Introduction
An expanding array of observational data now enables social, economic and environmental behaviours to be researched in a large-scale and empirical way. This is exciting as there are increasing opportunities to effect evidence-based decision making in science, government and industry. In order to generate insights and draw conclusions, however, such data-intensive research relies on reasonably informal, interactive data analysis approaches: those that combine data graphics and statistics via computational notebooks (R Markdown, Quarto, Jupyter) or interactive data analysis tools such as Tableau and PowerBI. Unlike traditional scientific processes, we don’t know what an optimal and rigorous interactive analysis should look like and their success more often than not relies on the expertise and skills of the data scientist.
Our proposed Theory & Methods Challenge Fortnight will develop proposals for conducting and reporting data-intensive research in a more formal way. Our hope is that this activity will lay the foundations for rigorous interactive data analysis practices and guidelines for computational tools that underpin the next generation of analysis platforms. Through the TMCF multi-day event, we aim to explore three sub-challenges:
- Modelling paradigms for data-driven science: establish what is distinctive about modelling in data-driven science by mapping out existing data-driven projects and the analysis practices they use.
- Recognising and capturing context: develop systematic ways of documenting the context under which analytical findings are made – a grammar for structuring exploratory research findings – so that inferences can be more formally reported.
- From analysis to communication: explore tools and technologies for documenting interactive data analysis processes with integrity – balancing claims to knowledge with informational complexity.
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