Course Introduction1-Mar-2017, Maurizio Patrignani Click to download: 010-presentation-04.pdf [5.4 MB] Teachers. Program. Exams. Data overloading. Comparison of Scientific Visualization and Information Visualization. First examples of visualization. Lectures ahead. |
Data and Information13-Mar-2017, Maurizio Patrignani Click to download: 020-data-model-04.pdf [600 KB] Structured and Unstructured data. Data transformation. Data tables. Examples data modeling and visualization. |
Visual Perception15-Mar-2017, Maurizio Patrignani Click to download: 030-vision-03.pdf [700 KB] Our vision’s principles and limitations. Peripheral and central view. Edge detection mechanisms. |
Perception of Colors15-Mar-2017 and 20-Mar-2017, Maurizio Patrignani Click to download: 040-color-02.pdf [2.7 MB] The perception of color. Chromatic aberration. Color perception. Color spaces. Colormaps. |
Perception and Cognitive Issues20-Mar-2017 and 27-Mar-2017, Maurizio Patrignani Click to download: 050-perception-01.pdf [1.9 MB] Perception abilities. Weber's law. Stevens' power law. Gestalt laws. A two stage model for visual perception: preattentive processing. |
Multivariate Data Representations27-Mar-2017, Maurizio Patrignani Click to download: 060-multivariate-04.pdf [4.3 MB] Combined views (multiple bars, stacked bars, multiple views, table lens, scatterplot matrix). Icons or glyphs (Chernoff faces, multidimensional icons). Alternative coordinate systems (parallel coordinates, star plots, star coordinates). |
Infovis on the Web - SVG03-Apr-2017, Valentino Di Donato Click to download: 070-web-dev-03.pdf [630 KB] Basic ingredients of Web data visualization. JavaScript crash course. Raster and vector graphics (properties, pros and cons). Properties and examples of SVG and HTML5 Canvas. |
Infovis on the Web - D3.js05-Apr-2017, Valentino Di Donato Click to download: 080-hands-on-d3-js-03.pdf [867 KB] Overview of JavaScript libraries. Focus on D3.js: installation, usage, tools from probability theory, other utilities, objects conversion, maps, sets, array operators, scales, example application. |
Visualization of Time Series Data10-Apr-2017, Maurizio Patrignani Click to download: 090-timeseries-04.pdf [3.5 MB] Definition of time series and temporal data. Visualization of time series (single dependent variable, multiple dependent variables). Examples and case studies. |
Design Methods, Tasks, and Evaluation12-Apr-2017, Maurizio Patrignani Click to download: 100-methods-tasks-evaluation-04.pdf [1.5 MB] Design methodologies and design choices. User tasks. Evaluation and validation (goals, difficulties, practices, guidelines). |
Interaction19-Apr-2017, Maurizio Patrignani Click to download: 110-interaction-04.pdf [2.0 MB] Classification of interaction mechanisms, goals, and timings. Examples of interaction strategies. |
Visualization in Computer Networks24-Apr-2017, Maurizio Patrignani Click to download: 120-computer-networks-05.pdf [3.9 MB] Visual analysis in the computer network domain. Motivations. Taxonomies (by stakeholder, by network abstraction, by data source). Real-world examples and use cases. Open problems. |
Graph Drawing: An Introduction26-Apr-2016, Maurizio Patrignani Click to download: 130-graph-drawing-02.pdf [1.7 MB] Graph Drawing. Graph Drawing conventions and aesthetics. The divide an conquer approach for testing planarity of a graph. |
Node-link Representations of Trees3-May-2017, Maurizio Patrignani Click to download: 140-trees-node-link-02.pdf [630 KB] Representing trees within the node-link paradigm. Layered drawings of trees. Hv-drawings of trees. |
Implicit Representations of Trees8-May-2017, Maurizio Patrignani. Click to download: 150-implicit-tree-representations-03.pdf [3.1 MB] Limitations of node-link representations. Algorithms and systems for visualizing trees using implicit representations. Treemaps (nested treemaps, cushion treemaps, cluster treemaps, squarified treemaps, ordered treemaps, quantum treemaps, Voronoi treemaps, and circular treemaps). 3D Space-filling approaches. |
Representations of Graphs and Networks with the Force-Directed Approach (Part I)10-May-2017, Maurizio Patrignani. Click to download: 160-force-directed-first-03.pdf [2.7 MB] The force-directed paradigm. The barycenter method. Spring embedders. |
Representations of Graphs and Networks with the Force-Directed Approach (Part II)15-May-2017, Maurizio Patrignani. Click to download: 170-force-directed-second-05.pdf [890 KB] Scalability and flexibility of the force-directed paradigm. Fruchterman-Reingold and Barnes–Hut algorithms. Simulating graph theoretic distances. Magnetic fields. Generic energy functions. Handling drawing constraints. |
Representations of Hierarchical Data (Part I)17-May-2017, Maurizio Patrignani. Click to download: 180-layered-first-04.pdf [3.6 MB] Algorithms for the representation of layered networks. The Sugiyama approach. Step 1: Cycle removal. Step 2: Level Assignment |
Representations of Hierarchical Data (Part II)22-May-2017, Maurizio Patrignani. Click to download: 190-layered-second-03.pdf [1.1 MB] Algorithms for the representation of layered networks. The Sugiyama approach. Step 3: Crossing Reduction. Step 4: X-Coordinate Assignment |
Orthogonal Drawings (via Network Flows)29-May-2017, Maurizio Patrignani. Click to download: 200-orthogonal-flow-03.pdf [3.5 MB] Algorithms for the representation of orthogonal drawings. The Topology-Shape-Metric approach. Extension to graphs of arbitrary degree |
Orthogonal Drawings (via Visibility Representations and Incremental Algorithms)31-May-2017, Maurizio Patrignani. Click to download: 210-orthogonal-visibility-03.pdf [680 KB] Representations of orthogonal drawings obtained from visibility representations and by incremental approaches. |
Straight-Line Grid Drawings05-Jun-2017, Maurizio Patrignani. Click to download: 220-straight-line-grid-03.pdf [600 KB] Strategies for obtaining straight-line drawings of planar graphs in the grid. Canonical orderings. The shift method of de Fraysseix-Pach-Pollack and the realizer method of Schnyder. |
Visualizing Large Graphs12-June-2017, Maurizio Patrignani. Click to download: 230-large-graphs-05.pdf [3.2 MB] Strategies for the visualization of massive amount of data providing both overview and details. Alternate between views. Combine different views. Filtering and clustering principles. Three-dimensional and two-dimensional representations of clustered graphs. Hybrid representations. |