2007/4/3CMSC734 Information Visualization1 Network Visualization by Semantic Substrates Ben Shneiderman and Aleks Aris Presented by: Morimichi Nishigaki, Galileo Namata (Slides borrowed from Ben Shneiderman and Aleks Aris)

2007/4/3CMSC734 Information Visualization2 Review Network Vis. Strategies Node-link Diagrams Force-directedFamiliar Layout Circular layout Other Diagrams Temporal Placement Matrix-based Clustering

2007/4/3CMSC734 Information Visualization3 Force-directed >30% Familiar Layout ~30% Circular Layout ~15% Node layout strategy First 100 in visualcomplexity.com Statistics on Strategies

2007/4/3CMSC734 Information Visualization4 Collection of Challenges What are the challenges? –C1) Basic networks: nodes and links –C2) Node labels –C3) Link labels –C4) Directed networks –C5) Node attributes –C6) Link attributes Recurring Theme: More nodes and links = Harder!!!

2007/4/3CMSC734 Information Visualization5 C1) Basic Networks – Nodes and Links Power Law Graph 5000 nodes Uniformly distributed Power Law Graph, Linyuan Lu Vizster, Heer et al. Source: (135) Social friendship network 3 degrees from Heer 47,471 people 432,430 relations Source: (97)

2007/4/3CMSC734 Information Visualization6 C2) Node Labels Adding labels –e.g. article title, book author, animal name –Nodes overlap with other nodes –Nodes overlap with links Internet Industry Partnerships, Valdis Krebs Source: (168) nodes

2007/4/3CMSC734 Information Visualization7 C3) Link Labels Adding Labels e.g. Strength of connection, type of link Challenges: Length Space Belongingness Distinction from other labels & other types of labels Netscan, Marc Smith Source: (127)

2007/4/3CMSC734 Information Visualization8 C4) Directed Networks Direction –arrows –labels –thickness –color Source: (127) Yeast Protein Interaction SeeNet, Becker et al. Source: [1] Becker et al.

2007/4/3CMSC734 Information Visualization9 C5 & C6 Node & Link Attributes Types: –Categorical (e.g. mammal/reptile/bird/fish/insect) –Ordinal(e.g. small/medium/large) –Numerical (e.g. age/weight) Values of node attributes indicated by node size and shape Values of link attributes indicated by a letter and color CIA World Factbook Visualization, Moritz Stefaner Source: (192)

2007/4/3CMSC734 Information Visualization10 C1 ~12% C4 ~10% C2 ~66% Challenges First 100 in visualcomplexity.com Statistics on Challenges C5 ~10% C6 ~2% C1) Basic networks C2) Node labels C3) Link labels C4) Directed networks C5) Node attributes C6) Link attributes

2007/4/3CMSC734 Information Visualization11 High Priority Tasks C1) Basic Network T1) count number of nodes and links T2) for every node, count degree T3) for every node, find the nodes that are distance 1, 2,… T4) for every node, find betweenness centrality T5) for every node, find structural prestige T6) find diameter of the network C2-3) Label T9) for every node/link, read the label T10) find all nodes/links with a given label C5-6) Attributes C4) Directed links Variations on T1-10: count # of nodes in each category T11)find links b/w nodes with deferent attribute values T12)find the proportion links from a node that go to each category for every node T13) for a pair of nodes, find paths with the lowest cost T14) find links with connection strength greater than 0.5 Variations on T1-10: shortest paths, etc.

2007/4/3CMSC734 Information Visualization12 Two Principles Layout based on user-defined semantic substrates: non-overlapping regions –Group nodes into regions According to an attribute Categorical, ordinal, or binned numerical –In each region: Place nodes according to other attribute(s) Adjustable sliders to control link visibility: limit clutter –Give users control of link visibility

2007/4/3CMSC734 Information Visualization13 Legal Precedent Example Department of Government and Politics, Univ. of Maryland – Contains 2780 federal judicial cases from on “regulatory takings” –Regulatory taking - a government regulates a property that the regulation effectively amounts to an exercise of the government's eminent domain power without divesting the property's owner of title to the property.

2007/4/3CMSC734 Information Visualization14 Before Semantic Substrates

2007/4/3CMSC734 Information Visualization15 After Semantic Substrates NVSS 1.0 Demo –And now to our featured presentation … –Please pardon our resolution. This is as big as our screen gets.

2007/4/3CMSC734 Information Visualization16 After Semantic Substrates – NVSS 1.0

2007/4/3CMSC734 Information Visualization17 NVSS Edges

2007/4/3CMSC734 Information Visualization18 NVSS Filter

2007/4/3CMSC734 Information Visualization19 Supreme Vs. Circuit Court

2007/4/3CMSC734 Information Visualization20 Circuit Court Citations 9 th Circuit Court Federal Circuit Court

2007/4/3CMSC734 Information Visualization21 Other Examples: To & CC list co-recipients UMD ORG EDU COM Female Male Low Med High Jr Med Sr

2007/4/3CMSC734 Information Visualization22 Other Examples: Foodwebs Mammals BirdsInsects Reptiles Fish

2007/4/3CMSC734 Information Visualization23 Discussion Advantages –Location conveys meaning, interpretable –Instant perception of different types of nodes their relative number connections between different groups of nodes Limitations –Beyond 5 regions becomes challenging –Constraint on nodes interferes with aesthetics

2007/4/3CMSC734 Information Visualization24 In Case You Forgot …

2007/4/3CMSC734 Information Visualization25 Now where can I get this amazing tool? Lab Project Demo

2007/4/3CMSC734 Information Visualization26 Supplementary

2007/4/3CMSC734 Information Visualization27 Other “Semantic Substrates” JambalayaPivotGraph Pretorius et al. D-Dupe

2007/4/3CMSC734 Information Visualization28 PivotGraph