Agentic data science with the Data Agent Kit
cloud.google.com·6h ago
AI Research
arXiv CS.AI·Sep 12·5 min read
From Queries to Narratives: Cultural Heritage Data Stories for Knowledge Graph Exploration and Quality Assessment
TL;DR
Data stories have been developed to enhance the accessibility of cultural heritage knowledge graphs, enabling users to explore data and assess its quality more effectively. This approach combines narrative elements with executable SPARQL queries, making complex data more understandable and actionable.
✦ Why It Matters
Start using data stories to enhance user engagement with cultural heritage knowledge graphs today.
Key Takeaways
- Utilize data stories to simplify complex data exploration.
- Incorporate SPARQL queries for transparent data narratives.
- Leverage LODEON for creating reproducible data stories.
- Identify hidden data quality issues through narrative exploration.
How It Works
Data stories integrate narrative elements with SPARQL queries, allowing users to explore knowledge graphs interactively. By combining text, images, and query results, users can better understand the data's context and significance.
This method also highlights data quality issues that may not be apparent through aggregate statistics.