DSS Lection 8 Fundamentals of Data Visualizations and Visual Analytics

These vocabulary flashcards cover the definitions, key elements, spaces, and challenges associated with data visualization and visual analytics based on the lecture notes.

Visualization

The use of interactive visual representations of data to amplify cognition (Card, $2008$).

Primary Goal of Data Visualization

To make data more accessible and easier to interpret, allowing users to identify patterns, trends, and outliers quickly.

User (Key Element)

One of the four key elements of data visualization, focusing on who will be using the tool, what they care about, and why they care about those things.

Task (Key Element)

Focuses on what tasks need to get done, how often questions need to be answered, and what quality and timeliness of information is required.

Data (Key Element)

Focuses on identifying which data is relevant to the job and what needs to be done to make use of it.

Performance (Key Element)

Concerns how the final deliverable behaves, including dimensions, resolution, and data refresh frequency.

Temporal Data Abstraction

The common goal of temporal analysis tasks to reduce workload when computing visual representations and to keep perceptual efforts low for interpretation.

Dashboards

Interactive platforms that combine multiple visualizations such as charts, graphs, and maps.

Top-down Story

A visualization design that starts by showing all or most of the data and then drills down into different aspects of the overall visualization.

Visual Analytics

The science of analytical reasoning facilitated by interactive visual interfaces (Thomas and Cook, $2005$).

Information Space

The space concerned with modeling, abstracting, and characterizing the sources of information to be studied.

Computing Space

The space dealing with encoding and storing internal representations of elements and the computational operations carried out on them.

Representation Space

The space that makes internal representations accessible to users using interactive visual representations (IVRs).

Interaction Space

The space where the dyad of action-reaction takes place and perception connects to the mental space.

Mental Space

The space concerned with internal mental events and operations of human analysts.

Visualization Pipeline

The series of steps needed to convert raw data into a usable form, specifically transforming source data to data tables, data tables to visual structures, and imposing view transformations.

Complexity (Challenge)

A challenge where highly complicated visualizations appear cluttered or require extensive user training to avoid misinterpretation.

Bias (Challenge)

The risk that visualizations or their underlying data are intentionally or unintentionally distorted, potentially compromising the credibility of analyses.