Plant Height 3D Print

By Corwin Smith

This was the result of the plant height being printed on the 3D printer. I experimented with whether having the plant height really tall and far apart, or shorter and more together would give better results. I feel the right one with the taller and more spread out data points turned out to be more successful in this situation.

Hagberg Falling Number Lattice

By Corwin Smith

For my second project where I created a lattice structure based off of the Hagberg Falling Number. What I did was use the Grasshopper definition used to calculate averages (created by Denton Fredrickson) and added on to it to make a definition used to create these graph structures for both location, and rye type. I then lined them up so that the graphs for location and rye type lined up and it created this interesting lattice structure which I then made into a physical object.

Grasshopper Sketch

By Corwin Smith

This is the grasshopper definition in Rhino which was used to create the graphs for the lattice structure. In the green area is where the agronomic data is pulled in and averages are generated (The Agronomic and Grain Quality Averages portion of these Grasshopper sketches were done by Denton Fredrickson, and I utilized the framework he had created to add on and create my projects). In the grey area to the right is the stuff I did to take those averages and create the agronomic data. I created points which were placed from this data, and then lines were drawn between the points to create the final result before lining them all up. This could have been more efficient but it worked for what I wanted to do and I was happy with it.

This is the result of a suggestion made by Denton to use ranges in my grasshopper definition. This led to some research on how the range node worked, and I was able to make this definition which was much smaller and more efficient than what I have shown before in the media samples. The nodes in the grey area were what I put in to make those graphs, and you can see that it is much smaller and to the point that what I was working with before.

Musical Mapping in Relation to Hagberg Falling Number

By Will Austin

The Long Drawing functions similarly to my first project, but instead graphs both ergot and protein percentage in response to a movement through decreasing Hagberg Falling Numbers. The cultivars and locations were again gridded, this time in order of average Hagberg Falling Number. The data is drawn with a point for each of the fourteen locations repeating through all fifteen cultivars (unlike in the painting, which is a movement through all 15 cultivars in each location sequentially). The song sounds with two overlaid melodies of 14 notes offset slightly, with the melody responding to protein % one octave higher than that of ergot %. Each note in the melody corresponds in frequency to relative protein/ergot percentage, within a specific location. The fourteen note order of locations stays the same while proceeding through each cultivar. All data is sounded relative to the whole set within two octaves of the B-flat minor key.

Musical Mapping Ergot and Protein

By Will Austin

The painting contains a graph of % ergot ordered from average highest to lowest in both dimensions (cultivar vs. location), and a graph of % protein following the same order of cultivars and locations. The song which it accompanies is in the key of E minor, with fourteen 15-note melodies each divided by a full note rest. The variable of time is the movement through the 15 ‘cultivars’ (breeds) of rye from the least prone to ergot (fungal disease) to the most prone, repeating in structure through all of the studied locations from least prone to ergot to most (14 locations). The notes are determined by the relative percentage of protein divided through three octaves of E minor. Each registered breed is given a half note sustain, and each non-registered breed is given a quarter note. There is a bass drone under each 15-note melody which is the average for the current location across all breeds, dropped two octaves. It is meant to function generally as a graph of the correlation between ergot incidence (increasing as time) versus protein percentage (of grain).

Exploring Heading Date, Maturity Date, and Grain Yield

By Taelynn Graham

This was my first attempt to visualize this new data set. I was initially interested in making some of the time-based data appear in a linear fashion, as this was something I hadn’t done yet in my data viz experiments. I decided to look at if there was a relationship between the date the heads emerged to its maturity date, and if that had an impact on the yield of those crops.

The overlapping circles are drawn for each rye type at each location, and the size of the circles are reflective of the yield. The four rows represent each province the rye was planted. From top to bottom: Alberta, Saskatchewan, Manitoba, and Ontario. I think it’s interesting how Alberta is much more consistent in maturity date and has higher yields than Saskatchewan or Manitoba.

Kernel Size Grid with Ergot Percentage Colour Overlay

by Russell McMurty

This project was originally an experiment that revolved around showing data for every cultivar and every city at the same time. This, much like my first project, is written in Java on a program called “Processing”. This image created a sense of scale for a viewer of the size of rye kernels across the entire data set. Then using colour, I add another level of data by comparing instances of ergot growth across all of the cities and cultivars.

