Visualization Tools, Libraries, Data Sets, and Further Resources

Visualization tools — data exploration and visualization in dashboards:

• Tableau (Visualization environment, Dashboards)
• Visualize Free (Online, Dashboards)
• Glue (Python; multi-dimensional linked-data exploration)
• InstantClue (Visualization design and data exploration environment)
• Voyager 2 (Online, data exploration tool)
• QlikView (Visualization environment, Dashboards)
• Power BI (Visualization environment, Dashboards)
• Keshif Online (Online, Dashboards)

Visualization tools — authoring of individual charts:

• DataWrapper (Visualization environment, single chart)
• RawGraphs (Visualization environment, single chart)
• Make-a-vis (Visualization environment, single or multiple charts)
• Lyra (Online, visualization design environment)

Visualization tools — graph and network data:

• yFiles (+ yEd) (Graph drawing libraries and tools; several platforms)
• Gephi (Network analysis and visualization environment)
• Graphia (Network analysis and visualization environment)
• Cytoscape (Environment for complex networks and multivariate data analysis; several platforms)
• OriGraph (Online graph data wrangling tool)
• kepler.gl (Environment for large-scale geospatial and network analysis; online)
• Nomic Atlas (Environment for AI/ML-based analysis of text, image, and multidimensional data collections; online)

Visualization tools — other specific data types and representations:

• VoyantTools (Environment for text analysis; online)
• StoryMapJS (Authoring tool for map-based storytelling; online)
• TimelineJS (Authoring tool for timeline-based storytelling; online)
• Heatmapper (Environment for geographical map and heatmap visualization; online)
• EdWordle (Authoring tool for word clouds; online)
• Jigsaw (Visual analytic environment for document and multivariate data; several platforms, including WebJigsaw)
• Inviwo (Scientific visualization environment; several platforms, including C++ and Python)

Data analysis and visualization tools:

• Word Rain (Python; semantic-preserving word cloud-like visualization of texts and document collections)
• OpenRefine (Java; data preprocessing/wrangling)
• Datasette (Python; data preprocessing/wrangling and exploratory data analysis)
• Apache Superset (Python; data exploration and visualization platform for SQL DBs)

Interactive data mining / ML / AI tools:

• Orange (Machine learning and visual analysis environment; Python)
• Textable (Text mining extensions for Orange)
• KNIME Analytics Platform (Interactive data mining environment; several platforms)
• Weka (Interactive data mining environment; Java)
• ELKI (Interactive data mining environment; Java)

Data analysis and visualization libraries:

• Word Rain (Python; semantic-preserving word cloud-like visualization of texts and document collections)
• pyLDAvis (Python; visualization of topic models)
• Scattertext (Python; visualization of text document collections)
• t-SNE (Python and many other languages; dimensionality reduction for multivariate/high-dimensional data)
• UMAP (Python; a recent DR approach comparable, or in some cases, preferred to t-SNE)
• Further manifold learning and DR techniques (scikit-learn) (Python)
• densVis (Python; DR for density-preserving data visualization)
• NetworkX (Python; analysis and visualization of network data)
• py3plex (Python; analysis and visualization of multiplex and multilayer network data)
• muxViz (R; analysis and visualization of multilayer network data)
• ScanPy (Python; analysis and visualization of biological data)
• Yellowbrick (Python; visualization for machine learning)

Visualization libraries — JavaScript (general-purpose):

• D3 (JavaScript)
• D3 Discovery (Plugin catalog for D3)
• Observable Plot (JavaScript; from the authors of D3)
• plotly.js (JavaScript; based on D3)
• billboard.js (JavaScript; based on D3)
• vis.js (JavaScript)
• Chart.js (JavaScript)
• ApexCharts.js (JavaScript; based on D3)
• Google Charts (JavaScript)
• Regl Scatterplot (JavaScript; high-performance WebGL-based scatterplots)
• Vega (JavaScript; based on D3)
• Vega-Lite (JavaScript; based on D3 and Vega)
• nivo (JavaScript; based on D3 and React)
• Victory (JavaScript; based on D3 and React)
• Highcharts (JavaScript)

Visualization libraries — JavaScript (specific data types and representations):

• Rickshaw (Temporal data; JavaScript; based on D3)
• Leaflet (Geospatial data (maps); JavaScript)
• Mapbox GL JS (Geospatial data (maps); JavaScript)
• Cytoscape.js (Graph/network data; JavaScript)
• Sigma (Graph/network data; JavaScript)
• WebCoLa (cola.js) (Graph/network data; JavaScript; compatible with D3 and Cytoscape.js)

Visualization libraries — Python:

• Dash (Python; generates a web-based dashboard using plotly.js; also available for R, Julia, and F#)
• plotly.py (Python; generates a web-based visualization using plotly.js; also R, Julia, F#, and Matlab)
• HoloViz (Python; a set of high-level packages for interactive visualization)
• Bokeh (Python; generates a web-based bashboard)
• Chartify (Python; generates a web-based visualization using Bokeh)
• Altair (Python; generates a web-based visualization using Vega and Vega-Lite)
• mpld3 (Python; generates a web-based visualization using D3)
• Folium (Python; generates a web-based geographical map using Leaflet.js)
• Geoplot (Python; geospatial data (maps))

Visualization libraries — other languages and platforms:

• Processing (Environment for graphics programming; several platforms)
• Improvise (Java)
• JFreeChart (Java)
• Shiny (R; generates a web-based visualization)
• Shiny Dashboard (R; generates a web-based visualization using Shiny)

Visualization libraries — statistical and scientific visualizations:

