# The AnIML Ontology: Enabling Semantic Interoperability for Large-Scale Experimental Data in Interconnected Scientific Labs

arXiv: https://arxiv.org/abs/2604.01728 · HTML: https://mlsanity.com/paper/2604.01728/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 69 references that are in the map.
- First posted on arXiv 2 Apr 2026.

## Builds on (most cited first, 12 of 12)

- [BERTMap: A BERT-based Ontology Alignment System](https://mlsanity.com/paper/2112.02682/) (2021)
- [Autonomous discovery in the chemical sciences part II: Outlook](https://mlsanity.com/paper/2003.13755/) (2020)
- [DeepOnto: A Python Package for Ontology Engineering with Deep Learning](https://mlsanity.com/paper/2307.03067/) (2023)
- [OntoChat: a Framework for Conversational Ontology Engineering using Language Models](https://mlsanity.com/paper/2403.05921/) (2024)
- [A Simple Standard for Sharing Ontological Mappings (SSSOM)](https://mlsanity.com/paper/2112.07051/) (2021)
- [DOLCE: A Descriptive Ontology for Linguistic and Cognitive Engineering](https://mlsanity.com/paper/2308.01597/) (2023)
- [Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities](https://mlsanity.com/paper/2309.17255/) (2023)
- [An Ontology for the Materials Design Domain](https://mlsanity.com/paper/2006.07712/) (2020)
- [OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology Alignment](https://mlsanity.com/paper/2503.21902/) (2025)
- [Best Practices for Implementing FAIR Vocabularies and Ontologies on the Web](https://mlsanity.com/paper/2003.13084/) (2020)
- [Procedural Knowledge Ontology (PKO)](https://mlsanity.com/paper/2503.20634/) (2025)
- [RELRaE: LLM-Based Relationship Extraction, Labelling, Refinement, and Evaluation](https://mlsanity.com/paper/2507.03829/) (2025)

## Built on by (most cited first, 3 of 3)

- [LAP: An Agent-to-Instrument Protocol for Autonomous Science](https://mlsanity.com/paper/2606.03755/) (2026)
- [Discoverable Agent Knowledge -- A Formal Framework for Agentic KG Affordances (Extended Version)](https://mlsanity.com/paper/2605.19186/) (2026)
- [Knowledge Graph Re-engineering Along the Ontological Continuum (extended version)](https://mlsanity.com/paper/2605.22093/) (2026)

## Abstract (arXiv)

Achieving semantic interoperability across heterogeneous experimental data systems remains a major barrier to data-driven scientific discovery. The Analytical Information Markup Language (AnIML), a flexible XML-based standard for analytical chemistry and biology, is increasingly used in industrial R&D labs for managing and exchanging experimental data. However, the expressivity of the XML schema permits divergent interpretations across stakeholders, introducing inconsistencies that undermine the interoperability the AnIML schema was designed to support. In this paper, we present the AnIML Ontology, an OWL 2 ontology that formalises the semantics of AnIML and aligns it with the Allotrope Data Format to support future cross-system and cross-lab interoperability. The ontology was developed using an expert-in-the-loop approach combining LLM-assisted requirement elicitation with collaborative ontology engineering. We validate the ontology through a multi-layered approach: data-driven transformation of real-world AnIML files into knowledge graphs, competency question verification via SPARQL, and a novel validation protocol based on adversarial negative competency questions mapped to established ontological anti-patterns and enforced via SHACL constraints.