Comprehensive Data Visualization Techniques and Ethical Principles

What is text visualization?

The use of interactive graphical representations to transform complex, unstructured text data into an easily interpretable format.

What is the purpose of visual text analytics?

To enable knowledge discovery via interactive graphical representations of textual data.

Why is text visualization important?

It helps structure unstructured text, aids exploration, pattern recognition, sentiment detection, and communication of findings.

What does the Bag of Words model ignore?

Ordering relationships within the text.

What is stemming in text processing?

Grouping different forms of a word into a base form.

What is lemmatization?

Converting words to their base form.

What does Term Frequency (TF) measure?

The number of times a word appears in a document.

What is a word cloud?

A visual representation where the size of words indicates their frequency.

What is a temporal visualization?

A visualization that answers the 'WHEN' question, showing events over time.

What is the goal of temporal visualization?

To understand the temporal distribution of datasets and identify trends, growth rates, or patterns.

What type of graph shows trends over time?

Line Graph.

What is a choropleth map?

A map where colors represent different data values by region.

What does a proportional symbol map represent?

Data values using symbols that vary in size.

What is network visualization?

The process of representing networks graphically to reveal structure, patterns, and relationships.

What are nodes in a network?

Entities represented in a network, such as people or websites.

What do edges represent in a network?

Relationships or interactions between nodes.

What is degree centrality?

The number of connections a node has.

What is betweenness centrality?

How often a node lies on the shortest path between others, indicating its role as a broker.

What is the purpose of using color and size in network visualization?

To meaningfully encode data dimensions.

What is a challenge in network visualization?

Scalability, as visualizing millions of nodes and edges is difficult.

What is a flow map used for?

To show the movement of people, goods, or information.

What is a space-time cube?

A visualization that adds the temporal dimension to spatial data.

What is the purpose of small multiples in visualization?

To provide a series of similar graphs for easy comparison.

What does a heat map show?

Data density or intensity using colors.

What is the role of interactivity in visualizations?

To allow users to zoom, filter, and explore details.

What is the purpose of labeling in visualizations?

To provide clarity, but too many labels can reduce readability.

What is the main application of geospatial visualization?

To analyze spatial data, such as tracking disease spread or mapping urban development.

What is a major challenge in visualizing large networks?

Scalability: Visualizing millions of nodes and edges is difficult.

What issue arises from dense networks in visualization?

Overplotting: Dense networks can become 'hairballs'.

What does interpretation bias in visualization refer to?

Visual prominence doesn't always mean importance.

What is a solution to represent time-evolving connections in networks?

Employ animation or timeline sliders for dynamics.

Name a desktop tool used for network visualization.

Gephi: Open-source, interactive visualization and analysis.

What is a common programming library for network visualization in Python?

NetworkX.

What defines hierarchical data in visualization?

Hierarchical data emphasize subordinate or membership relations between data items.

What is a leaf node in a hierarchical data structure?

Nodes with no children.

What is a treemap?

A visualization that represents hierarchical data with a set of nested shapes, showing size relative to area.

What is a sunburst chart?

A hierarchy chart that uses concentric rings to represent hierarchical levels.

What does the icicle chart display?

Hierarchical data using stacked rectangles, where width corresponds to a quantitative value.

What ethical principle is crucial in data visualization?

The responsibility to be accurate, truthful, and clear.

Why is the myth of neutrality important in data visualization?

Data is not neutral; it is influenced by human decisions in collection and processing.

What is one ethical challenge designers face regarding privacy?

Collecting and handling data with empathy.

What does visibility in ethical data visualization refer to?

Deciding what to show and what to hide in visualizations.

What is a common ethical trap in data visualization?

Misleading correlations: showing two variables that move together but have no causal link.

What is the Visualization Hippocratic Oath?

A commitment to not use visualization to intentionally hide or confuse the truth.

What is driving change in data visualization?

The Internet, IoT, and network & complexity theories.

What are the 3 Vs of big data visualization?

Volume, Velocity, Variety.

What is a helpful tip for good visualization?

Deliver value: your visualization should provide insight, aid a decision, or prompt action.

What should you avoid in visualization design?

Being 'too cute': stick to good design principles and keep it simple.

What is the purpose of providing filters in data visualization?

To allow for 'what-ifs' and exploration.

What is the importance of clarity over aesthetics in visualization?

The purpose of the graphic dictates its form; clarity should not be sacrificed for aesthetics.

What is the role of context in data visualization?

Data without context is meaningless and can be misleading.

What is the benefit of using animation in data visualization?

It helps represent dynamic networks and time-evolving connections.

What is a radial tree?

A circular format of tree visualization that is more compact and better for larger trees.

What does circle packing represent in hierarchical data?

Hierarchical data using nested circles, where larger circles contain smaller ones.

What is the challenge of color overload in visualization?

Too many categories can confuse the viewer.

What is the significance of ethical data and design?

To ensure reliability, identify bias, and provide meaningful context in visualizations.