Geometry as Data Structure and Visualization

Introduction to Geometry as Data Structure and Visualization

Class, Computational Geometry, Data Structure, Projection, Remap, Interpolation, Generalization, Gestalk Principles, Principles of Graphical Integrity, Bertin’s Visualization design space

1) File format(CSV , JSON, GeoJSON, Image)
2) Geometry as Data Structure
2) Remap, Interpolation, Generalization
3) Object-oriented programming(OOP) pattern
4) Visualization


Structured data- CSV
Semi-structured data- JSON, GeoJSONlink
Image: Remote Sensing, DEMlink

Programming Paradigm / Typescript Classes
Software design pattern:
link, (GoF) Design Patterns
Inheritance (object-oriented programming):

Geometry Class as data structures
DataStructure Vector: link
DataStructure Color: link
Point object: link
Line object: link
Polyline object: link
Polygon object: link


R Space — R1 /R2 /R3 /Rn Space

Coordinate system
Geographic coordinate system

Projection demo: link

Remap: Bar Chart / Scatter plot
Interpolation (easing): link

Scaling, Clustering, Aggregation, Clustering and so on

Gestalk Principles: link
Grouping: Proximity — Similarity — Enclosure

Bertin’s Visual design space: link
Mark / point / lines / area
Channels / position / value / texture / color / orientation / shape

Principles of Graphical Integrity: link
Lie Factor / Data-Ink Ratio / Chartjunk / Graphical Integrity

How coronavirus charts can mislead us — link

45-ways-to-communicate-two-quantities: link

Nightingale-mortality: link
Domain knowledge / Analysis / Repeated measurements /
Speaking with data and persuading with visual insight

! not the beautiful but the meaningful


Introduction to Computational Design:
Data, Geometry, and Visualization Using Digital Medialink



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NJ Namju Lee

Computational Designer at NJSTUDIO, and Software Engineer at ESRI