Linked data to streaming data sensors sources for direct access

Abstract

Goal: Industrial operations are complex, and data sensors assure safety and reliable information for production improvements. Multiple stakeholders can take advantage of data acquisition for post-analysis and process control. Providing users and systems with friendly access to operating data is fundamental to the digital transition in the industry 4.0 scenario. Linking data and systems over ontologies and Industry Foundation Classes will boost supply chain performance in many layers. This paper presents the concept of valid data points over Uniform Resource Identifiers for sensor time-series into triples stores via Application Programming Interfaces. Design/Methodology/Approach: A streaming data source approach to integrating industrial sensor data and sharing it via Uniform Resource Identifiers is developed and tested using Node-Red with multiple data connection types, such as the Industry Foundation Classes and open-source time series databases. Results: The detailed proof of concept presented valid the feasibility of sharing sensor data via Uniform Resource Identifiers. The findings provide a backbone of a system able to interop Message Queuing Telemetry Transport data, Resource Description Framework datasets and Industry Foundation Classes schema. Limitations of the investigation: The system envisaged was tested using simulated data. However, it is expected to have similar results from real data use. Nevertheless, more research will be needed to implement more features, such as three-dimensional object integration. Practical implications: The solution designed and tested presented can be used in practice for companies that desire to expand via linked data shareability and interoperability. Also, researchers can advance the solution for specific features, such as creating an open-source data query and manipulation language. Originality/Value: This paper examines future deployments of systems-to-systems interoperability targeting user-friendly data shareability. It is meant to be useful for industrial and academic developments.