Geometry as Data Structure and Visualization

Introduction to Geometry as Data Structure and Visualization

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

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

DATA STRUCTURE

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):
link

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

VISUALIZATION

R Space — R1 /R2 /R3 /Rn Space

Coordinate system
Geographic coordinate system

Projection
Projection demo: link

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

Generalization
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

ADDITIONAL NOTE

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

Computational Designer at NJSTUDIO, and Software Engineer at ESRI

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