Storytelling and Visualization

Authorship refers to writing or creating a book, article, or document, or the creator of a work of art according to The Oxford English dictionary, especially with reference to an author, creator or producer. For our purposes, we will adopt a definition of author described by Rodgers, "An author is best described as an individual solely responsible for the creation of a unique body of work". Hullman et al. state, "Story creation involves sequential processes of context definition, information selection, modality selection, and choosing an order to effectively convey the intended narrative".
An author is best described as an individual solely responsible for the creation of a unique body of work.

Presenting the findings of a qualitative study of undergraduate writers at The City University of New York, Hullman explores student perspectives on models of authorship, the relationships between these models and student experiences of authorship in different writing situations, and proposes the importance of distinguishing between the multiple models and definitions of authorship and the rhetorical contexts associated with each. Rodger develops a qualitative study of 800 students on the definition of authorship and their rhetorical contexts over a one-hour interview. Students defined authors as "[people] who see writing as being beyond a hobby", and as a term that should be applied only to those individuals for whom writing is "something he or she has to do", "a career", or "an act that will lead to something being published".

All papers in this section focus on authoring-tools for storytelling. Wohlfart creates new volume visualization stories for medical applications. Gershon and Cruz present general storytelling for information visualization. Kuhn, Lee and Plowman all develop unique creator tools for storytelling visualization.

It is important to note that our survey is not simply a list of papers. Individual papers are summarized according to a special methodology. This process connects related papers together such that the connections and relationship to previously published literature is made clear.

3.1. Authoring-Tools for Linear Storytelling

The literature in this sub-section focus on visual designs for authoring in a linear style that is prescribed, automatic, or semi-automatic (as opposed to interactive) or decided by the users. In other words, creators are provided with assets to formulate a linear story.

Gershon and Page state that storytelling enables visualization to reveal information as effectively and intuitively as if the viewer were watching a movie. They introduce the concept of storytelling and presents advantages of storytelling.

One example presents a situation in which a number of enemy positions surround a school with children trapped inside as de facto hostages as the crossfire fills the space overhead and both sides move toward confrontation. Gershon and Page is based on previous work of Denning and explain the usage of storytelling in information visualization.

Lu and Shen propose an approach to reduce the number of time steps that users required in order to visualize and understand the essential data features by selecting representative datasets. They design a flexible framework for quantifying data differences using multiple dissimilarity matrices. A new visualization approach that filters data analysis results, which is achieved by measuring the degree of data similarity/difference and selecting important datasets that contain essential data features. See Figure 4.

They interactively select representative datasets that include a significant portion of features of scientific data, whose data distribution requires more analysis than time sequence, reduces the amount of data to necessarily visualize and still keeps the essential data information. This can be used to improve the efficiency of time-varying data visualization.

An interactive storyboard is used to visualize and explore the overall content of time-varying datasets through composing an appropriate amount of information that can be efficiently understood by users.

Lu and Shen is based on the previous work of time-vary visualization and design a general method for comparing data dissimilarities. They do not require a dense sampling frequency to capture the object evolution and their work is not limited to specific feature models, such as geometry or interval volumes, and their attribute designs.

Storytelling, in the context of this article, deals with the core of information visualization by extracting relevant knowledge and enhancing its cognition. Cruz et al. present generative storytelling as a conceptual framework for information storytelling. They create stories from data fabulas using computer graphics as a narrative medium. Data fabulas are a set of time-ordered events caused or experienced by actors.

A story is formed by characters. It involves the representation of the fabula's actors and the definition of a temporal structure. The engine transforming a fabula into story consists of two models. The event model creates a story timeline and an action model creates a set of actors behaviours. For example an empire's decline visualizing western empire's decline in the 19th and 20th centuries. See Figure 5.

Cruz et al. is based on previous work of narrative theory and presents generative storytelling as a conceptual framework for information storytelling.

3.2. Authoring-Tools for User-Directed and Interactive Storytelling

A large body of research has been carried out for authors wishing to create their own user-oriented or interactive stories. This literature focuses on interactive, user-driven authorship (as opposed to automatic or semi-automatic authorship). Storytelling is a relatively new form of interactive volume visualization presentation. Wohlfart explores the usefulness of storytelling in the context of volume visualization. He presents a story telling model and divides the concept of volumetric storytelling into story authoring and storytelling constituents. He presents a volumetric storytelling prototype application, which is based on the RTVR (real time volume redering) Java library for interactive volume rendering. See Figure 1. The storytelling model contains a range of hierarchy levels, in top-down order, which are: story node, story transitions, story action group, story action atoms. See Figure 1. The story nodes form the corner marks of the story and store the state of the whole scene. Story nodes are connected by story transitions, each consisting of one or multiple story action groups. Each story action group stores the scene changes relative to its preceding action group (or story node).

The story authoring process contains two steps: a story recording process and a story editing process. The outcome of this recording process is a raw prototype of a story told through volume visualization. In the story editing step, this raw story is refined until the final story outline is reached.

