- 1 General
- 2 Info and news
- 3 Systems
- 4 Tutorials
- 5 Learning
- 6 Creating
- 7 Really Useful Data project
This is a WIP resources page.
Media that represents data and other knowledge to help provide context and scale.
- form a mental image of; imagine: it is not easy to visualize the future
- make (something) visible to the eye: the DNA was visualized by staining with ethidium bromide
From the Keller Paper;
Ware says “power of a visualization comes from the fact that it is possible to have a far more complex concept structure represented externally in a visual display than can be held in visual and verbal working memories". In this regard, visualizations are cognitive tools aiming at supporting the cognitive system of the user. Visualizations can make use of the automatically human process of pattern finding (Ware, 2004). They can draw both on the visual and the spatial working memory system (Baddeley, 1998; Logie, 1995).
Compared with an informationally-equivalent textual description of an information a diagram may allow users to avoid having to explicitly compute information because users can extract information ‘at a glance’ (p. 2). “Such representations work best when the spatial constraints obeyed by representations map into important constraints in the represented domain in such a way that they restrict (or enforce) the kinds of in- terpretations that can be made” (Rogers & Scaife, 1997, p. 2). They can help to ex- ploit the rapid processing capabilities of the human visual system and very easy per- ceptual judgements are substituted for more difficult logical ones (Paige & Simon, 1966). Chabris and Kosslyn (in this book) suggest the principle of ‘representational correspondence’ as a basic principle of effective diagram design. According to this principle visualizations work best if they depict information in the same way that our internal mental representation do.
- Get the above academic details for bibliography
Info and news
- HCi: Flowcharting
- Kroki! - provides a unified API with support for BlockDiag (BlockDiag, SeqDiag, ActDiag, NwDiag), C4 (with PlantUML), Ditaa, Erd, GraphViz, Mermaid, Nomnoml, PlantUML, SvgBob and UMLet... and more to come!
- https://en.wikipedia.org/wiki/DOT_(graph_description_language) - graph description language. DOT graphs are typically files with the file extension gv or dot. The extension gv is preferred to avoid confusion with the extension dot used by early (pre-2007) versions of Microsoft Word.
- ditaa - a small command-line utility written in Java, that can convert diagrams drawn using ascii art ('drawings' that contain characters that resemble lines like | / - ), into proper bitmap graphics. This is best illustrated by the following example -- which also illustrates the benefits of using ditaa in comparison to other methods :)
- blockdiag - and its family generate diagram images from simple text files
- nwdiag - generates network-diagram images from .diag files (similar to graphviz’s DOT files).
- Webgraphviz - Graphviz in the Browser
- https://github.com/knsv/mermaid - Generation of diagram and flowchart from text in a similar manner as markdown 
- https://github.com/shd101wyy/markdown-preview-enhanced - One of the 'BEST' markdown preview extensions for Atom editor!
to totally rework
See also JS scripts
- Karma is an information integration tool that enables users to quickly and easily integrate data from a variety of data sources including databases, spreadsheets, delimited text files, XML, JSON, KML and Web APIs. Users integrate information by modeling it according to an ontology of their choice using a graphical user interface that automates much of the process. Karma learns to recognize the mapping of data to ontology classes and then uses the ontology to propose a model that ties together these classes. Users then interact with the system to adjust the automatically generated model. During this process, users can transform the data as needed to normalize data expressed in different formats and to restructure it. Once the model is complete, users can published the integrated data as RDF or store it in a database.
- SIMILE Widgets - an open-source “spin-off” from the SIMILE project at MIT. Here we offer free, open-source web widgets, mostly for data visualizations. They are maintained and improved over time by a community of open-source developers.
- Exhibit enables web site authors to create dynamic exhibits of their collections without resorting to complex database and server-side technologies. The collections can be searched and browsed using faceted browsing. Assorted views are provided including tiles, maps, etc.
- Kibana - lets you visualize your Elasticsearch data and navigate the Elastic Stack, so you can do anything from learning why you're getting paged at 2:00 a.m. to understanding the impact rain might have on your quarterly numbers.
