The R Statistics operation, available in as a DataManager operation block and also via Data > Operations, allows you execute R scripts to transform your data, such as performing k-means clustering. It is currently in development.

Feel free to explore it and the "Data > R Statistics > R operations library" dialog.

Behind the scenes, it works be taking one or more input datasets and optional input parameters, exporting the data and values to R as variables, executing the R script, and importing the data back, which becomes the output of the operation/block.

You can either build up a library of scripts which you use later, or can cut your own scripts ad-hoc in each block. We'll be providing (soon) a set of bundled scripts with Omniscope for performing common statistical tasks such as clustering, so you can perform these tasks without any knowledge of R.

When you design a script, you specify how many input datasets it has, and how many input parameters (and their types / configuration). You then write the script, with the corresponding variable names listed at the side.

When you use a script in DataManager, you pick from the library, link up one or more input blocks, and customise the values for any parameters that script has, before clicking Execute. For example, k-means clustering would have 1 input dataset, which must already be normalised, and would require you to tick the fields to perform clustering upon, resulting in the original data table with additional fields containing the cluster number and other statistical results.