Introducing open science practices across the research lifecycle
Data workflows & visualisation
- Incorporate open science best practices for funder and publisher compliance
- Focus on transparency, reproducibility and re-usability
- Harness the power of static or interactive data visualisation
At Talarify, we incorporate open science principles into our data workflows and can support you to do the same. Whether you are using spreadsheets, proprietary software, or open-source software and coding, we help to develop a pathway to openness starting from where you are and working with what you have.
Making data and analyses available via open-source, interactive data visualisations can facilitate transparency and broader dissemination and impact of your work. Our tools of choice for analysis pipelines and visualisations include freely available, open-source products like Python, R, OpenRefine, and others.
According to the UNESCO Recommendation on Open Science, open science
is defined as “an inclusive construct that combines various movements and practices aiming to make multilingual scientific knowledge openly available, accessible and reusable for everyone, to increase scientific collaborations and sharing of information for the benefits of science and society, and to open the processes of scientific knowledge creation, evaluation and communication to societal actors beyond the traditional scientific community.”
We provide training on open science principles and practices to ensure clients understand its relevance to their work and stimulate motivation to update workflows and practices. Many people are still hesitant to “go open” because of the fear of being scooped amongst others. We contextualise openness and identify client processes and workflows that are ready to be opened up without putting people (researchers or research subjects) at risk.
Source: http://www.researchsupport.uct.ac.za/why-open-science (This work is licensed under a Creative Commons Attribution 4.0 International License. Originally developed by UCT Research Support)
Convert existing data workflows and analysis
Whether you are using spreadsheets, proprietary software, or open-source applications, we identify opportunities to enhance, automate, and renew your workflows to make your analysis more efficient, transparent, reusable, and reproducible. We work with clients over an extended period to support stepwise improvements that are sustainable and relevant to their contexts.
Developing open-source data analysis workflows or visualisations
Our staff has extensive experience developing data analysis pipelines, stand-alone scripts, and static or interactive data visualisations in Python and R. We can work with you to design and build proof-of-concept products whilst teaching you the skills. Alternatively, we can join a project as collaborators and take full responsibility for data analysis or visualisation components.
