play with the data long enough and it becomes possible to find a way to see patterns in it

One of the things I’ve been struggling with in my current research is how best to communicate the results from the various experiments I’ve run. My experiments have thus far yielded a total of ten different phases, with as many as seven of them appearing in a single experiment. I use two different capsules at each pressure and temperature at which I run experiments; each capsule has a different bulk composition. Therefore I’ve been displaying the result graphically, by using 8-pointed stars divided into an inner ring for one of the composition types, and an outer ring for the other. The resultant triangles representing the phases present are either left blank if it isn’t present or filled in with colour-coding if it is. One phase, quartz, is always present (save for when we reduce the starting SiO2 to eliminate it), so it doesn’t need a triangle of its own, and another occurs only in one high-P run, so it appears as a different colour triangle replacing one attached to a low-P phase; this is why I’ve been able to get away with using only eight points for the star.

However, there are times when it is necessary to communicate with text or a table, rather than with an illustration, and this is where I’d been stymied. I simply wasn’t seeing much in the way of a pattern with my data in terms of mineral assemblages. A mineral assemblage is the group of minerals which are all stable at the same pressure/temperature; they would have been the products of the reaction(s) which produced the assemblage. (When doing experiments we talk of phases rather than minerals—a phase is a particular composition of a mineral (many minerals can have more than one possible compositions, so may be considered a family of mineral phases)—in general only one phase within a family will be stable at a given set of conditions) .

Today I finally discovered a way to organize my data so as to see patterns in the assemblages. This required using colour coding and playing with the data, combining them into groups until I was able to determine that the “important” phases of the list of 10 are talc, garnet, and biotite. The others are either ubiquitous (quartz, chloritoid and muscovite) or only show up in a few of the runs and can be considered "minor" (zoisite, lawsonite, kyanite, carbonate). Once I’d worked that out, I was able to split the data into four groups each of which are +/- the minor phases and + the ubiquitous phases.

However, it was also necessary to consider each of the two bulk compositions separately to see the relationships between the groups, and I had to draw circles around the stars on my original P-T diagram to see how the groups relate to pressure and temperature. (I love having a drawing program which lets one draw circles on layers that can be made visible or invisible, so that one can see only the circles relevant to a single composition at one time.) Once I had all of the groups for each bulk composition circled it was easy to see that:

The experiments using the metagreywacke composition only have groups A, B, and C thus far. These groups plot on diagonal trends for this composition such that with respect to temperature B is less than both A and C, but with respect to pressure C is less than both B and A.

The experiments with metapelitic composition have groups A to D which plot in a grid such that with respect to temperature B is less than A while D is less than C and with respect to pressure C is less than A while D is less than B.

Now that I can see these patterns I shall really look forward to obtaining the results from future experiments to see how they relate to this overall pattern.