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Network Visualization by Semantic Substrates Aleks Aris Ben Shneiderman.

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Presentation on theme: "Network Visualization by Semantic Substrates Aleks Aris Ben Shneiderman."— Presentation transcript:

1 Network Visualization by Semantic Substrates Aleks Aris Ben Shneiderman

2 Outline Graph Drawing Aesthetics Graph Drawing Aesthetics Node Placement Methods Node Placement Methods Challenges of Network Visualization Challenges of Network Visualization Semantic Substrates Semantic Substrates Demo Demo Questions & Answers Questions & Answers

3 Graph Drawing Aesthetics Minimize edge crossings Minimize edge crossings Draw links as straight as possible Draw links as straight as possible Maximize minimum angle Maximize minimum angle Maximize symmetry Maximize symmetry Minimize longest link Minimize longest link Minimize drawing area Minimize drawing area Centralize high-degree nodes Centralize high-degree nodes Distribute nodes evenly Distribute nodes evenly Maximize convexity (of polygons) Maximize convexity (of polygons) Keep multi-link paths as straight as possible Keep multi-link paths as straight as possible … Source: [9] Davidson & Harel

4 Node Placement Methods Node-link diagrams Node-link diagrams –Force-directed –Geographical maps –Circular layouts One or multiple concentric One or multiple concentric –Temporal layouts –Clustering –Layouts based on node attributes (later) Matrix-based representations Matrix-based representations

5 Force-directed Layout Source: Also known as: Spring Also known as: Spring Spreads nodes Spreads nodes –Minimizes chance of node occlusion

6 Geographical Map Familiar location of nodes Familiar location of nodes Source: (100)www.visualcomplexity.com SeeNet, Becker et al.

7 Circular Layouts (1 circle) Ex: Schemaball Ex: Schemaball –Database schema –Tables connected via foreign keys Source: Schemaball, Martin Krzywinski

8 Circular Layouts (concentric) Source: (26)www.visualcomplexity.com Radial Tree Viewer, Nihar Sheth

9 Circular (concentric) & Temporal Hudson Bay Food Web Source:

10 Temporal Layout Source: [16] Garfield, “Historiographic mapping of knowledge…”

11 Clustering Source: (85)www.visualcomplexity.com Vizster, Heer et al.

12 Hierarchical Clustering Source: [33] Schaffer, et al.

13 Matrix-based Layout Ex: VisAdj (Ghoniem, et al.) Ex: VisAdj (Ghoniem, et al.) –column: source vertex –row: target vertex Source: [17] Ghoniem et al., IEEE /04 VisAdj, Ghoniem et al.

14 Challenges of Network Visualization C1) Basic networks: nodes and links C1) Basic networks: nodes and links C2) Node labels C2) Node labels –e.g. article title, book author, animal name C3) Link labels C3) Link labels –e.g. Strength of connection, type of link C4) Directed networks C4) Directed networks C5) Node attributes C5) Node attributes –Categorical (e.g. mammal/reptile/bird/fish/insect) –Ordinal(e.g. small/medium/large) –Numerical (e.g. age/weight) C6) Link Attributes C6) Link Attributes –Categorical (e.g. car/train/boat/plane) –Ordinal(e.g. weak/normal/strong) –Numerical (e.g. probability/length/time to traverse/strength)

15 C1) Basic Networks (nodes & links) Power Law Graph Power Law Graph –5000 nodes –Uniformly distributed Power Law Graph, Linyuan Lu Source: (135)www.visualcomplexity.com

16 C1) Basic Networks (continued) Social friendship network Social friendship network –3 degrees from Heer – 47,471 people –432,430 relations Vizster, Heer et al. Source: (97)www.visualcomplexity.com

17 C2) Node Labels Adding labels Adding labels –Nodes overlap with other nodes –Nodes overlap with links Internet Industry Partnerships, Valdis Krebs Source: (168)www.visualcomplexity.com250 nodes

18 C3) Link Labels Challenges: Challenges: –Length –Space –Belongingness –Distinction from other labels & other types of labels Netscan, Marc Smith Source: (127)www.visualcomplexity.com

19 C4) Directed Networks Direction Direction –arrows –labels –Thickness –color Source: (127)www.visualcomplexity.com Yeast Protein Interaction SeeNet, Becker et al. Source: [1] Becker et al.

20 C5 & C6) Node & Link Attributes Value of node attribute indicated by node shape Value of node attribute indicated by node shape Value of link attribute indicated by a letter Value of link attribute indicated by a letter CIA World Factbook Visualization, Moritz Stefaner Source: (192)www.visualcomplexity.com

21 Semantic Substrates Group nodes into regions Group nodes into regions –according to one attribute Categorical, ordinal, or binned numerical Categorical, ordinal, or binned numerical In each region: In each region: –place nodes according to other attribute(s) Advantages Advantages –Location conveys meaning, interpretable –Instant perception of different types of nodes different types of nodes their relative number their relative number connections between different groups of nodes connections between different groups of nodes Limitations Limitations –Beyond 5 regions becomes challenging –Constraint on nodes interferes with aesthetics

22 Demo

23 Thank you!

24 Questions & Answers

25

26 NVSS: Network Visualization by Semantic Substrates

27 Comparison with Fruchterman- Reingold

28 Filtering Links by source-target

29 Filtering links by time attribute (1)

30 Filtering links by time attribute (2)

31 Overlapped Links

32 Three Regions Links from District Courts Links from District Courts Indicates longevity of cases (short to long) Indicates longevity of cases (short to long) –District –Circuit –Supreme

33 Scalability 1280x x1024 1,122 nodes 1,122 nodes 7,645 links 7,645 links

34 Using a third attribute in regions 13 circuits for both Circuit and District Courts 13 circuits for both Circuit and District Courts Horizontally separated Horizontally separated Reveals that links remain mostly within a circuit although there are some across (lateral citations) Reveals that links remain mostly within a circuit although there are some across (lateral citations)


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