Infographics

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This is a WIP resources page.

Really Useful Data project

See Visualisation

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.

Related events

Roadmap

Quick to do list;

  1. Finish transfer of research notes
  2. Add additional info and data sources
  3. Focus on accessible methods of creating vis.

Key questions

  • 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?


Visualisation

Media that represents data and other knowledge to help provice a mental context and scale

visualize, verb

  1. form a mental image of; imagine: it is not easy to visualize the future
  2. make (something) visible to the eye: the DNA was visualized by staining with ethidium bromide

See also Organisation#Knowledge, JS_scripts#Graphics

General

Quotes

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).

COX;

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

Semantic Web and Linked Data

  • EEA Daviz is a web tool developed by the European Environment Agency which helps creating interactive data visualizations easily through the web browser, no extra tools are necessary. It is free and open source. You can generate attractive and interactive charts and combine them in a dashboard with facets/filters which updates the charts simultaneously. Data can be uploaded as CSV/TSV or you can specify SPARQL to query online Linked open data servers (aka sparql endpoints). Daviz is the first Semantic web data visualisation tool for Plone CMS, entirely web-based! At the moment Simile Exhibit and Google Charts visualizations are supported. The architecture allows to extend Daviz with more visualisation libraries (visualisations plugins). - zope/plone

Systems

Google

Karma

  • 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

Other

Tutorials

Design, data and vis basics;

d3;

Learning

See also Learning

Journalism

Examples

People

Creating

See JavaScript, JS_scripts#Visualisation

Google

Gap Minder

other