This process presents a volume visualization following the storytelling model. And the key feature is interaction, including viewing interaction, representing interaction and data interaction. Wohlfart and Hauser also discuss the paradoxical integration of storytelling and interaction, also called the narrative paradox.

Figure 1 shows an image sequence taken from a sample linear volumetric story visualized with their prototype. The distinct story nodes refer to the key events in the story, which provide an overview first, then details on specific features in the dataset, and at the end a conclusion made by the story author. The necessary story transitions are represented as orange arrows from one story node to the next and are animated in the prototype application. The story consumer may take over some story parameters (e.g., camera angle) already during playback or at the end of the story to further investigate the dataset.

This story guides the observers through the visualization, puts the contained visual representations into context with each other and finally introduces them to important features in the data. See Figure 6. Wohlfart is based on previous work of volume visualization  and interactive visualization and combine these concepts together to develop a storytelling model for volume visualization.

Geological storytelling is a novel graphical approach for capturing and visualizing the reasoning process that leads to a geological model. Lidal et al. present a sketch-based interface for rapid modelling and exploration of various geological scenarios. The authors present a concept that handles sketching processed over time and a novel approach for externalizing the mental reasoning process. The process can be presented and evaluated. The geological storytelling model contains three main parts. See Figure 7.

The canvas is a sketch-based interface where the geologist can draw the geological story on a 2D seismic slice backdrop, utilizing a pen and paper interaction style. The StoryTree is a tree graph representation of all the geological stories, each with its own subtree of story nodes. Individual story nodes can be selected for editing in the canvas. One or more complete story trees can be selected for playback or comparative visualization in the InspectView. The InspectView serves two purposes. First, it is a view where a story can be played and evaluated. In addition, multiple stories can be played synchronized for a side-by-side visual comparison.

The data-based story is recorded in SketchStory as a sequence of charts in XML files. The charts are linked with specific sketch gestures. The presenter draws an example icon and then draws a sketch gesture for chart invocation. Sketchstory recognizes the gesture and creates the corresponding chart. Lee et al. is based on previous work for storytelling of information visualization and sketch-based interaction, and develops the SketchStory system to enhance storytelling in a presentation.

Lidal et al. is based on a previous storytelling model for scientific visualization and develops a storytelling model for geological visualization.

Lee et al. present SketchStory, a data-enabled digital white board to support real-time storytelling. It enables the presenter to stay focused on a story and interact with charts created during presentation. See Figure 8.

Storytelling is one of the most impactful ways to teach, learn, and persuade. Lundblad and Jern present geovisual analytics software with integrated storytelling. It can be applied to large spatial-temporal and multivariate data through dynamic visual user interfaces.

Using a scatter plot matrix gives the analyst a good overview of all correlations between the selected indicators. The analyst can use the scatter plot matrix as an overview and then steer the scatter plot for interesting detailed combinations over time. See Figure 9. The distribution plot presents a special visualization technique that displays the variation within individual European countries. The Motala River map is visualized for different stories divided into different layers, such as a glyph layer, stream layer, polygon layer and background map layer. It shows the local and total water flow, and water path from source to ocean.

Lundblad and Jern is based on the previous work of the storytelling concept and work of web-based geovisual tools, integrates storytelling with geovisual analytics software.

3.3. Authoring-Tools for Parallel Storytelling

In this category of literature, authors create stories in parallel. In other words there may be multiple authors working in parallel i.e., simultaneously for the final outcome. This is opposed to a single author as in the previous subsection.

GeoTime events are recorded in x, y, t, coordinate space. This is used in observation analysis and can make a major contribution to a storytelling model. Eccles et al. presents the GeoTime stories prototype that combines a geo-spatial map with narrative events to produce a story framework. See Figure 10. This system provides functions for simple pattern detection in simultaneous movement activity. These functions look at possible interactions between people within the narrative, the speed at which they travel, and the type of location that they visit. Narrative text authoring enables the analyst to create and present stories found within the data. The story window displays this data as well as discovered patterns. The system enables multiple stories to connect together if they follow a linear flow. Also simultaneous narratives can be shown in a single image for a direct comparison.

This system uses a similar approach to Sense.us. Instead of using a blog-type discussion workflow for adding text, Geotime is designed for authoring a single story and annotations are integrated into the data itself.

The CodeTimeline visualization by Kuhn and Stocker enables developers who are new to a team to understand the history of the system they are working on. Designed to show a development team's tribal memory, the software offers a partial replacement for exhaustive documentation. See Figure 11.

A collaboration view presents visualizes code ownership and historical patterns in collaboration. A sourcecloud flow view presents a word cloud of added and removed vocabulary between software releases. Lifetime events can be added by users as a frame of reference in each of the visualizations. This method of linking also enables new users to learn more about the history of the software development. These events can be include anything from email threads to pictures of the team during work.

Prior to Kuhn and Stocker, Ogawa presents "software evolution storylines" and "Code Swarm", which focus on the interactions between developers on projects but do not focus on telling a story about the software history. Codebook, a concept presented by Begel et al., outlines a social network that connects software engineers with their shared code base. It encourages interaction with their code and others, enabling a broader understanding of the project they share with other developers.