Quick Guide: InfoRapid KnowledgeBase Viewer — Features and UsesInfoRapid KnowledgeBase Viewer is a lightweight desktop application for visualizing, exploring, and presenting knowledge graphs and structured data. It supports reading common graph formats, interactive browsing, basic graph analytics and several export options. This guide walks through its main features, typical uses, and practical tips to help you get the most from the tool.
What InfoRapid KnowledgeBase Viewer is best for
InfoRapid KnowledgeBase Viewer is designed for users who need a simple, fast way to open and inspect knowledge graphs without installing a full ontology editor or graph database. Typical use cases include:
- Ad hoc exploration of RDF/OWL/Turtle/GraphML files.
- Visualizing relationships in small-to-medium knowledge graphs for presentations or reviews.
- Quick sanity checks of exported data from semantic tools or ETL pipelines.
- Teaching or demonstrating basic graph concepts and link structures.
Strengths: fast startup, intuitive interactive graph view, support for multiple import/export formats.
Limitations: not meant for large-scale graph processing, limited advanced reasoning or query capabilities compared to full-featured tools (e.g., Protégé, Neo4j).
Supported formats and data import
InfoRapid KnowledgeBase Viewer accepts several common graph and semantic web formats—useful when you want to inspect outputs from different tools:
- RDF/XML
- Turtle (.ttl)
- N-Triples
- OWL files
- GraphML
- CSV (when mapped to nodes/edges)
To open a file: File → Open, then select the graph file. The viewer automatically parses triples and builds a node–edge visualization. For CSV, ensure you map columns to source/target node IDs and optional edge labels.
Interactive visualization and navigation
The core feature is the interactive graph canvas:
- Zoom and pan to focus on areas of interest.
- Click a node to view details: labels, URIs, and attached properties.
- Expand or collapse neighborhoods to explore connected entities without clutter.
- Search by label, URI, or property value; results highlight matching nodes.
- Different layout algorithms (force-directed, hierarchical) help reveal structures.
- Node and edge highlighting makes it easy to trace relationships.
Practical tip: use incremental expansion when exploring dense graphs—start from a seed node and expand neighbors stepwise.
Styling, filtering, and layout options
You can adjust visual appearance to improve clarity:
- Change node colors and shapes by property or class to emphasize categories.
- Edge thickness and labels can reflect property importance or values.
- Apply filters to hide nodes/edges by type, degree, or property values.
- Switch layouts to reveal hierarchical flows or clusters.
Use styling to create focused views for presentations — e.g., color nodes by type and hide low-degree nodes to emphasize core entities.
Basic analytics and inspection
While not a heavy analytics platform, the viewer provides useful quick-inspection tools:
- Degree counts (in-degree, out-degree, total degree) for nodes.
- Connected component detection — see isolated subgraphs.
- Shortest path between selected nodes (when available).
- Quick counts of node and edge types.
These features are handy for sanity checks (e.g., confirm that every product node links to a category).
Exporting and sharing visuals
InfoRapid KnowledgeBase Viewer includes export options to share findings:
- Export images (PNG, SVG) of the current canvas for documentation or slides.
- Export subgraphs in RDF/OWL/GraphML to feed other tools.
- Copy node/edge lists into CSV for spreadsheets.
For reproducible reports, export the selected subgraph and include a screenshot with annotations.
Practical workflows and examples
- Data QA after conversion: After exporting RDF from a database, open the file in the viewer to confirm expected relationships and spot missing links.
- Client demos: Prepare a focused subgraph, style nodes by role, and export a high-resolution image for presentations.
- Classroom lessons: Use the search and expand features to demonstrate RDF triples and graph traversal.
Example: to check relationships between authors and publications, filter nodes to type “Author” and “Publication”, then expand publication nodes to reveal authorship edges and verify counts.
Tips for working with larger graphs
The viewer is best with small-to-medium graphs (thousands, not millions, of triples). For larger datasets:
- Pre-filter or extract relevant subgraphs using a SPARQL endpoint or a script before loading.
- Increase layout iterations or choose a faster layout for initial overview, then refine.
- Use component filtering to focus on connected areas rather than the full graph.
Alternatives and when to switch
If your needs grow beyond inspection and visualization, consider switching to:
- Protégé — for ontology editing and reasoning.
- Neo4j or JanusGraph — for large-scale storage and fast graph queries.
- Gephi — for advanced network analysis and large graph visualization.
- Apache Jena / RDFox — for SPARQL querying and RDF processing.
Use InfoRapid KnowledgeBase Viewer as a quick visualizer and complement it with these tools for heavy-duty work.
Troubleshooting common issues
- File doesn’t open: confirm file encoding and format; try exporting to a different supported format (Turtle/RDF/XML).
- Too crowded canvas: apply filters or load a subgraph.
- Missing labels: check whether labels are provided as rdfs:label or as literals in other properties and map display settings accordingly.
Summary
InfoRapid KnowledgeBase Viewer is a practical, easy-to-use tool for quickly visualizing and exploring knowledge graphs. It’s ideal for data inspection, demos, teaching, and small-scale analysis. For heavy querying, editing, or enterprise-scale graphs, pair it with more powerful graph engines or ontology tools.
Leave a Reply