- What is your team’s data strategy? How will you acquire, apply, analyze, and visualize data for your project?
In order to measure the effect on the wellbeing of Lehigh students and faculty, we essentially have broken our data strategy down into three categories: air quality, student attraction to the structure, and effects on mental health. To measure air quality, we plan to use an air quality meter, which can provide us with readings for ambient temperature, humidity percentages, CO2 levels, and volatile organic compound (VOC) concentrations. To measure student attraction to the structure, we would record the area either by physically being there and taking tallies throughout the day or recording the particular area. We are also considering collecting this data via surveys, however we are still uncertain of this because we are concerned about the data bias that would come with this method of collecting data. Finally, to measure mental wellbeing, we would measure things such as stress, creativity, and perceived happiness through surveys and interviews with students. Through this method, we would need to specify where the students answering the survey spend their time on campus, as well as take into account possible confounding variables such as changing seasons or other potential things that affect moods/stress.
One thing common to all of the measurements we seek is that we would take multiple collections of them before and after the implementation of our living wall/green space so as to see how these readings fluctuate over time. For the after specifically, we would analyze measurements collected in both the short and long term to see both immediate and long term effects of the living wall. For measurements taken with the air quality meter, this will show how variables such those listed above will first begin to change and then eventually regulate over time. For student attraction to nature and mental health effects, if people were to gravitate to the structure more over time, this would give us a lot of insight into both how many people are attracted to nature/the importance that nature holds to them, as well as to the positive mental health effects that nature can have on people.
2. What data will be needed for the short-term success of your project (thinking of the next 4-6 months)? What data will you track in the longer-term (2-5 years)?
Short Term:
Over the next few months it is crucial for us to gather information that will serve as the foundation of our project. This both includes data that proves the existing need for our structure, as well as data that are necessary for prototyping. Specifically, we will need to find existing studies and data that exemplifies a correlation between people being exposed to plants and an increase in wellbeing, as that is the core of our project. This also includes gathering our own data from Lehigh students by conducting surveys to get a better understanding of their wants and needs before we begin prototyping. In terms of data for the structure itself, we will need to gather data on how our plants grow under certain conditions (i.e different light wavelengths, temperature, water pH, etc.), so we can create the most efficient system possible.
Long Term:
Once a structure is completed, we plan to conduct experiments to measure the structures’ effects. Metrics that we are currently planning to track in the long term include air quality & humidity to show the structure’s effects on the indoor climate. Additionally, our team has mentioned the idea of tracking if students frequent the area more often once these structures are implemented to measure if students are more attracted to this living area. Finally, once the structures are implemented, we plan to conduct studies that measure differences in students’ stress, creativity, and perceived happiness when in one of our living spaces vs when in an arbitrary location. Our group does plan to start investigating some of these long term goals once we have a working prototype, which leads to some overlap between our short and long term goals.
In the longer long term (try saying that 5 times fast), we want to create more than one of these living spaces on campus. When this process occurs, an additional metric will be the sheer quantity of structures/living spaces on campus. This metric is linked to our goals of making nature more accessible to the lehigh community year round.
3. What data will your project create and share? Who might use that data and how? Provide three compelling examples of use cases for your data.
We want to measure the perceived mental health benefit of the wall, as well as the change in air quality, noise reduction, and success of particular plant growth. Some of these are comparative–we need to measure them before the wall is installed and then after its installation. One of those is perceived mental health benefit. The data we record on perceived mental health benefit of users is greatly useful to people looking for a reason to install a living wall, or people who are trying to find ways to improve their workspace. If our wall shows that people feel better when working in the presence of a living wall, that is greatly useful to people who are trying to increase employee wellbeing. If our wall shows that people feel worse, or there is no change, it is still vital data–it is important to know what aspects of the workspace could be harmful, or know that building a living wall will not be money well spent towards wellness goals.
Data on the success of our plant growth is not necessarily for external use–we ourselves and future members of the project would use this data best. If we record the specifics of how plants are growing in certain areas on the wall and how they interact with each other, we can make sure that we maintain the wall in a way that promotes the most possible greenery, pushing further towards our end goal of improving mental health. This data isn’t exclusively for our use, but it is most important for us–there is already published data on what particular plants require and what we are creating is very specific to our project.
As stated earlier, we would also like to measure the effect of the immediate air quality that the living wall has. Collecting data to see whether the immediate area around the living wall has better air quality would not only help us determine the effectiveness of the living wall, but it would also benefit Lehigh students as well. It would also be beneficial for Lehigh Valley as a whole, since “Lehigh Valley ranks fourth most polluted in PA, worse than Philly and Pittsburgh”. Future college living wall projects can use our data as well, since there isn’t that much data about living walls on college campuses and how effective they are. Also, future living wall projects for Lehigh specifically can also use our data, since our living wall may not be the only living wall on campus within a couple years. I think that air quality will be an effective way to measure how well the living wall truly fits on our campus.