# Talking datasets: Understanding data sensemaking behaviours

arXiv: https://arxiv.org/abs/1911.09041 · HTML: https://mlsanity.com/paper/1911.09041/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Nov 2019.

## Built on by (most cited first, 7 of 7)

- [From Local to Global: A Graph RAG Approach to Query-Focused Summarization](https://mlsanity.com/paper/2404.16130/) (2024)
- [Improving Steering and Verification in AI-Assisted Data Analysis with Interactive Task Decomposition](https://mlsanity.com/paper/2407.02651/) (2024)
- [The Dataset Nutrition Label (2nd Gen): Leveraging Context to Mitigate Harms in Artificial Intelligence](https://mlsanity.com/paper/2201.03954/) (2022)
- [LongDA: Benchmarking LLM Agents for Long-Document Data Analysis](https://mlsanity.com/paper/2601.02598/) (2026)
- [Is a Seat at the Table Enough? Engaging Teachers and Students in Dataset Specification for ML in Education](https://mlsanity.com/paper/2311.05792/) (2023)
- [DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization](https://mlsanity.com/paper/2305.18358/) (2023)
- [Prompting Datasets: Data Discovery with Conversational Agents](https://mlsanity.com/paper/2312.09947/) (2023)

## Abstract (arXiv)

The sharing and reuse of data are seen as critical to solving the most complex problems of today. Despite this potential, relatively little is known about a key step in data reuse: people's behaviours involved in data-centric sensemaking. We aim to address this gap by presenting a mixed-methods study combining in-depth interviews, a think-aloud task and a screen recording analysis with 31 researchers as they summarised and interacted with both familiar and unfamiliar data. We use our findings to identify and detail common activity patterns and necessary data attributes across three clusters of sensemaking activities: inspecting data, engaging with content, and placing data within broader contexts. We conclude by proposing design recommendations for tools and documentation practices which can be used to facilitate sensemaking and subsequent data reuse.