli

I’m a Research Software Engineer at the University of Sheffield helping researchers do more with their code and data. I’m also an editor for rOpenSci, a community of users and developers, Creating technical infrastructure of peer-reviewed R software tools for working with scientific data sources on the web.

  • Personal highlights:

TBA

  • More information:

I care about reproducible research in R! I learnt to code during my PhD in Marine Macroecology and was instantly hooked. Building on past experience as a quality assurance auditor, my experiences made me interested in how we practice science and specifically how we can do more out of the real workhorses of modern research, our code and data. Working in The Turing Way is a fantastic opportunity to take stock of the great work that has already been done in this space, aggregate and distill it to templates, checklists and best practices guidelines that are immediately useful to researchers. It’s an opportunity to set standards and harness the power of convention, especially with ECRs that have an opportunity to set up good practices from the start! Indeed, I hope the Turing Way will very much become the “Sheffield Way” too!

Becky Arnold

I’m an astrophysics PhD student at the University of Sheffield and I do computer simulations of star forming regions. I’m a 2018 Software Sustainability Institute fellow using the funds to organise talks and workshops about various issues surrounding good programming practise.

  • Personal highlights:

TBA

  • More information:

I am passionate about Science. All over the world humans come together to try and figure out how the universe works and that’s amazing, just as amazing as the answers themselves. I’m also passionate about how we actually do that science, making sure it’s accurate and reproducible. If it isn’t both of those things we haven’t moved forwards much, or worse still end up going in circles. I care deeply about changing the culture of academia, in which abuse of power (both minor and major) is all too common. I’ve met so many people that want to code well and follow best practise, which will benefit science enormously, but struggle to know how to do so. While there are lots of fantastic resources out there they’re often scattered and The Turing Way can improve that. I also hope that it can convince people that don’t consider themselves capable of being good programmers that there are steps they can take to drastically improve their coding.

Camila Rangel Smith

I am a Research Data Scientist at The Alan Turing Institute. I hold a PhD in Particle Physics from Université Paris Diderot where I worked on the ATLAS experiment at the Large Hadron Collider at CERN. During my PhD I participated on the discovery of the Higgs Boson particle announced by CERN in 2012. I continued working on ATLAS as a postdoc with Uppsala University where I focused on searches for physics beyond the Standard Model of Particle Physics. Right before joining the Turing, I worked as Data Scientist in the EdTech sector developing innovative products focused on the assessment process in education. Currently I’m working in collaboration with researchers from the Global Systems Institute at University of Exeter called Data science for Sustainable Development. In this project we are using remote sensing to monitor the resilience of patterned vegetation from semi-arid dryland ecosystems in the Sahel.

  • Personal highlights

I think The Turing Way is an excellent resource that can change the way science is done (I wish I had it when I started my PhD!). Although the international language of science is English, I know for a fact that not everyone in places like Latin-American have the time and resources to learn it, so I think we must do everything we can to break those barriers and improve the accessibility of knowledge for everyone. This is my motivation to translate the book to Spanish, and I hope that the Spanish version will be used as an important resource on the master course we are developing in LA-CoNGA physics project.

  • More information

I’m from Venezuela, and although I have done most of my career in Europe I’ve been always keen to stay connected to the academic and scientific wold back in Latin-America. I’m the co-founder of the CEVALE2VE project (http://www.cevale2ve.org/en/home/), which of a virtual learning community that aims to tackle the serious issue of brain-drain in some Latin-American countries by bringing back the knowledge in a digital/online platform. More recently that project has become consolidated into LA-CoNGA physics (http://laconga.redclara.net/), an EU Erasmus+ funded project with a mission to create a Latin American and European Community for Advanced Physics. In this project I’m helping to build a data science module that will be thought in an online master course.

Heidi Seibold

I lead a group on Open AI in Health at the Helmholtz Zentrum Munich. I develop machine learning methods to figure out which patients react well to certain treatments and implements these methods in R. My passion for open and reproducible research has led me to join the Turing Way community. I am involved in meta-research projects (research about research), I support, teach and contribute to open projects such as The Turing Way. My work for the Journal of Statistical Software includes reproducibility checks. We only publish papers which are fully computationally reproducible. I also work on making our machine-learning software more user-friendly, reusable and extensible. Together with a PhD student I am thinking about how to use data from hospitals to help doctors and patients find the right treatment for each individual patient.

