Data
Data can - but does not need to be - acquired from one of these sources:
Scientific Visualization Ressourcen:
- IEEE SciVis Contests 2004-now
https://scivis2021.netlify.app/previous/
Each year, SciVis contests provide a challenging scientific data set to be visualized; list of all SciVis contests from 2004 until now. - Visualization Group Data Sets
http://www.cg.tuwien.ac.at/research/vis/datasets/
3D volume data sets from our institute. - Stefan Roettgers Volume Library
http://www9.informatik.uni-erlangen.de/External/vollib/
A collection of free 3D volume data sets. - The Stanford Volume Data Archive
http://graphics.stanford.edu/data/voldata/
3D volume data sets from CT. - Osirix DICOM Data
http://www.osirix-viewer.com/datasets/
Medical volume data sets in DICOM format. - Protein Data Bank
http://www.rcsb.org/
3D shapes of proteins, nucleic acids, and compelx assemblies. - Open Scientific Visualization Data Sets
by SCI, Utah; including CT, MR etc.
https://klacansky.com/open-scivis-datasets/
Information Visualization und Visual Analytics Ressourcen:
- VAST challenge archive
http://www.vacommunity.org/About+the+VAST+Challenge
Archive of all Visual Analytics Science and Technology (VAST) Challenges from 2006. - UCI Machine Learning Repository
http://archive.ics.uci.edu/ml/datasets.html
Provides hundreds of data sets mainly for the machine learning community, but also interesting for visualization! - sci-kit learn Datasets
https://scikit-learn.org/stable/datasets.html
Provides some interesting data sets for machine learning, but also interesting for visualization - Papers with Code
https://paperswithcode.com/datasets
Machine learning data sets (mainly images, texts, and videos), that could also be interesting for visualization or visual analytics - Kaggle Datasets
https://www.kaggle.com/datasets
Ten thousands of public datasets, including Bitcoin, YouTube statistics, transports etc. - FiveThirtyEight Data
https://data.fivethirtyeight.com/
Data used and provided by the FiveThirtyEight opinion poll analysis / politics, economics, and sports blog website. - data.gv.at
https://www.data.gv.at/
offene Daten Österreich - Gapminder world data
https://www.gapminder.org/data/
Provides hundrets of country indicators, such as population, infant mortality rates, life expectancy at birth, employment rates etc., over many years. - Tableau sample data sets
https://public.tableau.com/s/resources?qt-overview_resources=1#qt-overview_resources
Dozens of data sets about education, science -- and even characteristics of Star Wars characters. - CIA world factbook
https://www.cia.gov/library/publications/the-world-factbook/rankorder/rankorderguide.html
Country comparisons of different geographic or economic statistics can be downloaded. - Data.Gov
https://catalog.data.gov/dataset
Hundrets thousands of data sets (e.g., demographic statistics on zip code level) provided by the U.S. government. - Google public data explorer
http://www.google.com/publicdata/home
Search through publicly available data sets, such as world bank, eurostat, WTO etc. - Statista
https://www.statista.com/
Large collection of statistics (TU Wien has a license) - Stanford Large Network Dataset Collection
http://snap.stanford.edu/data/
Provides any kinds of network data. - The Koblenz Network Collection
http://konect.uni-koblenz.de/
Large network datasets of all types collected by the University of Koblenz-Landau. - GMap Graph Datasets
http://gmap.cs.arizona.edu/datasets
Collection of graphs and networks used for demonstrating GMap. - graphdrawing.org Benchmark Data
http://www.graphdrawing.org/data.html
Benchmark data for various classes of graph drawing algorithms. - Network Data Collection
http://www-personal.umich.edu/~mejn/netdata/
Network data collected by Mark Newman. - Visualization publications dataset
http://www.vispubdata.org/site/vispubdata/
Contains all IEEE VIS publications from 1990 to 2015 with titles, authors etc. and citations to previous VIS papers. - IMDbPY
https://imdbpy.sourceforge.io/
Python package to retrieve and manage data of the IMDb movie database. - Car dataset
https://www.cg.tuwien.ac.at/courses/Visualisierung1/exercises/data/cars_406.zip
A classic small multivariate data set about cars. - Nutrients dataset
https://www.cg.tuwien.ac.at/courses/Visualisierung1/exercises/data/nutrients_7538.zip
A classic multivariate data set about nutrients. - Car Evaluation Data Set
http://archive.ics.uci.edu/ml/datasets/Car+Evaluation
A larger car datset. - Plants Data Set
http://archive.ics.uci.edu/ml/datasets/Plants
A classic and quite large multivariate data set about plants.
