What Antaeus Is
Antaeus is a system for finding patterns in multivariate data. It is intended to be used by a single investigator working from individual data tables. It provides tools for looking at your data when you don't yet know what you're looking for, led by your intuition and knowledge about the emergent phenomena represented. Antaeus does not use and requires no knowledge of statistics (see A Second Opinion). However, it is based on the functional use of fundamental mathematical principles (see Seeing Your Data).
The basic plot type used everywhere in Antaeus is the scatter plot, supplemented by its high-density counterpart, the sunflower plot (see The Sunflower Plot). These plots are supported by quantile plots and histograms, which are used to see the data of a single variable. Scatter plots are used to look for the relationship between two variables, but as the number of variables increases, more and more scatter plots become necessary to visualize all the possible interrelationships.
As an example, the screen shot below shows a scatter plot from the Weather Data demo cube, installed with Antaeus, in the Single Scatter Plot SV (SynchroView). This data consists of 12 variables (measures) and 2 dimensions (date and location) defined by a data table containing 11,458 records, which results in a basic set of 144 different scatter plots. But any scatter plot can be greatly modified by using subsets of the data records, defined in terms of measure and dimension values. Each subset results in a different set of basic scatter plots. Also, as can be seen in the screen shot, the data points in a scatter plot can be separated, using color, into groups corresponding to different values of a dimension (see Dimensions and Separation):
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To explore this diversity in a logical manner, something more than a data reduction facility is needed. Antaeus uses a structure called the data cube, which is generated from a flat-file comma, tab, or semi-colon delimited data table. A data cube ("cube" for short) is entirely independent of the data table it was created from, and these cubes can be freely exchanged between users. The cube is represented in the interface by a virtual scatter plot matrix within which you navigate the universe of possible scatter plots. The "something more" consists of supporting SVs that enable you to modify the logical structure of the data cube to provide new ways of asking questions about your data.
As an example, there is an SV that lets you create new measures as mathematical functions of existing measures (see Functions—Defining new measures). The Scatter Plot Matrix SV below shows an 8x8 matrix, from the Iris Data Extended demo cube, using 4 new measures defined as simple ratios of the original 4 measures:
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Another SV lets you create new dimensions by partitioning the data points of a scatter plot into mutually disjoint groups of records (see Partitions—Defining new dimensions). The following screen shot of the Double Scatter Plot SV, which displays a double plot from the GHCN Station List demo cube, illustrates what you can do by creating a new dimension. In this case, a dimension was created from the Elevation measure with five values for five strata of elevation, four of which are separated. Also, one of the cube's eight subsets—also created from the Elevation measure—is applied as a brush:
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Antaeus exploits the ever-increasing memory and speed of contemporary PCs by allowing data tables and cubes to be as large as your hardware can handle. This may result in frustration when working interactively with large files, but several mechanisms are provided for dealing with this (see Navigating Large Cubes).
All the plots generated by Antaeus are very highly finished and do not require any user interaction to achieve this level of quality. You can size the plots by dragging the edges of their windows, and you have extensive control over the palettes used to color them, but all their construction details are handled proactively.
Antaeus is also a platform from which plots may be published. Any plot may be saved to clipboard or file (when too large for the clipboard) as a Windows Enhanced Metafile (EMF). These can be embedded in reports, papers, and presentations created in Microsoft Office products such as Word, PowerPoint and Publisher. Support for EMF files is also increasing among non-Microsoft publication suites. These sophisticated programs are empowered by the use of plots they cannot possibly construct themselves.