  • Personal highlights:

I work in data science and open and reproducible research are the things I think and care about the most. So to me it only made sense to get involved. Plus: the community seemed amazing! To me The Turing Way is a role model when it comes to collaborative, distributed work. I learned so much just by participating in the book sprint and seeing how Malvika, Kirstie and everyone else contributed to providing an extremely welcoming and at the same time productive space. I took what I learned and tried to apply it in other contexts such as teaching. I will continue to do so. The Turing Way also inspired me to think about new ways we could teach people about open and reproducible (data) science. I am currently thinking a lot about how we could use the content from The Turing Way and turn it into a course. This idea was also part of an application, where I proposed to start a new group on Open AI. I regularly recommend The Turing Way as a resource. Both for learning more about reproducible data science and also when discussing specific topics. I think that people are taking it on and reading it :)

  • More information:

First, I would like to continue to help create content, review others content and be helpful in any way I can. Sometimes I like to look at really old issues and pull requests for example. Reviving such old, often almost finished bits, is very rewarding. Apart from that I also have a bigger, long term idea for The Turing Way. I personally am not a huge fan of reading. So books are not my favorite way to learn. In the past years I learned a lot by listening to others in talks, podcasts, videos, and of course conversations. So for me it is only a natural next step for The Turing Way to become more than a book. It could be an ecosystem, with the book at its basis. And – if we decide to go that route – I would like to be a part of it.

Ismael Kherroubi Garcia

I’m Ethics Research Assistant at the Alan Turing Institute. I have a BSc in Business Management and Administration and am currently working towards an MSc in Philosophy of the Social Sciences. I am an associate member of the Chartered Institute of Personnel and Development (CIPD).

  • Personal highlights:

Since my undergraduate degree, I have worked in fintech and then in arts organisations within human resources teams, finally reachint the Alan Turing Institute and helping support the Ethics Advisory Group. I think my highlight is that I’ve got a great background as a generalist! I am currently really thrilled to be working alongside Laura Carter and Sophia Batchelor to build a community around the Guide for Ethical Research!

  • More information:

I am really fascinated by philosophical discussions about the social sciences, so I love the thought of questioning what an open science culture looks like and how to get there!

Laura Carter

I’m a PhD candidate in the Human Rights Centre at the University of Essex, UK, researching the human rights implications of the use of data-driven technologies in the UK public sector, focusing on gender stereotyping and gender discrimination. Prior to my PhD, I worked as a human rights researcher for almost a decade, specialising mostly in human rights, sexual orientation and gender identity. I carried out field research in Europe and sub-Saharan Africa covering topics including homophobic and transphobic hate crimes, criminalisation of homosexuality and of sex work, legal gender recognition for trans people, and health rights for intersex people.

  • Personal highlights:

I’m really enjoying learning more about Open Science practices and communities! I’m excited to be part of an OLS-2 mentee cohort alongside Ismael Kherroubi Garcia and Sophia Batchelor, working on the Guide to Ethical Research: if you’re interested in building a community of thoughtful, reflective, ethical data scientists, please come and join us!

  • More information:

I’m interested in feminist and queer research methodologies and in interrogating structures of power and systems of categorisation. Throughout my career, most of my work has been on understanding these systems, how they work, and how they harm: so that they can be dismantled! More information about me on my website.

Louise Bowler

I’m a Research Data Scientist in the Alan Turing Institute’s Research Engineering Group. I have a degree in Physics from Imperial College London, after which I joined the Life Sciences Interface Doctoral Training Centre at the University of Oxford. I worked on an interdisciplinary PhD project that combined mathematical modelling, cardiac electrophysiology and safety pharmacology, and moved over to the Turing afterwards. Since then, I’ve worked on a range of projects spanning synthetic data, data visualisation, and of course, the Turing Way!

  • Personal highlights:

I got involved with The Turing Way via case studies of reproducibility in academic projects - essentially, I was a reproducibility detective during the initial phase of the project! :female_detective: The Turing Way was my first experience of working with collaborators from so many different institutions, and the community around this project has been a real highlight for me. My official time on the Turing Way has come to an end, but I still enjoy keeping in touch through the Book Dashes and other events.