Tools
Visualization or Graphics Toolkits and Libraries:
- D3.js - JavaScript library for data-driven visualization documents
https://d3js.org/ - Vega Light - high-level visualization grammar based on JSON
https://vega.github.io/vega-lite/ - Python Visualization Libraries - Python offers a variety of visualization libraries, like Bokeh, Plotly, Seaborn, Altair, or Folium. Here is an overview:
https://mode.com/blog/python-data-visualization-libraries - R Visualization Packages - R provides some visualization packages as well:
https://mode.com/blog/r-data-visualization-packages - three.js - JavaScript 3D scenegraph library based on WebGL
https://threejs.org/ - babylon.js - JavaScript 3D rendering engine based on WebGL (and partially supporting WebGPU)
https://www.babylonjs.com/ - Stardust: GPU-based Visualization Library
https://stardustjs.github.io/ - DataShader - Python library for large-scale data visualization
https://datashader.org/ - Leaflet - JavaScript library for mobile-friendly interactive maps
http://leafletjs.com/ - CesiumJS - JavaScript library for 3D geospatial visualization
https://cesium.com/platform/cesiumjs/ - Google Visualization API for the creation of visualization
https://developers.google.com/chart/interactive/docs/reference - Qt Data Visualization Module
http://doc.qt.io/qt-5/qtdatavisualization-index.html - Visualization Toolkit (VTK) -- 3D graphics, image processing, and visualization library
https://www.vtk.org/ - Kitware toolkits and applications (including VTK, ParaView, ITK, 3D Slicer etc.)
https://www.kitware.com/platforms/ - Unity3D - game engine; sometimes used for 3D visualization
https://unity3d.com/ - Unreal Engine - game engine; sometimes used for 3D visualization
https://www.unrealengine.com - A Frame - framework for web VR applications
https://aframe.io/ - R Shiny - web-based dashboards based on R
https://shiny.rstudio.com/ - Collection of Vis-Tools
http://selection.datavisualization.ch/
Other useful tools and libraries:
- Crossfilter - JavaScript library for efficient handling of large tabular datasets
http://square.github.io/crossfilter/ - Pandas - Python library for data manipulation and analysis
https://pandas.pydata.org/ - OpenRefine - tool for cleaning and tranforming messy data
http://openrefine.org/ - NetworkX - Python package for graph creation, transformation, analysis
https://networkx.github.io/ - scikit-learn - machine learning in Python
https://scikit-learn.org/stable/ - TensorFlow - open source machine learning framework (especially for deep learning) for Python, Java, C, Go, and JavaScript
https://www.tensorflow.org/ - CUDA - parallel computing platform for NVIDIA GPUs
https://developer.nvidia.com/cuda-zone - OpenCL - open, cross-platform parallel programming framework
https://www.khronos.org/opencl/ - Numba - JIT compiler translating subset of Python / NumPy into fast machine code
http://numba.pydata.org/
Links
- A Tour Through the Visualization Zoo (Heer et al., 2010)
https://cacm.acm.org/magazines/2010/6/92482-a-tour-through-the-visualization-zoo - A Survey of Surveys in Information Visualization
http://sos.swansea.ac.uk/ - Data Visualization Milestones
http://www.datavis.ca/milestones/ - Survey on text visualization techniques
http://textvis.lnu.se/ - Survey on tree visualization techniques
http://treevis.net/ - Survey on BioVis techniques
http://biovis.lnu.se/ - Survey on set visualization techniques
http://www.cvast.tuwien.ac.at/~alsallakh/SetViz/literature/www/index.html - Survey on trust in machine learning visualization
https://trustmlvis.lnu.se/ - Information Visualization community platform
http://infovis-wiki.net/index.php/Main_Page
The InfoVis:Wiki project is intended to provide a community platform and forum integrating recent developments and news on all areas and aspects of Information Visualization. - Visual Complexity
http://www.visualcomplexity.com/
Web portal, which represents very nice projects of visualizations in practical use. - The Python Graph Gallery
https://python-graph-gallery.com/
Hundrets of charts, each with corresponding python code. - TED-Talk by Hans Rosling
http://www.ted.com/index.php/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html (Video)
A very good example how InfoVis can be used to explore large and high-dimensional data sets. - TED-Talk by Gary Flake
http://www.ted.com/talks/gary_flake_is_pivot_a_turning_point_for_web_exploration.html (Video)
Talk about Pivot - an interesting application to browse the web.
Contact
If you discover any broken link, or you think something has to be added to this list, contact Manuela Waldner.