Managing Open and Reproducible Computational Projects: Glossary

This material is developed for mid-career and senior researchers in biomedical and biosciences fields.

This training aims to build a shared understanding and facilitate the integration of computational reproducibility in data science.

motivations

Shared repository with well structured and organised files are crucial for starting a project

Documentation is as important as data and code to understand the different aspects of the project and communicate about the research.

Licencing and open science practices allow proper use and reuse of all research objects, hence should be applied in computational research from the start.

Good research data management practices esures findability of your research data.

Storing, regular backing-up and archiving prevents data loss.

Sharing all types of research data transparently makes them easier to understand and reuse by others.

Gives fair recognition to people generating, handling and using data, and further stimulates collaboration with others.

Version controlled repository help record different contributions and contributor information openly.

Open Science is an umbrella term that involve different practices for research in the context of different research objects.

Online Persistent Identifiers or Digital Object Identifiers are useful for releasing and citing different versions of research objects.

First key point. Brief Answer to questions. (FIXME)

First key point. Brief Answers to questions. (FIXME)

Make group leaders familiar with practices that are crucial for their teams to develop reproducible code.

Encourage researchers to think about code reproducibility through quality check, testing, sharing their code as well as a research environment.

Introduce Continuous Integration for automating the testing process.

There are many benefits of code review and this should be implemented and practised in research team culture as early and as frequently as possible.

Synchronous code review creates opportunities for researchers to get feedback and learn from others in real-time.

Asynchronous code review is a good practice when working with busy researchers or collaborators in different time zones.

First key point. Brief Answer to questions. (FIXME)