  • More information:

As scientists, we share our work via papers and talks, but the intricacies of precisely how we implement an analysis pipeline or novel algorithm can be very difficult to convey in those formats. We’re currently seeing changes in the default way we want to publish our papers through the open access movement, and I’d love to see a similar change in mindset happen about the data that we collect and the code that we develop so that others can reproduce, learn from and build upon our work. I want to ensure that the route to sharing these types of research output is open to everyone, regardless of their level of programming experience - the route might not always be straightforward, but it’s a great opportunity to share and learn from our experiences! So many research projects now contain computational elements, yet it is easy to forget that not everyone has access to training in software engineering, or has a group of colleagues with such interests. If we say that we want people to make their research open and reproducible, we need to give them the tools they need to be confident in doing so. I see the Turing Way as the means of bridging that gap, by providing a friendly, practical and helpful guide for researchers at all stages of their careers.

Malvika Sharan

I am the community manager of The Turing Way at The Alan Turing Institute. I work with the community of diverse members to develop resources and ways that can make data science accessible for a wider audience. After receiving my Ph.D. in Bioinformatics and I worked at European Molecular Biology Laboratory, Germany, that helped me solidify my values as an Open Researcher and community builder. I co-founded the Open Life Science mentoring program in 2019 to help enhance access to Open Leadership tools for individuals interested in building communities around their work. I am also a fellow of the Software Sustainability Institute and a board member of the Open Bioinformatics Foundation.

  • Personal highlights:

As a community manager, I appreciate the opportunities for facilitating the work our contributors carry out in this community space while learning new skills and ideas from them. Through my talks, panel sessions, and workshops, I like to interact with members across different research domains, who I otherwise will never get a chance to meet. Besides connecting with members from diverse perspectives, my highlights in The Turing Way are co-developing community governance, acknowledgment pathways, and community resources in the Community Handbook for our members. I enjoy designing training resources around leadership in research in collaboration with Open Life Science.

Martin O’Reilly

I’m Principal Research Software Engineer and Deputy Head of the Research Engineering Group at the Alan Turing Institute. My focus is on using good software engineering practices to increase the impact of research software by making it reusable, reliable and robust I also have a strong interest in reproducible research, and am working to improve the tools and working practices at the Turing to make it easier for our researchers to work reproducibly I’ve moved back and forth between industry and academia over the years, gaining an MSc in Artificial Intelligence and a PhD in Computational Neuroscience along the way.

  • Personal highlights:

TBA

  • More information:

I feel strongly that researchers have a responsibility to ensure that the outcomes of their research are made available to all - researchers, practitioners and the public. These outcomes should be made available in a way that allows others not just to reproduce them, but also to re-use and build upon them. An awful lot of researcher and practitioner time is spent getting to the point they can usefully evaluate whether some research is of use to them, or in re-discovering unpublished negative results. This seems extremely wasteful and I’m convinced we can and should do better. In particular, I feel a lot can be done to improve the effective re-use of data produced by research projects. While there has been significant progress in recent years in the amount of data published alongside research articles, there is still a wide gulf between open data and re-usable data. In terms of research areas, I’m fascinated by the brain and especially the approach of understanding the brain by “faking it” (i.e. modelling and simulation). I’m particularly interested in robots as a way of embodying these models in the real world. I believe the Turing Way can impact positively in both these areas. By providing recommended working practices and guidance on associated tooling, we can make it easy for researchers to do the right thing. By publishing this with the weight of the Turing brand, we can apply social pressure for the adoption of these practices as new norms in the research communities we operate in.

Martina G. Vilas

I’m currently finishing my PhD in Neuroscience at the Max-Planck-Institute AE in Frankfurt, Germany. I study how the brain processes conceptual knowledge analyzing neural recordings with computational modelling techniques. As an advocate of open-research, I also work on improving the reproducibility of neuroscientific-analyses and enjoy contributing to open-source software projects.

  • Personal highlights:

Since the Book Dash in February 2020, I help with the maintenance of The Turing Way infrastructure and its reliance on Jupyter Book. The Turing Way is not only a great guide for conducting reproducible research, but it also provides a wonderful entry point into open-source contribution in general and connects you to a variety of open data-science communities. I’m also a mentor at the OLS-2 program and I have also worked with the pandas core-contributors in providing guidance to people from underrepresented groups in technology on making their first open-source contribution.

