On Friday 30th April, we hosted our first community call based on the theme:
‘Building a Culture of Collaboration’.
The one-hour long event brought 30 attendees together from eight research institutions to celebrate the six month anniversary of the 4TU.ResearchData community and learn about building a culture of collaboration.
📥 Download the slides from the event and watch the recording!
Community Highlights: Value for members
The aim of the community is to provide an inclusive space for members to connect and exchange knowledge and ideas about the best practices for the creation and reuse of FAIR data.
Since the community was initiated in October 2020, we have welcomed more than 60 researchers and data supporters to the community platform and Slack workspace. Here’s some of the feedback we received from community members when we asked them about their personal highlights and experiences…
Updates from the community-led working groups
The aim of the working groups is to provide a support network for the data stewards and create opportunities for them to discuss and learn about important topics related to research data management. The expectation is that co-develop processes and documentation that can be scaled up and implemented across the 4TU.ResearchData partner and member institutions.
FAIR and Reproducible Code:
Train the Trainer sessions
Nicolas Dintzner kicked off the round of working group updates by reporting on the progress made by the FAIR and Reproducible Code working group. This working group is focused on how data stewards can empower researchers to create FAIR software through training and support.
During meetings, group members share experiences about the best practices for writing FAIR and reproducible code.
So far, the group has discussed how tools, integrated development environments (IDEs), version control, writing and testing, documentation, collaboration, licensing, and sharing and archiving of code can be used to improve code management and quality.
Early group discussions revealed that members have different skill sets when it comes to writing and managing code. Therefore, the next step is to organise ‘train the trainer’ sessions where data stewards can learn from one another in a supportive environment. During these sessions, the more advanced members will teach the less advanced members the necessary skills to support researchers with code management.
Training sessions will start in June this year using the ‘Best practices for writing reproducible code’ course material developed by Barabara Vreede at Utrecht University.
In order to understand the roles and responsibilities of data stewards at 4TU.ResearchData partner institutions in helping researchers to achieve privacy and GDPR compliance, the group has recently undertaken a ‘gap analysis’ to compare institutional workflows and identify topics for further discussion.
Selected topics were ‘data access’, ‘data transfer’ and ‘data anonymisation’. Proposed outputs of this working group include:
- The collection of example use cases that involve the collection of personal data since this would serve as an educational resource, and;
- The development of training for researchers about the use of open source tools for data anonymisation (e.g. Amnesia Data Anonymisation Tool).
Engagement and Education:
Disciplinary guides about data management
The focus of the Engagement and Education working group is to exchange and synthesize efforts related to data management training for different audiences across the 4TU.ResearchData partner institutions.
During the community call, Yan Wang explained that the working group has two main objectives.
- The first is to get an overview of the current state-of-the-art training activities conducted by working group members and to identify opportunities for cross-institutional collaboration.
- The second is to collect examples of research projects from different faculties and departments, and to curate these use cases into disciplinary guides that can be used to illustrate the importance of research data management practice in different contexts. Such guides will be interesting and informative for data supporters and researchers alike. A writing sprint will be organised in the coming months to develop the disciplinary guides.
The Keynote: Building Open Communities of Collaboration
“The Turing Way’s moonshot goal is to make reproducibility too easy not to do,” says Malvika.
The Turing Way guide aims to provide data scientists in academia, industry, government and the third sector with all the information they need at the very beginning of their project so that their work can be easily understood, reproduced and reused.
Starting as a ‘Guide for Reproducible Research’ that covered aspects of version control, testing and continuous integration, the project has now expanded to include guides on ‘Project Design’, ‘Communication’, ‘Collaboration’ and ‘Ethical Research’. It also includes a ‘Community Handbook’ so that their processes and community practices can be reused by others.
Collaboration at the community’s core
Two years (plus 150 subchapters, >250 GitHub contributors and thousands of users) later, the Turing Way community has continued to grow with collaboration at the heart of the project.
What is the key to building an open community of collaboration? Here are our top 10 take home messages from Malvika’s talk:
- Understand your community members. Identify their interests; grant access to skills, and support their needs.
- Design for intentional collaboration. Define pathways for collaboration and ‘label unlabelled doors’ so that it’s easy for people to navigate their path and get involved.
- Document all the processes. Be explicitly open about collaborations and let community members know where, when and how they can participate.
- Foster a safe and inclusive workspace. Provide guidelines, such as a code of conduct, to encourage safe and enjoyable participation.
- Provide an open source framework for knowledge exchange. This means that everyone can freely read, reuse, modify and distribute resources, thereby leading to collaboration, peer-production and project sustainability.
- Encourage mentorship and create space for the review of work to maintain and improve resources.
- Welcome external contributions and collaborations. For example, sharing best practices from other communities can be a valuable contribution to your community.
- Make your work global. Translate resources into other languages so that others can benefit from them.
- Create a sense of shared ownership that inspires contributions. If the project belongs to the community then everyone will feel responsible.
- Recognise all contributors so that efforts are not hidden or ignored. Provide an opportunity for community members to build their CV through their contributions!
With special thanks to…
- The speakers; Nicolas Dintzner, Santosh Ilamparuthi, Yan Wang and Malvika Sharan, for your insightful and motivating presentations.
- The event organisers; Lauren Besselaar (Events Coordinator) and Deirdre Casella (Communications Officer) for moderating the event and producing the wonderful Twitter thread! 🧶
- All community call participants for your attention and thought-provoking questions during the session!
See you in the next Call!