- https://github.com/kantord/just-dashboard - Create dashboards using YAML/JSON files
- VTK - The Visualization Toolkit - an open-source, freely available software system for 3D computer graphics, image processing, and visualization. It consists of a C++ class library and several interpreted interface layers including Tcl/Tk, Java, and Python. VTK supports a wide variety of visualization algorithms including scalar, vector, tensor, texture, and volumetric methods, as well as advanced modeling techniques such as implicit modeling, polygon reduction, mesh smoothing, cutting, contouring, and Delaunay triangulation. VTK has an extensive information visualization framework and a suite of 3D interaction widgets. The toolkit supports parallel processing and integrates with various databases on GUI toolkits such as Qt and Tk. VTK is cross-platform and runs on Linux, Windows, Mac, and Unix platforms. VTK is part of Kitware’s collection of commercially supported open-source platforms for software development.
- Tulip - an information visualization framework dedicated to the analysis and visualization of relational data. Tulip aims to provide the developer with a complete library, supporting the design of interactive information visualization applications for relational data that can be tailored to the problems he or she is addressing.
- ParaView - an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView’s batch processing capabilities. ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of petascale size as well as on laptops for smaller data, has become an integral tool in many national laboratories, universities and industry, and has won several awards related to high performance computation.
- leather - he Python charting library for those who need charts now and don’t care if they’re perfect.Leather isn’t picky. It’s rough. It gets dirty. It looks sexy just hanging on the back of a chair. Leather doesn’t need your accessories. Leather is how Snake Plissken would make charts.
- Apparatus is a hybrid graphics editor and programming environment for creating interactive diagrams. The Apparatus Editor runs in the browser and interactive diagrams created with Apparatus can be shared and embedded on the web. Apparatus is free, open-source software. 
- Idyll - a tool that makes it easier to author interactive narratives for the web. The goal of the project is to provide a friendly markup language — and an associated toolchain — that can be used to create dynamic, text-driven web pages.Idyll helps you create documents that use common narrative techniques such as embedding interactive charts and graphs, responding to scroll events, and explorable explanations. Additionally, its readable syntax facilitates collaboration between writers, editors, designers, and programmers on complex projects.
- https://github.com/3b1b/manim - Animation engine for explanatory math videos
- GGobi - an open source visualization program for exploring high-dimensional data. It provides highly dynamic and interactive graphics such as tours, as well as familiar graphics such as the scatterplot, barchart and parallel coordinates plots. Plots are interactive and linked with brushing and identification.
- Vega - a visualization grammar, a declarative language for creating, saving, and sharing interactive visualization designs. With Vega, you can describe the visual appearance and interactive behavior of a visualization in a JSON format, and generate web-based views using Canvas or SVG.
- Plotly - graphing library makes interactive, publication-quality graphs online. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts. https://github.com/plotly/plotly.py
Design, data and vis basics;
- graphdrawing.org - This site is a collection of resources mostly related to the annual International Symposium on Graph Drawing, but we anticipate the inclusion of, e.g., an overview of software tools in the future.
- D3 for Beginners Part I: Joe Golike on Thinking in D3
See also Learning
- http://raw.densitydesign.org/ - d3 to create svg from pasted data
- Google I/O 2008 - Visualize your Data: Visualization API
- Google's Public Data Explorer: A New Tool for Visualizing Information
- Grap is a language for typesetting graphs specified and first implemented by Brian Kernighan and Jon Bentley at Bell Labs. It is an expressive language for describing graphs and incorporating them in typeset documents. It is implemented as a preprocessor to Kernigan's pic language for describing languages, so any system that can use pic can use grap. 
- Asymptote is a powerful descriptive vector graphics language that provides a natural coordinate-based framework for technical drawing. Labels and equations are typeset with LaTeX, for high-quality PostScript output.
- Grafana - allows you to query, visualize, alert on and understand your metrics no matter where they are stored. Create, explore, and share dashboards with your team and foster a data driven culture.
See also Computing#Data science and stats
Really Useful Data project
With aims to provide insight on elements of data and design literacy, and describe patterns for using either for informational and learning purposes.
Really useful data, designed and engineered right. -J.K.
Data, linked data, and how to visualise. -M.
Quick to do list;
- Finish transfer of research notes
- Add additional info and data sources
- Focus on accessible methods of creating vis.
- What data sets and sources are useful for our purposes?
- What types and examples of visualisation are available?
- Methods for display a relation between data and media?
- How to build and manage a system for visualising data?