# Accessing and Interpreting OPC UA Event Traces based on Semantic Process Descriptions

arXiv: https://arxiv.org/abs/2207.12252 · HTML: https://mlsanity.com/paper/2207.12252/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 23 references that are in the map.
- First posted on arXiv 25 Jul 2022.

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

- [Representing Timed Automata and Timing Anomalies of Cyber-Physical Production Systems in Knowledge Graphs](https://mlsanity.com/paper/2308.13433/) (2023)
- [Integration of Domain Expert-Centric Ontology Design into the CRISP-DM for Cyber-Physical Production Systems](https://mlsanity.com/paper/2307.11637/) (2023)

## Abstract (arXiv)

The analysis of event data from production systems is the basis for many applications associated with Industry 4.0. However, heterogeneous and disjoint data is common in this domain. As a consequence, contextual information of an event might be incomplete or improperly interpreted which results in suboptimal analysis results. This paper proposes an approach to access a production systems' event data based on the event data's context (such as the product type, process type or process parameters). The approach extracts filtered event logs from a database system by combining: 1) a semantic model of a production system's hierarchical structure, 2) a formalized process description and 3) an OPC UA information model. As a proof of concept we demonstrate our approach using a sample server based on OPC UA for Machinery Companion Specifications.