When scientists observe, they aren’t just “looking around” — they are capturing information that can be measured, counted, or described in a way others can understand and verify. This measurable information is what we call data.
Think of it this way:
Without data, your observation is just a personal impression. With data, it becomes evidence that you (and others) can analyze to answer questions. It’s what allows you to:
To translate your observations into data, think about:
When you decide what you will measure and what units you will use, you are also identifying your variables:
Example:
By identifying your independent variable (x) and dependent variable (y), you make your data collection more focused and your research question clearer — which will help you design a project that’s measurable and doable within your two-week Naturehood data collection window.
Here are ways you could turn a simple observation into measurable data for your project:
| Observations | Data |
|---|---|
| “There’s a lot of trash in the park after weekends.” | Count the number of pieces of trash within a 10-square-meter area every Monday morning for two weeks. |
| “The flowers in my neighborhood attract bees.” | Count the number of bees visiting a specific flower bed in 10-minute intervals at the same time of day over 14 days. |
| “One side of the park looks drier than the other.” | Measure soil moisture in three spots on each side using the same tool at the same time of day for two weeks. |
| “The playground is busier in the afternoon.” | Record the number of people using the playground every hour between 12 PM and 6 PM for 14 days. |
| “The pond seems greener than last month.” | Measure algae coverage as a percentage of the pond surface once a week for two weeks, using a photograph grid for consistency. |
| “There are fewer birds near the road than in the trees.” | Count the number of birds spotted in a 5-minute period at both locations each day for two weeks. |
| “I sometimes see coyotes in the park at dawn.” | Record the number of coyote sightings per morning over a 2-week period, noting the time and location of each sighting. |
| “Crickets seem to chirp more on warm nights than on cooler ones.” | Count the number of cricket chirps in a 30-second interval at the same location and time each evening for two weeks, noting temperature and weather conditions. |
| "There are more people using a park bench around 6 pm." | Count the number different people who sit there in 30-minute intervals over two weeks. |
Collecting data is only the first step — to understand what it means, you need to see it. Graphs and charts turn raw numbers into a picture, making it easier to spot patterns, trends, and relationships between variables.
In your Naturehood project, visualizing your data can help you:
For most projects, a scatter plot works well because it shows how one variable (your independent variable) relates to another (your dependent variable).
Once your chart is made, you can quickly interpret patterns: upward or downward trends, clusters, or no clear relationship at all. This visual evidence strengthens your conclusions and makes them easier for others to understand.
You will learn how to graph your data in one of your classes. To reinforce your learning, watch the tutorial below to see data graphing in action using Google Sheets.