• ggplot2 (R; statistical graphics)
• Matplotlib (Python; statistical graphics and scientific plotting, static plots with very limited interaction options)
• Seaborn (Python; statistical graphics, based on Matplotlib)
• Chaco (Python; statistical graphics and scientific plotting, based on Matplotlib, further interaction options)
• Veusz (Python; statistical graphics and scientific plotting)
• PyVista (Python; scientific visualization)

Visualization libraries no longer in active development (not recommended for assignments):

• JavaScript InfoVis Toolkit (JavaScript)
• Flare - Data Visualization for the Web (ActionScript)
• JUNG Java Universal Network/Graph Framework (Java)
• InfoVis Toolkit (Java)
• JChart (Java)
• XmdvTool (Qt)

Scientific publication data:

• Vispubdata: Visualization Publication Dataset
• VIS30K (31+ thousand images from IEEE VIS conferences)
• arXiv Dataset
• hdblp: historical data of the dblp collection

Text data:

• The Brexit Blog Corpus
• Project Gutenberg eBooks - Offline Catalogs and Feeds
• 4000 CNN articles from 2023
• OpinRank Data - Reviews From TripAdvisor & Edmunds
• Enron Email Dataset
• News Commentary Corpus
• PHEME Rumour Scheme Dataset
• Multi-Domain Sentiment Dataset
• 200,000+ Jeopardy! Questions
• European Parliament Proceedings Parallel Corpus 1996-2011
• Open Parallel Corpora
• The Language Archive
• CLARIN corpora of academic texts
• Språkbanken (University of Gothenburg) language resources
• 1 Billion Word Language Model Benchmark
• CC-100: Monolingual Datasets from Web Crawl Data
• The Pile: An 800GB Dataset of Diverse Text for Language Modeling
• OpenWebTextCorpus
• Nordic Tweet Stream
• 20 Open Datasets for Natural Language Processing

Graph and network data:

• Gephi sample datasets
• Graphia example datasets
• YoutubeGraph-Dyn: An evolving graph dataset from YouTube interactions
• Stanford Large Network Dataset Collection
• BigDND: Big Dynamic Network Data
• ICON: Colorado Index of Complex Networks
• Network Repository: An Interactive Scientific Network Data Repository

Other and mixed data types:

• Towards A Quantitative Survey of Dimension Reduction Techniques - Datasets
• IMDb Non-Commercial Datasets
• Amazon Review Data
• Yelp Open Dataset
• Netflix Prize Data
• Stack Exchange Data Explorer
• OpenStreetMap data
• SuiteSparse Matrix Collection (formerly the University of Florida Sparse Matrix Collection)

Miscellaneous data set collections and search tools:

• Visual Analytics Benchmarks Repository
• UC Irvine Machine Learning Repository
• Awesome Public Datasets
• KDNuggets Datasets for Data Science, Machine Learning, AI & Analytics
• Kaggle Datasets
• Google Research Datasets
• Google Research Dataset Search
• OpenML data sets and collections
• Harvard Dataverse
• European Data
• Swedish National Data Service
• Sveriges Dataportal (Swedish open data)

Literature review/survey methodology:

• A Typology of Reviews: An Analysis of 14 Review Types and Associated Methodologies
• Literature Review as a Research Methodology: an Overview and Guidelines

Overall methodology for visualization design and evaluation:

• Embracing Disciplinary Diversity in Visualization
• A Nested Model for Visualization Design and Validation
• Design Study Methodology: Reflections from the Trenches and the Stacks
• A Matter of Time: Applying a Data–Users–Tasks Design Triangle to Visual Analytics of Time-oriented Data

Tools and papers for choosing a color map:

• ColorBrewer 2.0
• Diverging Color Maps for Scientific Visualization
• Rainbow Color Map (Still) Considered Harmful
• Rainbow Colormaps Are Not All Bad
• Rainbow Colormaps: What are They Good and Bad for?
• Somewhere Over the Rainbow: An Empirical Assessment of Quantitative Colormaps + Viridis color map in D3.js
• Optimizing Colormaps With Consideration for Color Vision Deficiency to Enable Accurate Interpretation of Scientific Data + cmaputil + Cividis color map in D3.js
• Good Colour Maps: How to Design Them + PerceptualColourMaps package in Julia
• Color Blindness Simulator
• Coblis — Color Blindness Simulator

Evaluation/validation, usability studies, questionnaires:

• Evaluating Information Visualizations
• Patterns for Visualization Evaluation
• Measuring Usability: Are Effectiveness, Efficiency, and Satisfaction Really Correlated?
• SUS Analysis Toolkit + paper
• UMUX-Lite Questionnaire + paper

• InfoVis:Wiki, the Information Visualization community platform
• A Tour through the Visualization Zoo
• Information is Beautiful
• A Visual Bibliography of Tree Visualization
• A Visual Survey of Visualization Techniques for Time-Oriented Data
  • Visualization of Time-Oriented Data (2nd Edition, Open Access Book)
• A Visual Survey of Text Visualization Techniques
• A Visual Survey in Enhancing Trust in Machine Learning (ML) Models with Visualization
• Quantified Self Viz Contest Entries
• Overview of Data Visualizations and Infographics
• From Data to Viz + The D3.js Graph Gallery
• Selection of Data Visualisation Tools
• Data Visualization for Human Perception
• Visual Perception
• Exploring Preattentive Attributes
• Nightingale — The Journal of the Data Visualization Society
• Save the Pies for Dessert (critique of the pie chart visualization technique)
• Visualization Resources
• Data Visualization Teaching and Learning Materials
• Mastering the Information Age: Solving Problems with Visual Analytics (Free Book)
• Progressive Data Analysis: Roadmap and Research Agenda (Free Book)
• Search User Interfaces (Free Book)