Lecture by Prof Alex. Introduction to Information Visualization. Why study it?
No lab for 1st week of course.
Lecture by Prof Alex. Visual perspectives and mechanics of visual perceptions.
Course requirements and expectations. An overview of data visualization with the what(data) - why(task) - how(idiom) model. Workshop on big picture questions.
Dataset types — tables, charts, networks, fields, geometry, hiereachies. Data scales — nominal, ordinal, interval, ratio. Data ordering — sequential, diverging, cyclic.
Introduction to how the web draws graphics, and the SVG specification. Important foundation for D3 labs next week. Web dev perspectives.
Connect to a simple endpoint API and print out the data in a table. Basic refresher on skills that you will need moving forward.
Why are people using data viz? We'll analyze by looking at a high-level framework of actions and targets. Actions: Analyze, search, query, etc. Targets: Trends , outliers , features, etc.
4 levels of visualization validation: domain/problem → data/task abstraction → viz idiom → algorithm / technology. Case studies and examples.
Introduction to D3 (Data Driven Documents), the defacto data visualization library for the web. Toolchains and other libraries. Selections, domains, ranges, axes. Enter, update, exit - design pattern for glassy transitions.
Create a simple bar chart generated by code and dataset from data.gov.sg
Defining how visualizations are composed of marks and channels. Analyzing the effectiveness of visual channels through accuracy, discriminability, salience, separability.
D3's geo projection library. GeoJSON and TopoJSON formats. Choropleth visualization. Useful for charts with a geospatial component.
Create a choropleth population map with data from data.gov.sg
Color: perception, specification and use. How the eye sees color. Colorspaces. Implications for color use as a visualization channel.
Force simulations and network diagrams in D3. Useful for showing datasets which are in a graph-like format.
Force network diagram from sample covid tracing data.
Kontinentalist, an award winning data visualization studio based in Singapore, will share how they approach their gorgeous work from both a technical and design perspective.
Visualization critiques and proposal presentation (milestone 1)
A deeper dive into various different visualizations that are used for tabular data. Bar, line, scatterplot, streams, etc. Use case examples.
Hierarchical / network chart types. Force directed networks, treemaps, sankeys and arc diagrams. Use case examples.
Visualization critiques and proposal presentation (milestone 1)
Spatial / geospatial chart types. Choropleth, hexbins, isocontours, etc. Use case examples.
Techniques to consider for improving visualizations. Manipulating views - changes, selection and navigation. Faceting and layers. Focus + context (embedding).
Leaflet, 2.5D and 3D geospatial viz. Building a simple viz layer on top of a raster base map.
Geospatial viz (PSI data from assignment 1) on OneMap map base
SLA guest lecture on One Map. SLA engineers will talk about their geospatial projects, and the tools they use to build them, e.g.Cesium and CityGML for 3D map applications.
Guidelines on 3D use, animation and interaction. Latency and feedback. A summary and future perspectives.
Final lecture.
Project Development. Consultation by request. No lecture.
Final project presentations (part I)
Individual quiz assessment for this course (35%)
Final project presentations (part II)