trends-dashboard

You can visualize TIPS project data by aggregating trend-scout, value-model, report, and catalog outputs into a self-contained HTML dashboard. This process consolidates scattered project files into an interactive visualization that opens directly in a browser.

Building an interactive HTML visualization from JSON data is best handled by consuming tips-project.json and related output files to render a complete overview. This approach maps Trends, Implications, Possibilities, and Solutions into a multi-tab exploration interface without external dependencies.

Yes, you can generate D3 visualizations without external dependencies by rendering a self-contained HTML file. The dashboard reads local project JSON files to produce a standalone visualization that supports multi-tab exploration and data-grounded storytelling.

To map Trends, Implications, Possibilities, and Solutions visually, the dashboard renders a companion TIPS graph alongside Overview, Scout, Value Model, Report, and Catalog views. This graph surfaces score, BR values, themes, and pipeline status to support stakeholder alignment.

The trends-dashboard generator works across Trend Scout, Value Model, Report, and Catalog workflows. It consumes trend-scout-output, tips-value-model.json, and tips-trend-report-claims.json to render a complete visual overview for project exploration.

A limitation of a self-contained HTML dashboard is that it relies entirely on the pre-aggregated JSON data inputs. It is designed for visual exploration and storytelling rather than live data processing, meaning the visualization reflects static snapshots of your project pipeline status.