  • More information:

More information about me can be read on my website.

Patricia Herterich

I am a Research Data Specialist at University of Edinburgh’s Digital Curation Centre, UK. I am a 2019 Software Sustainability Institute Fellow and HiddenREF committee member. From 2016 to 2019, I worked as Research Repository Advisor at the University of Birmingham. From 2012 to 2016, I’ve worked at CERN as a doctoral student supporting Open Research stuff and then abandoned the PhD and started a real job using all the skills I aquired.

  • Personal highlights:

Working on the Turing Way reminded me about what I value in my work and that I do have more technical skill than I think. Based on the Turing Way work, I have started the product managmement role for DMPonline and I’m trying to take the inspiration from the project into my every day work whenever I can.

  • More information:

As a librarian, it feels like our influence is often limited, but I try to set up workshops/events to at least get the discussion started and give especially PhD students the feeling that they can challenge the status quo and there will be people in the institution that will support them that might not be their supervisor. I really love how the Turing Way aims to create good examples and I hope we can develop some ideas and resources that can have a positive impact in changing the current system. I care about collaborating and get really excited about trying new tools if my limited tech skills allow.

Paul Owoicho

  • Role: Google Season of Doc: Technical Writer, OLS project lead: Embedding Accessibility in The Turing Way (2020)

  • GitHub id: paulowoicho

  • ORCID: TBA

  • Short bio:

I am a Technical Writer / Google Season of Docs (GSoD) Participant working to make The Turing Way consistent, sustainable, and accessible. I have a BSc in Software Engineering from the American University of Nigeria, and an MSc in Data Science from the University of Glasgow. Before now, I worked as a Research Analyst in the Fintech & Innovation Division of Guaranty Trust Bank, Nigeria. While there, I helped to drive the Bank’s push to become a platform by creating innovative digital products.

  • Personal highlights:

The Turing Way is my first foray into open source and has been a fantastic learning experience. Not only have I gained a deeper understanding and appreciation for how GitHub works, but I am also learning to prioritise sustainability and empowerment in the work that I do. I am also very grateful for the opportunity to work with people (whom I may not have met otherwise) from around the world.

  • More information:

I enjoy browsing through and collecting memes. I am also interested in the intersection of Machine Learning, Information Retrieval, and Natural Language Processing. With these interests, soon, I hope to begin a PhD that explores how conversational search can be made more effective with the use of clarifying questions.

Rosie Higman

I am a Research Data Librarian at the University of Manchester, co-leading the research data management support service. My focus is on data sharing, training and encouraging researchers to engage in Open Research. My background is in the social sciences and I have recently started a PhD with the British Library and the University of Sheffield looking at Open Access and the role of the National Library.

  • Personal highlights:

TBA

  • More information:

I am passionate about Supporting researchers! Making it as easy as possible for researchers to make their research reproducible and open, and for this to be easier than undertaking research in a closed manner. I try to help researchers make small improvements in making their research open, on the basis that some progress is better than none! Working in research data management I’m naturally concerned that data is not taken seriously as an independent research output and the reward system in academia is so heavily geared towards ‘high impact’ journal articles. As someone from a non-STEM background I’m also interested in how we can make reproducible research as accessible as possible. This will be the first project where I’ve worked directly in GitHub and I’m excited to get more confident in using it! I spend much of my time talking to researchers about the overarching principles of why reproducible and open research is a good idea and am excited by the idea of giving people practical guidance on how to do this. Messy code is frequently cited in these discussions as a reason for not sharing code so if we could produce something which helps people get past this barrier would be great. I hope that the Turing Way will be something we can also use at the University of Manchester and other Turing universities around the country!

Rachael Ainsworth

I am the Research Software Community Manager at the Software Sustainability Institute. Previously, I worked as a Research Associate and Open Science Champion at the Jodrell Bank Centre for Astrophysics at the University of Manchester. My research involved observing jets from young stars with next-generation radio telescopes to investigate the physical processes that assemble stars like our Sun, and am currently working to make data from the radio telescope facilities at Jodrell Bank more accessible to all. I am also a FOSTER certified Open Science Trainer, Mozilla Open Leader, and Organiser for the women in data meetup group HER+Data MCR.

