To develop data-driven feedback loops for urban systems by creating landscape variables.
Exercise Instructions
In this exercise, you will decompose the ecological relationships identified in the last exercise into tractable parameters that can capture the solution space of your research question. Then you will develop variables that use those parameters to compute a value of a particular data type. As you do so, you will move your structured observations of the physical world into a computational space. There will be two tables produced as a part of this exercise, each building on the other, designed to help you move through the complexity of digitizing the physical world.
Data representation of final table. Explain the desk research involved in the development of your part parameter and environmental parameter.
Final visual representation for each row of in the data table.
Abstraction of visual representation.
Data Representation Instructions
Definitions
Part Parameter : Measures associated with the part.
Environmental Parameters : Measures associated with the environmental factor.
Landscape Variable : Computes an unknown quantity or quality about the ecological relationship. Binds the Part Parameter and Environmental Parameter into a single generative and tractable digital value.
Variable Data Type : Describes how the parameters in the variable compile. Slightly different from how it may be taught in a technical class; the data type name used here are designed to be friendly to humans. For example, floats or integers are numbers. Variable data types can be a number, category, boolean, image, or video, but this list is not exhaustive.
Machine Learning Concepts
This exercise requires some basic background knowledge of machine learning pipelines. We will review this in class. You should have taken notes. If not, ask a classmate. In the visuals provided, the ones that require this understanding is marked in neon green.
Step 1: Urban Object and Environmental Parameters
Copy and retain the Part ID, Part Name, Environmental Factor, Ecological Relationship, Observations, and Observation Range data outputs from the last exercise into a new table.
Between Observation and Observation Range, create two columns and label them Part Parameter and Environmental Parameter.
Break down Environmental Relationship into Part Parameters and Environmental Parameters. For each row, fill in the part parameter and environmental parameter associated with the part and environmental factor, respectively.
Parameters need to be associated with either the urban object or the environment. This can be tricky. Decide based on which will be theoretically generating the values for that parameter, that will eventually need to be collected as data. A good rule of thumb is that the parts are static and always there, whereas the environment is consistently changing or mobile. Your parameters may be qualitative or quantitative.
For categorical observations of your ecological relationship, you will digitally translate the observation into a placeholder taxonomy. This placeholder taxonomy includes the set of observations that was collected during your inventory audit, but also includes observations that were not observed and is therefore unknown. In the case of the debris type for example, there may be other unknown debris types outside of the ones observed during your survey. Each taxonomy should be accompanied by a tag.
By the end of this step, you should have developed data outputs Part Parameters and Environmental Parameters and related this to Part ID, Part Name, Ecological Relationship, Observations, and Observation Range from the last exercise. This is will be your first table.
Develop the visual representation for this step to help you iterate when you get stuck.
Step 2: Landscape Variables and Variable Data Type
Copy and retain all data outputs and values into a new table.
Between Environmental Parameter and Observation Range, create two columns and label them Landscape Variable and Variable Data Type.
For each row, create a Landscape Variable and define its Variable Data Type.
Develop the visual representation for this step to help you iterate when you get stuck.
Prior Student Examples
Assignment has changed significantly. No example available. Follow instructions above.
Visual Representation Instructions
Step 1: Sketch Data on Base Drawing
For each ecological relationship, develop a sketch data visualization of your part using your base drawing that illustrates how the environmental factor interacts with it. In the example above, the areas where debris appears on top of the grate is shown in pink, and the impacted holes highlighted.
Imagine what needs to be seen in order to enable the ecological relationship.
Step 2: Visualize Part Parameters and Environmental Parameters
Extend the taxonomy by visually representing the dynamic relationships of the part parameters and environmental parameters for each ecological relationship.
Feel free to develop your own style, but make sure table elements are shown / extended in your diagram in a legible and clear manner.
Look at precedents of drawings for inspiration.
Step 3: Visualize Landscape Variables
Develop your diagram further by incorporating the landscape variables.
Show how the part parameter and environmental parameter feed into the landscape variable.
Feel free to develop your own style, but make sure table elements are shown / extended in your diagram in a legible and clear manner.
Look at precedents of drawings for inspiration.
Step 3: Create Abstraction of Diagram
Once you've design and developed a form for all your diagrams, create an abstraction encompassing all the possible configurations.
Prior Student Examples
Assignment has changed significantly. No example available. Follow instructions above.
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