Let’s examine an average research workday from the KaleidaGraph viewpoint: A scientific experiment is in progress and our researcher is trying to balance her lab hours with other responsibilities to educate and report. The scientific instrumentation which records the experimental data is storing thousands of data points per hour in an Excel spreadsheet. There are new graduate students to assimilate into the lab and an important conference is rapidly approaching. This is the environment in which KaleidaGraph shines. The lab staff masters the basic functionality of KaleidaGraph in less than one hour using the Quick Start guide that walks users through the entering and importing of data, plot customization, applying curve fits and error bars, and exporting the plot. Most have not even cracked the documentation because, well, they are busy graduate students, and the use of KaleidaGraph is so intuitive.

An Excel spreadsheet opens directly from within KaleidaGraph, so that data is readily available in the data windows. But someone has sent some collateral data from a neighboring lab, so that text file is easily imported into the application as well. The appropriate 2D graph type is selected from the Gallery menu and the students proceed to manipulate any and all of the graph elements to meet the very exacting standards for the conference publication. Upon completion of the prototype graph, a template is saved so that succeeding runs of data can quickly be graphed in the same style. The students then analyze the relationship of the data using ANOVA, t-test, or a nonparametric test, and apply a custom curve fit to see the data trends.