  • Personal highlights:

I have promoted The Turing Way through many presentations, notably at the Open Science Fair 2019 where I presented a poster and delivered 3 demonstrations of the project to attendees, one of which was recorded as part of the ORION Open Science Podcast. Through The Turing Way project I have gained valuable skills in open project management and met truly inspiring individuals working hard to promote openness and reproducibility in research.

  • More information:

I am passionate about promoting openness, transparency, reproducibility, wellbeing and inclusion in STEM and facilitating cross-stakeholder conversations in order to change research culture for the better. I also love space exploration. The Turing Way goal of ensuring that reproducible data science is “too easy not to do” really resonates with me. I find that it can be difficult to get researchers to engage with reproducibility and sharing their research outputs because they perceive that it will take too much time and effort with very little reward - when the opposite is true! Ensuring results are reproducible not only benefits research as a whole and increases efficiency, but working this way also offers researchers more opportunities for impact and collaboration.

Sarah Gibson

I am a Research Software Engineer at The Alan Turing Institute where I implement software best practices to translate academic research into real world solutions through the Turing’s collaborative network. I am also an operator and maintainer for the Binder project and runs a BinderHub cluster at the Turing which receives traffic from mybinder.org. In 2020, I am also honoured to be a Software Sustainability Institute Fellow and to continue advocating for reproducible and sustainable research through software.

  • Personal highlights:

Becoming a core member of The Turing Way and Project Binder, and helping people all around the world launch and share their analyses in the cloud.

  • More information:

I’m passionate about applying the skills I learnt during my PhD somewhere closer to home and learning new skills along the way. The Turing Way is an ideal opportunity for me to learn better research practices and widen my horizons from what academia has taught me.

Sophia Batchelor

I am a PhD student at the University of Leeds studying sensorimotor learning with the Center for Immersive Technologies. My research focuses on understanding how how our brains interprets, and responds to both our physical reality, and a constructed reality (AR/VR). I do this through a deep love of the brain and emerging technologies. We will soon be existing in the future that we are creating now; so when we build with a “people first” (or a brain first) philosophy, we end up building a space that allows people to flourish.

  • Personal highlights:

MY FIRST CONTRIBUTION TO THE TURING WAY! It’s an absolute honor to join The Turing Way community as we look towards an open, ethical, and accessible future. After having such a mixed STEM and non-STEM background, I’m thrilled to have joined this community as it grows and guides my thinking about how and what it means to do research.

  • More information:

I’m a fierce advocate for ethical and open research, and those beliefs tend to carry into everything I do. I previously worked on Brain Computer Interfaces after finishing my undergrad at UC Berkeley where I saw the incredible work that can be done through collaborative, crossdisciplinary science. I’m now part of Open Life Science’s second cohort learning how to implement the teachings of The Turing Way because when good science and good practice meets, great things can happen.

Collaborating Organisations

When members participate in The Turing Way community with the in-kind support of their funders and organisation, we acknowledge each member individually and list their organisations as “Collaborating organisations”. Such organisational supports are applicable when one or multiple members from a project or community collaborate to build resources in The Turing Way.

Netherlands eScience Center

The Netherlands eScience Center is the Dutch national hub for the development and application of domain overarching software and methods for the scientific community. Their main goal is to enable scientists with varying computing experience to fully utilize the potential of the available e-infrastructure and allow them to achieve otherwise unreachable scientific breakthroughs. The Netherlands eScience Center is primarily funded by the national research council (NWO) and the national e-infrastructure organization (SURF) of the Netherlands.

The Netherlands eScience center maintains its own guide for reproducible software development. The focus of the eScience center guide has a big overlap with The Turing Way and therefore it makes sense to avoid duplicating efforts. The eScience center contributes to The Turing Way in the areas which are relevant for the eScience guide. The eScience guide points to The Turing Way in when information would otherwise be duplicated.

Details of each members with their contributions have been listed alphabetically.

Carlos Martinez Oritz

Carlos obtained his PhD in Computer Science at the University of Exeter. Afterwards he worked on various research projects at the University of Exeter and Plymouth University. At the eScience Center, he has worked as an engineer in diverse projects in digital humanities and life sciences, developing expertise in natural language processing, linked open data and software sustainability. He is also a certified Software Carpentry instructor and is frequently involved in organising trainings.

