# JSON: data model, query languages and schema specification

arXiv: https://arxiv.org/abs/1701.02221 · HTML: https://mlsanity.com/paper/1701.02221/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Jan 2017.

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

- [Towards Learning Universal Hyperparameter Optimizers with Transformers](https://mlsanity.com/paper/2205.13320/) (2022)
- [RAG for Geoscience: What We Expect, Gaps and Opportunities](https://mlsanity.com/paper/2508.11246/) (2025)
- [PatchBoard: Schema-Grounded State Mutation for Reliable and Auditable LLM Multi-Agent Collaboration](https://mlsanity.com/paper/2605.29313/) (2026)
- [Notation Matters: A Benchmark Study of Token-Optimized Formats in Agentic AI Systems](https://mlsanity.com/paper/2605.29676/) (2026)
- [ER-RAG: Enhance RAG with ER-Based Unified Modeling of Heterogeneous Data Sources](https://mlsanity.com/paper/2504.06271/) (2025)
- [Leveraging Generative AI for Enhancing Domain-Driven Software Design](https://mlsanity.com/paper/2601.20909/) (2026)
- [Autoregressive Synthesis of Sparse and Semi-Structured Mixed-Type Data](https://mlsanity.com/paper/2603.01444/) (2026)

## Abstract (arXiv)

Despite the fact that JSON is currently one of the most popular formats for exchanging data on the Web, there are very few studies on this topic and there are no agreement upon theoretical framework for dealing with JSON. There- fore in this paper we propose a formal data model for JSON documents and, based on the common features present in available systems using JSON, we define a lightweight query language allowing us to navigate through JSON documents. We also introduce a logic capturing the schema proposal for JSON and study the complexity of basic computational tasks associated with these two formalisms.
