Record of Contributions¶
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:
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.
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.
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 process that is inclusive and community-lead.
Contributors names should be added alphabetically
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).
As a core contributros I want to share “Why I 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 authoritative, 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.
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 academia, and I think some part of that can be solved by doing away with our laissez-faire attitude towards governance and management.
Role: Code of Conduct Committee member (2018 - present)
GitHub id: annakrystalli
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.
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!
Role: Book Dash November 2020 Attendee
I’m the founder of R-Ladies in Saudi Arabia (Dammam). I initially majored in pharmacology but quickly developed an interest in biochemistry, structural biology, and bioinformatics. I enjoy applying deep learning to answer biological questions.
I am currently co-developing a chapter on “CI services”. I have helped upgrade the Jupyter Book Infrastructure and add hypothes.is to enable collaborative annotation of The Turing Way chapters. I have also translated the README.me chapter in Arabic. Personal quote: “I find it hard to express my personal thoughts and feelings in words. This was such an amazing experience. It helped me to develop my technical skills. Thank you so much to everyone I met in this Book Dash event :heart:.”
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.
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¶
Role: Book Dash May 2019 Attendee, Translation Lead - Spanish (2020)
GitHub id: crangelsmith
ORCID id: 0000-0002-0227-836X
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.
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.
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.
Role: Book Dash November 2020 Attendee
GitHub id: EKaroune
Short bio: I’m an independent post-doctoral researcher working in the field of Environmental Archaeology and Palaeoecology. I have a PhD in Palaeoecology from the Institute of Archaeology, University College London. I am currently working on a project with Historic England concerning the development of novel methodologies in phytolith research for application to British Archaeological remains. I am also working on a project to improve the FAIRness of phytolith data.
I have contributed to the Guide for Collaboration. Specifically, I drafted the chapter on “Getting Started with GitHub” for novice learners. I have really enjoyed working in such a collaborative way during the November 2020 Book Dash. I have had interesting discussions concerning the accessibility of The Turing way and research in general with other contributors. I have further developed my Github skills by working in collaboration with @paulowoicho, @malvikasharan and @KirstieJane to develop a chapter on ‘Getting started on Github’. This improvement in my skills will really benefit my own personal research to develop my own collaborative working groups and teach others how to use these research tools. Here are a few links where I have contributed to: Chapter on “Getting Started with GitHub”. Curating terms for the online Glossary to maintain a list of all definitions in Afterword.
I try to work as openly as possible and a large part of my current research is developing easy and accessible to all collaborative and open ways of working. I am also working hard to bring together specialists in my field into a working group for Open Science so that we can work collaboratively towards subject-specific FAIR guidelines for phytolith data.
Role: Book Dash February 2020 Attendee, semi regular co-working call crasher
GitHub id: EstherPlomp
I’m a Data Steward at Delft University of Technology in the Netherlands, where I support researchers with their data management and open science practices. For my PhD research I analysed human teeth for their isotopic/chemical composition in order to say something about human mobility patterns (fields of forensics, archaeology, osteology).
Thanks to the Turing Way I really learned how to work collaboratively using GitHub. The book dash was a great kick start to actually practise and directly apply these skills, which now allows me to contribute more confidently to other projects as well! I primarily contributed to the Reproducible Research Chapter, to the Research Data Management section. I reviewed existing content and I’m working on adding a section on Data Management Plans and how to handle personal data. I also made a The Turing Way poster that I presented during a conference. I hope to pay it forward and facilitate others in learning how to work with GitHub through The Turing Way or The Carpentries workshops. I’m very grateful to be part of this great and inclusive community!
I think scientific research should be accessible to anyone that would like to learn and contribute. I’m hoping to bring together specialists from my research field to establish guidelines for isotopic data from human remains and guidelines for how to handle and document physical samples. I’m a co-chair of the Research Data Alliance group Physical Samples and Collections in the Research Data Ecosystem IG. Please do get in touch if you work with physical samples and would like to get involved! I’m part of the Open Research Calendar Team. This is a calendar that you can use to stay up to date with open research events, or add your own events to in order to increase visibility. Visit us at the Open Research Calendar Website or follow the calendar on Twitter!
Role: Core contributor (2020), Book Dash February 2020 Attendee
GitHub id: HeidiSeibold
ORCID id: 0000-0002-8960-9642
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.
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. Specifically, I have co-authored these chapters: Research Compendia, File Naming Convention, and reviewed many contributions. 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 :)
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.
Role: Book Dash November 2020 Attendee
GitHub id: irenekp
I’m an undergraduate student majoring in Information Science and Engineering. While short, my journey with Data Science and Data Management has been varied and I’ve loved watching how a single concept can mould into so many different disciplines! I have been able to work with data science as an RA for a couple of projects that focused on different aspects of Social Network Analysis. I’ve also been able to follow data management and related practices during my internships at a fintech and a telecom company.
