1 Storylines (Movie Plots)

Origin Notes: This dataset was initially collected by Yuzuru Tanahashi, then stored on his homepage at UC Davis which was lost. Through the help of personal connections at UC Davis, we were luckily able to recover the dataset. graph features handled: Clusters (pre-existing), Dynamic, Dynamic (discrete), N-layers Graph features in papers: dynamic,dynamic (discrete),layered graphs,n-layers,clusters (pre-existing),dynamic,dynamic (discrete),layered graphs,n-layers,clusters (pre-existing),dynamic (discrete),layered graphs,n-layers,clusters (pre-existing),compound graphs,layered graphs,n-layers Origin Paper: Design Considerations for Optimizing Storyline Visualizations (https://www.notion.so/Design-Considerations-for-Optimizing-Storyline-Visualizations-8a8056ac18c748dd9cdbcd1766addd3f?pvs=21) Originally found at: UC Davis’ website, personal page Size: 698-24056 nodes, 357-23088 edges Number of Graphs: 6 format: NA Appeared in years: 2015,2013,2012,2016,2017,2020,2022 Type of Collection: Uniform Benchmark is it stored properly?: No must be analyzed: Yes In repo?: Yes Related to Literature - Algorithm (1) (Dataset tag relations): Crossing Minimization in Storyline Visualization (https://www.notion.so/Crossing-Minimization-in-Storyline-Visualization-2953ec267f7f468bb4b306faee452952?pvs=21), Sequence Braiding: Visual Overviews of Temporal Event Sequences and Attributes (https://www.notion.so/Sequence-Braiding-Visual-Overviews-of-Temporal-Event-Sequences-and-Attributes-54be1011c0324f04bcc2bafa58b89859?pvs=21), Stratisfimal Layout: A modular optimization model for laying out layered node-link network visualizations (https://www.notion.so/Stratisfimal-Layout-A-modular-optimization-model-for-laying-out-layered-node-link-network-visualiza-77fd27b418d64ef6ab570cffd0ec4a24?pvs=21), Design Considerations for Optimizing Storyline Visualizations (https://www.notion.so/Design-Considerations-for-Optimizing-Storyline-Visualizations-7d26fa762ce44baa96b51c7361bfed17?pvs=21), StoryFlow: Tracking the Evolution of Stories (https://www.notion.so/StoryFlow-Tracking-the-Evolution-of-Stories-a5e01c41d9ce44769f4cd154d4c293e3?pvs=21), Computing Storyline Visualizations with Few Block Crossings (https://www.notion.so/Computing-Storyline-Visualizations-with-Few-Block-Crossings-cb4a181c2cb0461f9cb01232dda5f19d?pvs=21), An Efficient Framework for Generating Storyline Visualizations from Streaming Data (https://www.notion.so/An-Efficient-Framework-for-Generating-Storyline-Visualizations-from-Streaming-Data-d06da0be3b5244b791f30c22ff2b7277?pvs=21) cleaned format?: Yes duplicate?: No link works?: No Added in paper: Yes OSF link json: https://files.osf.io/v1/resources/j7ucv/providers/osfstorage/64d90e9794a6be0ec012e7cb Origin paper plaintext: Design Considerations for Optimizing Storyline Visualizations Page id: 5d9ea7cbfc2c4a6c88a7ca1bf32c67d7 unavailable/skip: Yes Cleaned ALL data: No OSF link gexf: https://files.osf.io/v1/resources/j7ucv/providers/osfstorage/64d948c6803e0c0bf6558be7 OSF link gml: https://files.osf.io/v1/resources/j7ucv/providers/osfstorage/64d96e0b1101aa0ea36a0bd4 OSF link graphml: https://files.osf.io/v1/resources/j7ucv/providers/osfstorage/64d971960c2b4d0f64386417 first look: No sparkline data: {‘min’: 698, ‘max’: 24056, ‘step_size’: 5000, ‘num_bins’: 5, ‘bins’: [0, 5000, 10000, 15000, 20000], ‘num_nodes’: [4, 0, 0, 0, 1]} Related to Literature - Algorithm (Dataset tag relations) 1: An Efficient Framework for Generating Storyline Visualizations from Streaming Data (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/An%20Efficient%20Framework%20for%20Generating%20Storyline%20Vi%200a3f35ebac3f468cb9c3adee03f62a06.md), StoryFlow: Tracking the Evolution of Stories (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/StoryFlow%20Tracking%20the%20Evolution%20of%20Stories%2085d6352e70a54f3e8840adcfea70363a.md), Design Considerations for Optimizing Storyline Visualizations (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Design%20Considerations%20for%20Optimizing%20Storyline%20Vis%200a518ed402154bdcb136759d50e09b1b.md), Crossing Minimization in Storyline Visualization (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Crossing%20Minimization%20in%20Storyline%20Visualization%20adc579d114c9412e8dad9e068e18d960.md), Computing Storyline Visualizations with Few Block Crossings (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Computing%20Storyline%20Visualizations%20with%20Few%20Block%20%20852c12c9b8674d4482a281a689b27496.md), Sequence Braiding: Visual Overviews of Temporal Event Sequences and Attributes (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Sequence%20Braiding%20Visual%20Overviews%20of%20Temporal%20Eve%204dfe62dc294b4ef1b453ecf09be2ea0f.md), Stratisfimal Layout: A modular optimization model for laying out layered node-link network visualizations (../Benchmark%20sets%200cc6b5e454304aec98f3b59b1a720476/Literature%20ad87f14e7097454fb2f784e2c8a2797a/Literature%20-%20Algorithm%2012e01bfc60a84007aa7d2d34293e123d/Stratisfimal%20Layout%20A%20modular%20optimization%20model%20f%20ad2a312108774bad92f36064f5fd59ed.md)

2 Body

Statistics

Descriptions from Literature

From “An efficient Framework for Generating Storyline Visualizations from Streaming Data”:

The datasets we used for this study were the three movie datasets (Star Wars, The Matrix, and Inception) [25] which have been used in previous research as benchmark datasets for measuring layout legibilities. Star Wars consists of 14 entities and 200 time steps. The Matrix consists of 14 entities and 100 time steps. Inception consists of 8 entities and 490 time steps.

From “Design Considerations for Optimizing Storyline Visualizations” (origin paper):

The basic form of the data applied in this visualization is simply a chronological list of interactions between various characters. These interactions between characters can be separated into a series of interaction sessions, each session representing the time span of a set of interacting characters. More precisely, we define an interaction session as a unit which holds three attributes: • initiation time, • duration, and • members. Initiation time corresponds to the time when the interaction session begins. Duration corresponds to the duration of the interaction session. Members corresponds to the set of characters involved in the interaction session. Each interaction session represents a time slot in the data where its members are interacting. Note that any change in the formation of members (e.g., a character leaving or joining) indicates a separate interaction session.

Example Figures

From “An Efficient Framework for Generating Storyline Visualizations from Streaming Data”:

From “StoryFlow: Tracking the Evolution of Stories”:

From “Crossing Minimization in Storyline Visualizations”: