# SOSA: A Lightweight Ontology for Sensors, Observations, Samples, and Actuators

arXiv: https://arxiv.org/abs/1805.09979 · HTML: https://mlsanity.com/paper/1805.09979/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 May 2018.

## Built on by (most cited first, 27 of 27)

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- [How to Manage Tiny Machine Learning at Scale: An Industrial Perspective](https://mlsanity.com/paper/2202.09113/) (2022)
- [On-device Online Learning and Semantic Management of TinyML Systems](https://mlsanity.com/paper/2405.07601/) (2024)
- [Onto4MAT: A Swarm Shepherding Ontology for Generalised Multi-Agent Teaming](https://mlsanity.com/paper/2203.12955/) (2022)
- [A semantic approach to mapping the Provenance Ontology to Basic Formal Ontology](https://mlsanity.com/paper/2408.03866/) (2024)
- [Narrative Cartography with Knowledge Graphs](https://mlsanity.com/paper/2112.00970/) (2021)
- [The KnowWhereGraph Ontology](https://mlsanity.com/paper/2410.13948/) (2024)
- [From Detection to Action: Using LLM Agents for Fault-Tolerant Control](https://mlsanity.com/paper/2606.28011/) (2026)
- [SeLoC-ML: Semantic Low-Code Engineering for Machine Learning Applications in Industrial IoT](https://mlsanity.com/paper/2207.08818/) (2022)
- [A semantic web approach to uplift decentralized household energy data](https://mlsanity.com/paper/2208.10265/) (2022)
- [The S2 Hierarchical Discrete Global Grid as a Nexus for Data Representation, Integration, and Querying Across Geospatial Knowledge Graphs](https://mlsanity.com/paper/2410.14808/) (2024)
- [Batch Distillation Data for Developing Machine Learning Anomaly Detection Methods](https://mlsanity.com/paper/2510.18075/) (2025)
- [Semantic web technologies in sensor-based personal health monitoring systems: A systematic mapping study](https://mlsanity.com/paper/2306.04335/) (2023)
- [A Survey on Semantic Modeling for Building Energy Management](https://mlsanity.com/paper/2404.11716/) (2024)
- [Towards Enhancing Linked Data Retrieval in Conversational UIs using Large Language Models](https://mlsanity.com/paper/2409.16220/) (2024)
- [Grid-Based Projection of Spatial Data into Knowledge Graphs](https://mlsanity.com/paper/2411.02309/) (2024)
- [DomusFM: A Foundation Model for Event-Based Behavioral Monitoring in Smart-Homes](https://mlsanity.com/paper/2602.01910/) (2026)
- [A Pythonic Functional Approach for Semantic Data Harmonisation in the ILIAD Project](https://mlsanity.com/paper/2604.13042/) (2026)
- [HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities](https://mlsanity.com/paper/2605.09348/) (2026)
- [Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing](https://mlsanity.com/paper/2606.22496/) (2026)
- [ProbSPARQL: Querying Knowledge Graphs with Multi-dimensional, Uncertain Numeric Data](https://mlsanity.com/paper/2607.18262/) (2026)
- [RAG-Based Auto-Configuration for Industrial Fieldbus Devices](https://mlsanity.com/paper/2608.08618/) (2026)
- [GeoOutageBench: Benchmarking Ambiguity-aware, Ontology-grounded Geospatiotemporal KGQA for Multimodal Power Outage and Resilience Analysis](https://mlsanity.com/paper/2609.36082/) (2026)

## Abstract (arXiv)

The Sensor, Observation, Sample, and Actuator (SOSA) ontology provides a formal but lightweight general-purpose specification for modeling the interaction between the entities involved in the acts of observation, actuation, and sampling. SOSA is the result of rethinking the W3C-XG Semantic Sensor Network (SSN) ontology based on changes in scope and target audience, technical developments, and lessons learned over the past years. SOSA also acts as a replacement of SSN's Stimulus Sensor Observation (SSO) core. It has been developed by the first joint working group of the Open Geospatial Consortium (OGC) and the World Wide Web Consortium (W3C) on Spatial Data on the Web. In this work, we motivate the need for SOSA, provide an overview of the main classes and properties, and briefly discuss its integration with the new release of the SSN ontology as well as various other alignments to specifications such as OGC's Observations and Measurements (O&M), Dolce-Ultralite (DUL), and other prominent ontologies. We will also touch upon common modeling problems and application areas related to publishing and searching observation, sampling, and actuation data on the Web. The SOSA ontology and standard can be accessed at urlhttps://www.w3.org/TR/vocab-ssn/.