Turing Way was my first foray into Open Source, and I have found it extremely helpful in learning both about general github and open source practices as well as being part of a moving and collaborative community. I especially loved being part of an extremely multidisciplinary group of people, really shows me the real span of Data Science! The ethics book has been a great source of interest for me as it encompasses many of the issues I both grappled with, debated and deliberated upon extensively during my own data science projects. During my time working on the Data Anonymization Chapter (Issue: #1578 , Pull Request: #1579 ) I managed to read more extensively about anonymization and I found answers to many of the questions that had previously bothered me. I really hope that the work we’ve done here to consolidate all these ethical guidelines will help make practicing data science with a strong ethical basis and clear moral conscience more easy and accessible.
In line with my contributions so far, I am extremely passionate about working on an ethical framework for Data Science, seeing as a lot of it focuses on exposing patterns that could easily be invasive, I really think an ethical approach to it is the only way to keep practicing it sustainably in the long term. Science Communication is an other one of my key areas of interest, I’ve been combining it with my love for sustainable practices (be it data science or water resource management) so far to research upon and write articles that I hope would inform and educate more people! I hope to add Data Visualization to this combination soon! I intend to keep working at the cross roads of Data Science and Sci-Comm for the foreseeable future!
Ismael Kherroubi Garcia¶
Role: Core contributor (2020), OLS-2 for Turing project lead, Book Dash November 2020 Attendee
GitHub id: Ismael-KG
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).
Since my undergraduate degree, I have worked in fintech and then in arts organisations within human resources teams, finally reaching 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! Personal quote: “Research Ethics is complex, and two related concepts are Responsible Research and Innovation (RRI) and Research Integrity. Depending on whether we wear an RRI hat or research integrity goggles, we will encounter different research ethics questions. But it is important to wear the two at all times. I call this Steampunk Research Ethics.”
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!
José María Fernández¶
Role: Book Dash November 2020 Attendee (BioHackathon-EU)
GitHub id: @jmfernandez
I’m a senior research engineer from INB coordination unit, BSC, ELIXIR Spain. With an MSc in Computer Science, I have been working in bioinformatics since 1999, involved in very disparate projects along these years. Currently, I’m very involved in technical and scientific benchmarking, reproducibility and workflow execution abstractions, among other topics.
I have really enjoyed meeting so warming and the dynamic community around The Turing Way! I have mostly contributed to reviewing open Pull requests and networking with the community members.
Kim De Ruyck¶
Role: Book Dash November 2020 Attendee (BioHackathon-EU)
GitHub id: kderuyck
Since 2016, I am managing the Belgian ELIXIR Node (we pursue FAIRification of research data and facilitating reproducible analysis, through activities in data management and analysis as well as training; we also focus on domain specific services in plant sciences, human health and proteomics). I was trained as a Bioscience engineer, have a PhD in Medical Sciences and performed medical genetics research for many years.
I started familiarizing myself with the GitHub environment and learned how to collaborate through it. It was especially nice to meet the vibrant community working together on the Turing Way! Specifically, I have authored a subchapter on Research Data Management Toolkit.
I am a Biostatistician who transitioned to Data Science. I work at the University of Buenos Aires (Argentina). I specialize in several areas of Health Sciences. I am passionate about changing the way applied stats is taught and practiced. I have so much to learn and do; it seems I will need extra lives to accomplish all. More about me here.
I am currently co-developing a chapter on “Leadership in Data Science” and supporting Spanish community in translating and getting involved in the project. I hope this is my first of several Book Dashes! It was an outstanding experience. Thank you so much, Malvika and Kirstie, for brilliantly organizing and coordinating this event! ✨ 💖
Role: OLS-2 for Turing project lead, Book Dash November 2020 Attendee
GitHub id: 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.
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!
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.
“I’m not from a tech field but I’ve learned so much about github as a tool for collaborative working: thanks so much for everyone who was part of the November 2020 book dash for all your useful advice!”
Role: Core Contributor (2019), Book Dash February 2020 helper
GitHub id: LouiseABowler
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!
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.
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.
Role: Community Manager (2019 - present), Book Dash May 2019 Attendee
GitHub id: malvikasharan
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.
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.
Role: Book Dash November 2020 Attendee
I am a Research Assistant in the JDM lab at the University of Leicester. At UoL, I am also social media officer for the Post Doc and Research Staff association and ECR representative for my department. I hold an MSc in Social Psychology and a Ph.D. in Cognitive and Brain Sciences and my main research interests involve decision making, social hypothesis testing, and reasoning biases.
