Summary of A Semantic Approach For Big Data Exploration in Industry 4.0, by Idoia Berges et al.
A Semantic Approach for Big Data Exploration in Industry 4.0
by Idoia Berges, Víctor Julio Ramírez-Durán, Arantza Illarramendi
First submitted to arxiv on: 18 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Databases (cs.DB)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research proposes a novel visual query system for Industry 4.0 scenarios, enabling domain experts to explore and visualize data in a user-friendly manner. The system combines semantic annotation with 2D digital machine representations, linked to ontology terms. This enables high-level querying, customized graphical visualizations, and enriched data download for further analysis. The proposed system addresses the challenge of data exploration for manufacturing experts, who often require assistance from IT experts. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Industry experts are getting better at understanding big data and patterns in manufacturing processes thanks to Industry 4.0 technologies. However, they may struggle to find specific insights when exploring data because pre-designed visualizations might not show everything. This paper offers a solution by creating a special system that lets experts see and understand data in their own way. The system uses special descriptions called ontology terms to help experts ask higher-level questions, get customized views of the answers, and download more detailed data for further study. |