On the whole I was very impressed with this project. I was excited that it showed relationships between kernel size and location/cultivar that the scientist we had be working with confirmed are well known in rye breeding. I was extremely cool to learn that I was uncovering other, new relationships as well.

I would like to expand this project to cover more portions of the data. I was very content to have the size of the ellipses have a spatial connection with the size of the kernels. Upon more learning, I’ve decided that this visualization would be equally impactful when it contains other bits of data too.

Number of Galls on Main and Lateral Stolons

By Linda Shi

This model represents data collected by counting the number of galls found on main and lateral stolons of Whiplash. The four sizes of rings represent four stages of stolon growth from largest to smallest; we see the stolons in their old to super young stages. I have also chosen green zip ties to be the colour for main stolons whereas black ones represent lateral stolons. 
By building this physical model, I’m able to see, group by group, on what type of stolon or which stage of stolon growth is the wasp more prone to lay their eggs. I’ve noticed that on the main stolon, wasps are more attracted to the young and super young stages of the stems, whereas on the lateral ones, more galls are found in the oldest stage of growth. One thing to keep in mind is that the lateral stolons sprout later than the main stolons. This difference in time could potentially result in the differences we see between galled stolons. I’m interested in the potential architectural installation of this model. In a built project, I want to see people become part of the data and have a 1:1 scale interaction with it.

Cloud of Rings

By Linda Shi

In my final project, I’m taking the data I learned from Project one and the skills I’ve accumulated from Project two, to put together a larger skill installation in the presentation space. 
My Cloud of Rings, instead of using the different sizes of rings to represent different stages of plant growth, I’m using the thickness of the rings to do so. By reversing the dark and light colors of the stolons, this color representation of the main and lateral stolons are more accurately displayed. Since the main stolons have grown for longer periods of time, they are thus represented by the darker colors. 
Having the Cloud hang right above the hallway, I invite visitors to walk under the installation. The six strings hanging the are proportional to the number of total galls collected from each study. 
The rings above overlap each other, creating various densities in the surface mesh. I hope this creates an interesting experience for those who walk below it. I hope to bring this project further by becoming more proficient at Rhino and Grasshopper. I would also like to use the 3D printer to construct smaller mock-up models of future interactions.

Galls on Main and Lateral Stolons Voronoi Map

By Linda Shi

Taking the physical mock-up model one step further, my second project renders a pattern that evokes the same set of data from my first project.

Using 3D modelling software, Rhinoceros, and its plug-in parameter modifier, I was able to manipulate geometries on the plane. Using the parameter Voronoi, the maximum area is drawn around each point defined on the plane. I’m drawn to the mathematical and structural properties of the pattern, creating interesting dynamics between each of the defined points:

I want to use this pattern to represent the data collected. This pattern can easily be translated into a surface or screen that defines a specific architectural space. This will allow people to interact with data while navigating around the architectural installation.


By Kiri Stolz

This sketch represents the average number of galls in each of the six greenhouses that the bio-control experiments were carried out in. Each square represents one of the greenhouses, and the saturation of the colour is indicative of the average number of galls that had been created by the gall wasps at the end of the experiment. The idea here was to take the data back into the environment from which it came, and possible reveal new information about the space itself, and how that could have contributed to the production of galls or “fertility” of a particular greenhouse.

I was later made aware that some of the experiments were started later than others, which contributed to the low fertility rate in the top-leftmost greenhouse square. However, this data visualization led me to ask the questions necessary to learn more about the experiment than I had expected.

Galled vs. Ungalled Portions of Hawkweeds

By Morgan Bath

All of the projects that I created this semester dealt with only the galled vs ungalled and did not focus on the lateral and the stolen figures. The works on paper are drawings of hawkweed seeds which were then manipulated to represent the ungalled portions of the plant that still have the ability to grow and the holes represent the lack of growth that the gulls created. The colours of the papers represent different plant growth stages as well as in the colour of the warp strings on the weavings I started.

The sounds piece that accompanies the works on paper is a creation from using the data provided for each plant stage and using the frequency of each number to create ten-second interval sounds of each plant stage and type. This piece I think was very successful, it is straight forward but I don’t think it is too literal, like the other pieces, right up front. I used two types of sounds wave one to represent galled and one ungalled and then just inserted the data set into the program to generate the sound clips.

