Evidence based science mandates full disclosure of scientific data and ancillary experimental metadata payload. Only this data provenance can warrant the possibility of reviewing findings and claims. Reports should therefore contain information about biological materials, their treatments and the molecular dimensions being surveyed and the methods to perform those measurements. The ISA-Tab format  provides a generic grammar to organize and structure experimental information and linking it to matrices of results. While spreadsheet based representation is popular as a natural interface, devising new means to graph experiments and sample processing workflows can allow for more immediate understanding of overall experiment design. In particular by mimicking the practice of drawing experimental groups and applying the technique of dimensionality reduction, we are working at devising more engaging, compact and informative renderings than techniques currently available. We posit that the same techniques could be used to plan experiments and drive data acquisition (therefore providing game changing means to data management).