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Roadmap

Big Picture

Visualization Studio

Phase 1: Foundation ✅

Interactive dashboards with modern web components and real-time data binding

Data Ingestion

Phase 1: Foundation ✅

Multiple tabular formats with Delta Lake storage and data provenance

MultiQC Integration

Phase 2: Specialization ✅

Seamless integration with bioinformatics quality control reports

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Image Grid Component

Phase 2: Specialization ✅

S3-backed image galleries with configurable thumbnails and grid layout

Templates & Community

Phase 3: Templates 🚧

Reusable dashboard templates for standard bioinformatics workflows, nf-core integration, and nf-core plugin for automatic data ingestion

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Scientific Reproducibility

Phase 4: Reproducibility 📋

DOI integration, persistent access IDs, citable dashboards, full data provenance from sample to visualization

AI & Intelligence

Phase 5: Intelligence 📋

Smart dashboard creation & AI-assisted analysis

The Reproducibility Challenge

The Reproducibility Crisis in Data Visualization

  • "Dashboards disappear after papers are published."
  • "Visualizations can't be reproduced months later."
  • "Data lineage is lost between pipeline runs."
  • "Cross-experiment comparisons are impossible."

Depictio is built with FAIR principles in mind: Findable, Accessible, Interoperable, Reusable. Some challenges are already addressed today; others are part of our roadmap and will be tackled in future releases.

How Depictio will address the reproducibility crisis:

Challenge Solution
Dashboards disappear Will show in the future — persistent, queryable dashboards for cross-experiment comparison
Can't reproduce visualizations YAML-defined dashboards + traceable data — export and re-import any dashboard as code
No data lineage Will show in the future — Delta Lake time travel, auditing, and provenance
Siloed experiment data Cross-DC linking — meta-analysis across studies
Dashboards not citable Will show in the future — DOI integration, persistent access IDs, citable dashboard snapshots
No sample-to-viz traceability Will show in the future — persistent URL / access ID from sample (LabID) to pipeline to Delta
Reproducibility requires setup Will show in the future — nf-core plugin for automatic data ingestion; pre-built dashboard templates per pipeline

Current Features

Data Ingestion

  • YAML-based data ingestion via CLI (docs)
  • Polars-compatible formats (Parquet, CSV, JSON, TSV) → Delta Lake
  • S3/MinIO storage with backup/restore commands (docs)
  • MultiQC report integration (docs | #626)
  • Client-side table joining in CLI ( #634)

Dashboard Components

  • Generic components: Figure, Table, Card, Interactive (docs)
  • MultiQC components for QC reports (docs)
  • Image grid with S3/MinIO integration and configurable thumbnails ( #664)
  • Figure code mode with live preview ( #639)

Dashboard Interactivity

  • Two-panel layout with tabs ( #616)
  • Cross-DC filtering via universal linking (docs)
  • Interactive selection filtering: scatter/table selections
  • YAML dashboard import/export (docs)

Infrastructure

  • Docker + Kubernetes with Helm charts (docs)
  • Celery/Redis background processing
  • Multi-app architecture (Management, Viewer, Editor)
  • Authentication: local, Google OAuth, unauthenticated mode

Planned Features

Phase 3: Templates & Community (0-6 months)

Reusable dashboards for standard bioinformatics workflows, with a focus on nf-core community adoption.

  • Depictio templates system — pre-configured project and dashboard templates exportable/importable as YAML bundles
  • nf-core dashboard templates — one-click dashboards for nf-core pipelines (rnaseq, sarek, atacseq, methylseq, …)
  • nf-core plugin — automatically registers nf-core pipeline outputs in Depictio at run time, no manual CLI step required
  • Template marketplace — community-contributed templates with validation and screenshots
  • Schema versioning — backwards compatibility guarantees across Depictio versions

Phase 4: Scientific Reproducibility (6-12 months)

Publication-grade traceability and citation support for research outputs.

  • DOI integration — citable dashboard snapshots and persistent access IDs
  • Persistent access IDs — stable URLs per dashboard version; link from sample ID → pipeline run → Delta table → visualization
  • Data provenance — via LabID integration for pipeline versions, parameters, and timestamps
  • Static export — Quarto integration for HTML/PDF publication supplements

Phase 5: AI & Intelligence (12+ months)

  • Smart dashboard creation — describe the analysis you need; AI proposes a layout and component configuration
  • AI-assisted analysis — automated anomaly detection, visualization recommendations, and plain-language report narration
  • MCP server — expose Depictio as a tool for AI agents to create dashboards, query data, and manage projects programmatically

Visualization Modules

  • Reusable chart configurations catalog
  • High-dimensional methods (UMAP, PCA, t-SNE)
  • Omics visualizations (Volcano, MA, heatmaps)
  • JBrowse2 genome browser component

UI & Components

  • Markdown component for documentation
  • Extended interactive components (radio buttons, improved sliders, …)
  • Project creation wizard with workflow selection