Re-Assessing Stolon Growth with Attention to Galling in Hawkweeds

By Keith Morgan

My previous visualizations had given me a few assumptions about the trial that seemed to go against some of the hypotheses of the researchers. I had come across a trend that seemed to show that when introduced to the biocontrols at certain ages, the hawkweeds tended to grow more stolons rather than fewer. What I had not taken into account when exploring this was what the galls themselves were doing: how were the galls dispersed on the plants, and did this have an effect? Again, I severely averaged out the data, this time combining all of the trials and all of the ages for the test group as one entity, and the control group as another. The key metrics for this visualization were the total average number of main and lateral stolons that grew on one plant, the average number of main and lateral stolons that had galls, and finally the average total number of galls per plant. Assuming that a galled stolon is considered ‘dysfunctional’, these new numbers actually reversed my original assumption that while galled plants tended to have more stolons on average, they actually had fewer ‘functional’ stolons. In my visualization, only these functional stolons grow to full length.

Comparing Gall Formation on Main and Lateral Stolons in Whiplash and Mouse Ear Hawkweeds

By Keith Morgan

This was my first encounter with the data set, so in order to get familiar with the metrics and patterns in the data, I chose a straightforward representation to keep myself grounded. I attempted to show the number of main and lateral stolons that had been galled, in addition to the total number of galls that had formed on each species. These sets were expressed as the height of each collection of blocks in relation to the top of the clear walls on the sculpture. 
My process involved combining the data from all of the ages of the plants in each trial so that the comparison was left to differences between species instead of age. What this allowed me to do was show that proportionally speaking, the Whiplash species had more main stolons galled, while Mouse Ear had more lateral stolons galled. Still, when we look at the total number of galls that grew, it became apparent that both species grew an almost identical number of galls.

Crocheting the Relationships Between Galled and Ungalled Stolons

By Taelynn Graham

This visualization uses the exact same data as my interactive digital visualization. I decided to represent the length of each section with crochet stitches, and they became quite lengthy, which shows how much spreading the Hawkweed plants actually do. I want people to be able to really understand the proportion of stolons being galled, and having a tangible object that you can hold and stretch out really shows this in a way that isn’t quite as easily understood by looking at a digital shape. 
My intent was to keep the colours the same for both visualizations, so that viewers an easily move from one visualization to the other and be able to recognize that these are in fact the same pieces of data. The mounted crochet strips with a single strand down them represent the stolons galled and the average number of galls on these stolons. This is an added piece of data included to show how many galls exist in each section, and what it means in comparison to the proportions of galled stolons. Just because there are a lot of galls does not mean that the proportion is substantial.

Galled vs. Ungalled 3D Bar Graphs

By Corwin Smith

For this representation I wanted to show a comparison between galled and ungalled stolons in Whiplash. The green graphs represent the main stolons of Whiplash, and the yellow represent the lateral stolons of Whiplash. The graphs are separated into rooms, and then ages of the plants within the room. I always find 3D graphs on the computer to be very bad because of perspective, so I wanted to see if that same problem comes through when 3D printing the graphs of data. They were luckily much more effective as an actual 3D object than on the computer, and really allowed an interesting interaction from the viewer as they held it and were able to touch and look at it from all different angles.

Stolon and Gall 3D Print

By Corwin Smith

This stolon and gall 3D print was made to show a larger scale representation of what the data was being collected from. Cylinders that fill the galls on the inside of the stolons give information about galled versus ungalled stolons relating to the age of the plant. This stolon shows the data collected from the main stolons of Mouse Ear. I was hoping to show what the stolon looked like with the galls to add to the understanding of what is being represented by this data. The cylinders used to represent area inside a gall were used to show the ratio between galled and ungalled in the different ages.

Total Gall Count in the Main and Lateral Stolons for Mouse Ear Hawkweed

By Corwin Smith

The graphs represent the total gall count in the main and lateral stolons for Mouse Ear. The red represent lateral, yellow represents main, and green represents the total of both main and lateral. I was hoping to create these graphs to give an interactive aspect to them, where the user may swap them out and compare the different aspects of the data very easily.

Since it is a 3D object and can be moved around and interacted with, it brought a very unique feeling to the data when viewed the first time. It allowed myself to display a lot of data points efficiently and without the clutter that would happen with a similar 2d representation. This would allow them to compare parts of the data they need to.