The web provides access to millions of datasets. These data can have additional impact when used beyond the context for which they were originally created. But using a dataset beyond the context in which it originated remains challenging. Simply making data available does not mean it will be or can be easily used by others. At the same time, we have little empirical insight into what makes a dataset reusable and which of the existing guidelines and frameworks have an impact.
In this talk, I will discuss our research on what makes data reusable in practice. This is informed by a synthesis of literature on the topic, our studies on how people evaluate and make sense of data, and a case study on datasets on GitHub. In the case study, we describe a corpus of more than 1.4 million data files from over 65,000 repositories. Building on reuse features from the literature, we use GitHub’s engagement metrics as proxies for dataset reuse and devise an initial model, using deep neural networks, to predict a dataset’s reusability. This demonstrates the practical gap between principles and actionable insights that might allow data publishers and tool designers to implement functionalities that facilitate reuse.
Papersː
Talking datasets – Understanding data sensemaking behaviours
Dataset Reuse: Toward Translating Principles to Practice
When: February 15th 2022, 18:30 CET
Where: https://www.youtube.com/watch?v=8VJmR-3lTac
