Dataface Tasks

chart library

Purpose

Differentiated chart system, interaction language, and style quality bar. This workstream owns the chart rendering layer: the set of chart types (line, bar, area, scatter, KPI, table, etc.), their visual design language, interaction behaviors, and the overall aesthetic quality bar that makes Dataface dashboards look distinctive and professional. RJ Andrews leads the design direction. The chart library renders within dft-core's rendering pipeline but owns the design decisions: color palettes, typography, animation, responsiveness, and visual grammar. Adjacent to dft-core (which provides the rendering infrastructure) and dashboard-factory (which relies on chart-library quality for template polish).

Owner

  • Data Graphics Designer and Engineer (RJ Andrews)

Initiatives

Tasks by Milestone

A runnable prototype path exists for visual language, chart defaults, interaction behavior, and differentiated styling, with concrete artifacts that prove the flow works end-to-end in the current codebase. Core assumptions are documented, known constraints are explicit, and the team can explain what is real versus mocked without ambiguity.

Internal analysts can execute at least one weekly real workflow with a stable basic chart batch in the 5T Analytics environment, without bespoke engineering intervention for every chart. M1 proves the functional chart foundation: the core chart types, working examples, and enough reliability to support repeated analyst use.

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The chart library has distinct style packages, evaluation ownership, reusable design assertions, semantic-type-aware behaviors, exposed and documented chart properties, and a good table chart baseline. The system is coherent enough for regular use by multiple internal teams and initial design partners, with a predictable response loop for issues and requests.

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Launch scope for the chart library is complete, externally explainable, and supportable: starter dashboard composition patterns exist beyond the playground, data-informed chart properties are driving more of the default behavior, documentation is publishable, and operational ownership is explicit. Remaining gaps are non-blocking, risk-assessed, and tracked as post-launch follow-up rather than unresolved launch debt.

Post-launch stabilization is complete for visual language, chart defaults, interaction behavior, and differentiated styling: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

  • Regression prevention and quality gates — Add or enforce regression gates around chart default behavior so release quality is sustained automatically.
  • Sustainable operating model — Document and adopt sustainable operating model for interaction/accessibility polish across support, triage, and release…
  • v1.0 stability and defect burn-down — Run stability program for visual language system with recurring defect burn-down and reliability trend tracking.
  • Conditional Formatting — Implement conditional formatting primitives for the graph library to encode thresholds, exceptions, and trend states vi…

v1.2 delivers meaningful depth improvements in visual language, chart defaults, interaction behavior, and differentiated styling based on observed usage and retention signals, not just roadmap intent. Enhancements improve real customer outcomes, and release readiness is demonstrated through metrics, regression coverage, and clear migration guidance where relevant.

Long-horizon opportunities for visual language, chart defaults, interaction behavior, and differentiated styling are captured as concrete hypotheses with user impact, prerequisites, and evaluation criteria. Ideas are ranked by strategic value and feasibility so future investment decisions can be made quickly with less rediscovery.