  • Personal highlights:

We always advocate for software reuse and collaborative development of software. I love that we can do the same for software development guidelines: reuse content from the eScience guide and collaboratively develop with The Turing Way community!

  • More information:

I am a big advocate of improving software quality. I am really glad that the eScience center is collaborating with The Turing Way in providing guidelines and helping build better research software.

Mateusz Kuzak

Mateusz obtained his master degree in Biotechnology with specialization Biophysics, at the Jagiellonian University, Krakow, Poland. In September 2019 Mateusz joined the Netherlands eScience Center in the role of Community Officer with the focus on communities and training around Research Software Engineering, software best practices and sustainability, and the role of software in open science and reproducible research. Since 2015, Mateusz has been involved in the Carpentries community, first as an instructor, later contributor, mentor, Executive Counsil member and instructor trainer. He is also leading the Dutch chapter of the Carpentries and is on the core team of nl-RSE community.

  • Personal highlights:

  • More information:

Contributors

Thanks goes to these wonderful people (emoji key):


Rachael Ainsworth
📖 📋 🤔 💬 👀 📢
Tarek Allam
🚇 📖
Tania Allard
🤔 💬
Diego Alonso Alvarez
🤔 👀
Bouwe Andela
🖋
Kristijan Armeni
🐛
Becky Arnold
💬 💻 📖 🤔 👀

Dimitra Blana
👀 🖋
Louise Bowler
💬 💻 📖 💡 🤔 📋 👀
Alex Clarke
📖
Jez Cope
📖
Eric Daub
📖
Stephan Druskat
📖 🖋
Elizabeth DuPre
🚇 💬 👀

Stephen Eglen
👀
Joe Fennell
📖
Oliver Forrest
📖 🤔 🖋 👀
Pooja Gadige
📖
Jason Gates
📖 👀
Sarah Gibson
💬 💻 📖 🔧 👀 📢 🤔 ✅ 📹
Oscar Giles
📖

Richard Gilham
📖 🤔
Cassandra Gould van Praag
🤔 📖
Michael Grayling
📖
Nomi Harris
👀
Liberty Hamilton
🐛
Tim Head
💬 🤔
Patricia Herterich
💬 📖 👀 🤔 🖋

Rosie Higman
💬 📋 👀 🤔
Ian Hinder
📖
Hieu Hoang
🤔
Dan Hobley
📖
Chris Holdgraf
💬 🤔
Will Hulme
📖
James Kent
🐛

Greg Kiar
📖 👀
Danbee Kim
📖
Anna Krystalli
💬 💡 👀 🤔 ✅
Kevin Kunzmann
📖 🤔 🐛
Mateusz Kuzak
🐛 📋 🤔 👀 🖋
Eric Leung
🐛
Clare Liggins
📖

Robin Long
📖
Christopher Lovell
🚇
Frances Madden
🖋
Eirini Malliaraki
📖
Chris Markiewicz
🤔
Carlos Martinez
🐛 👀 🖋
Paula Andrea Martinez
🤔 👀

Lachlan Mason
🤔 📖 💻
Rohit Midha
📖
Javier Moldon
📖
Beth Montague-Hellen
📖
Alexander Morley
💬 👀 🤔 ⚠️ 🚇 🚧
James Myatt
📖
Oliver Clark
📖

Martin O'Reilly
💬 🔧 🤔
Jade Pickering
📖
Camila Rangel Smith
📖 🌍 🚧
Rosti Readioff
📖
James Robinson
🤔 💻
Pablo Rodríguez-Sánchez
🖋
Susanna-Assunta Sansone
📖

Ali Seyhun Saral
📖
Chanuki Illushka Seresinhe
📖
Nadia Soliman
📖
Andrew Stewart
✅
Sarah Stewart
📖
Oliver Strickson
💬 📖 ✅
Natalie Thurlby
💻 ⚠️

Gertjan van den Burg
📖 🤔 💬
Stefan Verhoeven
🖋
Kirstie Whitaker
💬 📖 🎨 📋 🔍 🤔 👀 📢
Tony Yang
📖 🌍 🚇
Yo Yehudi
📖 👀
Eirini Zormpa
🐛 👀
Malvika Sharan
📖 📋 🤔 📆 👀 📢 🚧 📹

