Fast and slow visualization

@machinelearnbot

This breakneck pace is a real data visualization constraint. It's not a myth that charts are often deployed in rooms full of people who only have a short time to comprehend them (or not) and make a decision. Automatic views into datasources are a critical aspect of exploratory data analysis and health checks. The fast mode of data visualization is real and important, but when we let it become our only view into what data visualization is, we limit ourselves in planning for how to build, support and design data visualization. We limit not only data visualization creators but also data visualization readers.


How to Spot Visualization Lies

@machinelearnbot

It used to be that we'd see a poorly made graph or a data design goof, laugh it up a bit, and then carry on. At some point though -- during this past year especially -- it grew more difficult to distinguish a visualization snafu from bias and deliberate misinformation.


Baikadi

AAAI Conferences

The task of narrative visualization has been the subject of increasing interest in recent years. Much like data visualization, narrative visualization offers users an informative and aesthetically pleasing perspective on "storydata." Automatically creating visual representations ofnarratives poses significant computational challenges due to the complex affective and causal elements, among other things, that must be realized in visualizations. In addition, narratives that are composed by novice writers pose additional challenges due to the disfluencies stemming from ungrammatical text. In this paper, we introduce the NARRATIVE THEATRE, a narrative visualization system under development in our laboratory that generates narrative visualizations from middle school writers' text. The NARRATIVE THEATRE consists of a rich writing interface, a robust natural language processor, a narrative reasoner, and a storyboard generator. We discuss design issues bearing on narrative visualization, introduce the NARRATIVE THEATRE, and describe narrative corpora that have been collected to study narrative visualization. We conclude with a discussion of a narrative visualization research agenda.


50 great data visualizations

@machinelearnbot

I think many of these visualizations are just pure art, but delivering no insight. So we selected a few of the most powerful ones for you. Click here to check the 50 visualizations. Check out our previous article on great visualizations. Or do a DSC search to find all our articles about visualization.


Data visualization

@machinelearnbot

Data visualization is what attracts at first sight is what properly should help affirm what text and numerical results say (Anscombe's quartet). It is important because otherwise it may bring confusion. For some time I was looking for information on the subject and I must say it is abundant. There are resources that can be used to improve the graphical representation of our investigation as we can find organized on Nature Methods and in the pages of the courses CS 171 - Visualization and CS 1109 Data Science on the subject of the prestigious Harvard University. The tools to perform graphics are abundant most important and most used are python and R also can be used more easily Matlab or Tableau, BoxPlotR,etc.