# Olio: A Semantic Search Interface for Data Repositories

arXiv: https://arxiv.org/abs/2307.16396 · HTML: https://mlsanity.com/paper/2307.16396/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Jul 2023.

## Built on by (most cited first, 2 of 2)

- [Boosting Text-to-Chart Retrieval through Training with Synthesized Semantic Insights](https://mlsanity.com/paper/2505.10043/) (2025)
- [Safire: Similarity Framework for Visualization Retrieval](https://mlsanity.com/paper/2510.16662/) (2025)

## Abstract (arXiv)

Search and information retrieval systems are becoming more expressive in interpreting user queries beyond the traditional weighted bag-of-words model of document retrieval. For example, searching for a flight status or a game score returns a dynamically generated response along with supporting, pre-authored documents contextually relevant to the query. In this paper, we extend this hybrid search paradigm to data repositories that contain curated data sources and visualization content. We introduce a semantic search interface, OLIO, that provides a hybrid set of results comprising both auto-generated visualization responses and pre-authored charts to blend analytical question-answering with content discovery search goals. We specifically explore three search scenarios - question-and-answering, exploratory search, and design search over data repositories. The interface also provides faceted search support for users to refine and filter the conventional best-first search results based on parameters such as author name, time, and chart type. A preliminary user evaluation of the system demonstrates that OLIO's interface and the hybrid search paradigm collectively afford greater expressivity in how users discover insights and visualization content in data repositories.