Jim Madge
🖋
Federico Nanni
🐛 🖋
Evelina Gabasova
🐛 🖋
Nick Barlow
🐛 🖋
Radka Jersakova
🐛 🖋
Nathan Begbie
🐛 🤔
Esther Plomp
🐛 🤔 🖋 👀 📢 📝 🌍

Anna Hadjitofi
🖋 🌍 ✅
Miguel Rivera
🐛
Barbara Vreede
🖋
Heidi Seibold
🤔 🖋
Max Joseph
👀
Martina G. Vilas
🚇 ⚠️ 📢 📹 ✅
Laura Carter
👀 🐛 🤔 🖋

Victoria Dominguez del Angel
🐛
Andrea Pierré
🐛
Graham Lee
🐛 👀
Mustafa Anil Tuncel
🐛
Mark Woodbridge
🤔 🖋
Chad Gilbert
🐛
Frances Cooper
🖋

Joanna Leng
🖋
Colin Sauze
🤔 🖋
Christina Hitrova
🤔
Kesson Magid
🤔
Arielle Bennett-Lovell
🤔 👀
Katherine Dixey
🤔
Nicolás Alessandroni
🤔

Alex Chan
🤔
Neil Chue Hong
🤔
Cameron Trotter
🤔
Carlos Vladimiro González Zelaya
🤔
Pedro Pinto da Silva
🤔
Sedar Olmez
🤔
Rose Sisk
🤔

Natacha Chenevoy
🤔
Paul Dominick Baniqued
🤔
Georgia Atkinson
🤔
Tess Gough
🤔
Annabel Elizabeth Whipp
🤔
Sian Bladon
🤔
Charlotte Watson
🤔

Philip Darke
🤔
Sparkler
🌍
Yini
🌍
Adina Wagner
🖋
Georgiana Elena
👀
Enrico Glerean
🐛
Wiebke Toussaint
🐛

Danny Garside
🐛
Shankho Boron Ghosh
🐛
Yash Varshney
🐛
Jay Dev Jha
🐛
Jeremy Leipzig
🐛
Pranav Mahajan
🖋
Augustinas Sukys
🤔

DerienFe
🤔
Xiaoqing Chen
🤔
takuover
🤔
Srishti Nema
🐛 🖋
Victoria
🤔
mjcasy
🤔 🖋
Aditi Shenvi
🤔

ceciledebezenac
🤔
tugceoruc
🤔
vasilisstav
🤔
acork25
🤔
Joe Early
🤔
Georgia Tomova
🤔
swalkoAI
🤔

giuliaok
🤔
sethsh7
🤔
Ferran Gonzalez Hernandez
🤔
alessandroragano
🤔
daniguariso
🤔
kgrieman
🤔
Siba Smarak Panigrahi
🐛

Pierre Grimaud
🐛
Sumera Priyadarsini
🐛
sallyob123
🤔
akira-endo
🤔
Solon
🤔
smasarone
🤔
Risa Ueno
🤔

l-gorman
🤔
Obi Thompson Sargoni
🤔
PeterC-ATI
🤔
Oliver Hamelijnck
🤔
Ismael-KG
🖋 👀 📝 🤔
Tushar Rohilla
🐛 🖋
Alex Bird
✅ 👀

Eric R Scott
🐛
David Foster
👀 🐛
Markus Löning
👀 🖋
Julien Colomb
🖋
Samuel Nastase
🐛
Raniere Silva
🖋
Naomi Penfold
👀 🤔

Daniel Mietchen
🐛
Sophia Batchelor
👀 🤔 🚧
Gianni Scolaro
🐛
Paul Owoicho
🤔 👀 🐛
Samuel Guay
🌍
Jessy Provencher
🌍
Reina Camacho Toro
🌍

Remi Gau
🐛
Florian Gilcher
🐛
Stefan Janssen
🌍
Andrian Nobella
🌍
Romero Silva
🌍
Gustavo Becelli do Nacimento
🌍
Cem Ulus
🌍

Angelo Varlotta
🌍
Luca Bertinetto
🌍
Laura Acion
️️️️♿️ 🌍
beccawilson
️️️️♿️
yaseminturkyilmaz
📝
Lenka
📝

This project follows the all-contributors specification. Contributions of any kind welcome!

Bibliography