After a lot of effort, the first release of Quadrigram became public last week.
Quadrigram is a service developed by Bestiario that supports the visual analysis of data. Rather than only supporting the development of visualizations, Quadrigram provides tools in the form of modules that cover all the steps of the process of Information Visualization allowing to gather, manipulate, visualize and share data.
It is relevant to stress out the main slogan of Quadrigram: “Finding questions. Finding answers” as it refers to a very important property of Information visualization: find questions regarding the data you didn’t even know you have. This concept raised by Catherine Plaisant in her paper “The Challenge of Information Visualization Evaluation” references to the fact that making data visible helps our brain to detect patterns that can also rise many questions that can lead to new insights.
In essence, Quadrigram is a visual programming language that provides a set of modules distributed in 5 different families that can be dragged in a canvas and connected among them forming “workspaces”. The modules have been classified as follows:
Operators: modules that manipulate or transform data structures
Controls: modules that provides interactivity to the workspace
Visualizers: modules that represent data. In this family we can find from the most common charts, to some of the most advanced visualizations created by Bestiario during the last 6 years
Resources: modules that simplify the process of incorporating data from many data sources to the workspace.
When put together, modules from those families help creating crazy workspaces to analyze, visualize and share insight from complex datasets as can be seen with the following space that permits to explore the activities of a company by projects, sectors, location, and profitability.
As a final remark, Quadrigram emphasizes and supports a concept that I’m really attached to: visualization shouldn’t be the last step in the analysis process (i.e. in the communication of the results). It should be used to sketch and draw conclusions at every single step of the analysis. That is, visualization should be used for understanding gathered data, for revealing it’s “shape” after it has been processed and transformed, and for communicating the results found during the process.