# Graph integration of structured, semistructured and unstructured data for data journalism

arXiv: https://arxiv.org/abs/2007.12488 · HTML: https://mlsanity.com/paper/2007.12488/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jul 2020.

## Built on by (most cited first, 5 of 5)

- [Cross Modal Data Discovery over Structured and Unstructured Data Lakes](https://mlsanity.com/paper/2306.00932/) (2023)
- [Q4EDA: A Novel Strategy for Textual Information Retrieval Based on User Interactions with Visual Representations of Time Series](https://mlsanity.com/paper/2101.08655/) (2021)
- [Integrating connection search in graph queries](https://mlsanity.com/paper/2208.04802/) (2022)
- [Text Data Integration](https://mlsanity.com/paper/2603.27055/) (2026)
- [Discovery-Driven Integration of Disjoint Tables via Text](https://mlsanity.com/paper/2609.26658/) (2026)

## Abstract (arXiv)

Nowadays, journalism is facilitated by the existence of large amounts of digital data sources, including many Open Data ones. Such data sources are extremely heterogeneous, ranging from highly struc-tured (relational databases), semi-structured (JSON, XML, HTML), graphs (e.g., RDF), and text. Journalists (and other classes of users lacking advanced IT expertise, such as most non-governmental-organizations, or small public administrations) need to be able to make sense of such heterogeneous corpora, even if they lack the ability to de ne and deploy custom extract-transform-load work ows. These are di cult to set up not only for arbitrary heterogeneous inputs , but also given that users may want to add (or remove) datasets to (from) the corpus. We describe a complete approach for integrating dynamic sets of heterogeneous data sources along the lines described above: the challenges we faced to make such graphs useful, allow their integration to scale, and the solutions we proposed for these problems. Our approach is implemented within the ConnectionLens system; we validate it through a set of experiments.