In the November 2020 book dash, I used GitHub for the first time! I helped fix some small bugs (grammar and syntax, typos, formatting) and, I proposed two chapters on data visualisation and on study pre-registration. I started familiarising myself with the GitHub environment and learned how to collaborate through it to provide valuable contributions to the project. My work during these 5 days has mostly been individual, but I would really love to collaborate with others to work on the two chapters I suggested! Here are few things that I am currently working on: a chapter on data visualisation (#1563), a section on cognitive biases/constraints in visualising and understanding data (#1572) and a subchapter on pre-registration (#1585).
I am passionate about science communication and research dissemination and interested in replicability, open science issues, and the interface between cognitive and social aspects in social psychology topics like intergroup relations and impression formation. At the moment I am particularly fascinated by data visualisation and infographics.
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.
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¶
Role: Core contributor, JupyterBook Infrastructure Maintainer (2020), OLS-2 for Turing mentor, Book Dash 2020 Attendee and helper
GitHub id: martinagvilas
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.
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. I have co-led and developed the tutorial on Creating a Jupyter Book with The Turing Way (Github repo). During the Book Dash (November 2020), I worked with @BatoolMM on the upgrade of the Jupyter Book that allows for annotation (PR #1516). I facilitated mentored contributions (in spanish as well 🇦🇷 🇧🇴 ) I also gave a talk about The Turing Way and computational reproducibility at the Brainhack Donostia 2020 (slides here)
More information about me can be read on my website.
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.
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.
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.
Role: Google Season of Doc: Technical Writer, OLS-2 for Turing project lead(2020)
GitHub id: paulowoicho
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. Thereafter, I worked as a Research Analyst in the Fintech & Innovation Division of Guaranty Trust Bank, Nigeria and helped to drive the Bank’s push to become a platform by creating innovative digital products. I completed a Master’s in Data Science from the University of Glasgow and starting my PhD in January 2021 studying conversational information-seeking systems. I spent two years as a Research Analyst at Guaranty Trust Bank in Lagos, Nigeria helping to build innovative digital products to meet the Bank’s customer objectives.
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. Although The Turing Way is my first open source project, I thoroughly enjoyed the experience and learned a lot along the way. Before the GSoD program, I only used Github to ‘store’ my projects. Now, I am much more proficient at using Github for collaborative endeavours and I am more adept at working with tools such as Markdown, Jupyter Book, and Sphinx. In addition, I gained familiarity with setting up and working with web analytics software. You can see the full report from GSoD participation here. The BookDash November 2020 was great! It was awesome to meet, collaborate, and share ideas with people from around the world. Beyond the Book Dash, The Turing Way is the very first open-source project I have ever worked on. The experience has been fantastic, and I intend to stick around as a contributor after the Google Season of Docs program ends. I also see myself getting involved in other open-source projects.
Asides technical skills, I developed a deep appreciation for what working on an open source project entails. My mentors helped me realise that the value I left behind from the GSoD program was not in the amount of work I did, but how I enabled other contributors to also do the work I was doing. As a result, I learned to contribute as a Technical Writer in a manner that was reproducible, sustainable, accessible, and inclusive.
Role: Core Contributor (2019), Book Dash 2019 Attendee and helper
GitHub id: rosiehigman
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.
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!
Role: Core Contributor (2019), Book Dash May 2019 Facilitator
GitHub id: rainsworth
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.
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.
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.
Role: OLS-2 for Turing mentor, Book Dash November 2020 Attendee
GitHub id: SamGuay
I’m a PhD student in Cognitive Neuroscience at the University of Montreal, Canada, researching the effects of repetitive head impacts inactive and retired athletes with a neuroimaging perspective. In parallel, I’ve started the Open Science UMontreal initiative to equip early-career scientists with better knowledge and tools to implement more open science in their workflow. The OSUM community members are really awesome :rocket:. Specifically, I have been working to set a process to translate The Turing Way in French. I contributed to adding hypothes.is to The Turing Way.
The whole November 2020 Book Dash was my highlight. I got to know a welcoming community and amazing humans throughout the week. It was amazing to witness so much progress in that tiny amount of time.
Role: Core contributor, Infrastructure Maintainer (2019 - present), OLS-2 for Turing mentor, Book Dash 2020 helper
GitHub id: sgibson91
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.
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.
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.
Role: HacktoberFest contribution facilitator, OLS project lead (2020), Book Dash November 2020 Attendee
GitHub id: BrainonSilicon
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.
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.
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.
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.
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¶
Role: Community manager, Book Dash November 2020 attendee/helper
GitHub id: c-martinez
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.
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!
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.
Role: Community manager, Book Dash November 2020 attendee/helper
GitHub id: mkuzak
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 Council member and instructor trainer. He is also leading the Dutch chapter of the Carpentries and is on the core team of nl-RSE community.
I have personally contributed to The Turing Way by drafting chapters in the guide for Reproducible Research, reviewed other contributor’s Pull Requests and mentored contributions from Netherlands eScience Center.
Thanks goes to these wonderful people (emoji key):
This project follows the all-contributors specification. Contributions of any kind welcome!