Lab 2 – The Display of Oceanographic Data
This chapter was created as a data skills precursor to the rest of the data lab chapters. It is meant to assist students in understanding data visualizations that they will encounter in the later activities. The chapter is scaffolded with increasing difficulty so that students are introduced to the different data visualization types in the introduction and then practice or apply their knowledge in each of the lab activities within the chapter.
Approximate Time Involved
- Each of the 5 activities may take 30-50 minutes for students to explore, discuss and complete the assigned questions.
- Instructors should plan to implement this activity prior to other Data Labs as background on different types of data visualizations and their interpretation.
- Alternately, instructors can use different Lab 2 activities prior to other lab activities that use similar data visualizations. The top of each Lab 2 activity lists its alignment with later lab chapters.
After completing this lab students will be able to:
- Identify key components of a scientific graph (axes scales, legends, multiple y-axes).
- Describe data patterns such as minimum and maximum values, trends over time or distance.
- Recognize graph types commonly used in oceanography (time series, station profile, vertical section contour plot, bubble or vector map).
- Discover that real-world data can be quite variable.
- Identify gaps in data and infer likely reasons for the gaps.
- Describe the oceanographic convention of plotting depth increasing down for station profiles and vertical sections.
These learning outcomes are introduced and practiced in the Lab 2 activities as follows:
|Learning outcome||Activity 2.1||Activity 2.2||Activity 2.3||Activity 2.4||Activity 2.5|
|1||Introduced||Guided practice||Guided practice||Guided practice||Applied|
|2||Introduced||Guided practice||Guided practice||Applied||Applied|
|4||Introduced||Guided practice||Guided practice||Applied|
None for classes with student access to a computer or tablet. Instructors might optionally supply printouts of the graphs and questions if in a classroom without computers.
What students should know before this activity
This lab activity introduces students to basic data literacy by stepping them through not only different types of data visualizations but the basics of how to read each data visualization.
Background that would assist students while completing the lab exercises include
- Scientific method and data collection – why we make data visualizations from raw data
- Basic features of a graph, including x-axis, y-axis, axes labels, scientific units
- Bathymetry and ocean basin features helpful but not mandatory (Activity 2.2)
- Latitude and longitude (Activity 2.2 and 2.3). Lab 1.3 introduces this concept.
What instructors should know before this activity
This chapter is a good chapter to cover early on in an introductory oceanography course or use as a refresher for upper level courses. The activities are designed to be completed in order. However, they may also be used individually as pre-labs to some of the later data lab chapters. For this reason, each Lab 2 chapter was developed as a stand-alone module.
Students may have seen data visualizations that are similar to those in this lab activity; however, they may not understand how to read those visualizations or graphs. Introductory students may not be familiar with graphs that show high variability. In addition, some students may have weak skills in how to read the graph at all. Please don’t assume that your students in introductory courses fully understand graphing or how to read graphs.
Real scientific data are often noisy, yet we tend to distill the information down into overly simplified data visualizations in textbooks. It’s important for students to realize that there is variability within data and to be able to identify major trends embedded in realistic data. As scientists we have the ability to look beyond the variability to see increasing or decreasing trends, seasonality or diurnal trends, but these are often missed by introductory level students (see Kastens et al., 2016 in Resources below). This chapter is scaffolded not only with different types of data visualizations that the students will encounter in oceanography and other science classes, but also with increasing complexity in data skills.
Instructors should familiarize themselves with the different types of data visualizations that the students will encounter within this activity.
It you are in a classroom or lecture hall without computers, you can either ask students to bring in their own laptops to work on the activities or project the graphics and have them answer the questions working in groups or as a discussion. Alternately you can go over the introduction to this activity explaining the types of data visualizations and assign the activities as homework.
A good introductory video, embedded on the Lab 2 introductory page, is the Tools of Science: Data as a Tool that explains oceanographic data collection and analysis, with reference to the OOI system. This video also introduces the Orientation-Interpretation-Synthesis framework for approaching datasets that forms the basis of activities in this and subsequent lab chapters.
Prior to this lab instructors should have already covered the scientific method and data collection in an effort for students to understand why there’s a need to turn raw data into data visualizations.
Instructors also may want to refresh the student’s memory on how an average is calculated, and its uses or misuses.
A helpful activity as a lead-in to the data skills lab may be to have students practice making general observations. Being able to describe what they are looking at is very important. In addition, trying to put what they are observing into context with their existing knowledge can help in student understanding and tap into higher order thinking skills. Using a gallery walk can be a good observation activity for introductory students by showing partial figures or graphs to simply get students talking about what their observations are in groups. Having students describe a variable that is increasing or decreasing, cyclic, etc…, without the axes/labels and without knowing what the variable is, can be very important first step to making simple observations.
Students often misinterpret the lack of data as a decrease to zero. It’s important for students to understand that a gap in data is the lack of data. They need to realize that scientific equipment sometimes fails or gets fouled and may not record data during a certain time period. We have purposely included a data gap within an activity.
In comparing different graphs students may forget the importance of scale or units on the x and/or y-axis. There have been many expensive and/or dangerous errors when mistakes are made. Point out the potential to misinterpret the comparison when scales are unequal. This is especially important since some graphing software, such as Excel, defaults to scales that depend on the data. As a result two different data sets can result in very different scales but similar graphs. The following article details some famous instances of mistakes, some funny and some tragic that are good examples for why scale or units are important: Great miscalculations: The French railway error and 10 others
The Introduction to Lab 2 refreshes students on basics of interpreting scientific visualizations. This includes careful orientation to axes and scales, identifying trends, understanding variability in realistic data, and visually interpreting correlations between two variables.
Activity 2.1 is an introduction to time series plots, and training to have the students really examine the information in any graph. Although there are a lot of questions, many of them are orientation questions and quickly answered. Note that the first four figures are static. Estimating values from such graphs means that there will be variability in student responses. Figure 2.1.5 is active, as you position your cursor over the graph exact values are displayed. And, you can use the sliders to focus on a smaller subset of the data. Many of the graphs used in the labs are active, so this represents a first introduction. But, students should feel comfortable estimating values from static graphs. In this activity students are also introduced to gaps in data and to the concept of averaging of data. Since temperature data is used in this exercise, if you have discussed air and/or ocean temperature in your class you can use this exercise as an opportunity to reinforce the seasonal trends.
Activity 2.2 is an introduction to bathymetric charts and bathymetric profiles. It’s important that students understand latitude and longitude prior to this activity. Bathymetric charts will help students understand that there can be different visualizations for the bathymetry, some more exact than others. Navigation charts frequently have depths as soundings, in addition to contour lines and colors indicating depth. Bathymetric charts used in scientific investigations frequently provide depth information using a color scale since this may provide a better visualization
You may choose to start this activity by having students contour some depth data. This PowerPoint file can be presented as a practice exercise (PDF version). One of the slides can be printed for the students to use. Choose from one of the two slides, one with just depth points, or one with the depth points and one contour line already drawn. The students should draw the contours, and label them. You may also choose to have them color the map, to make the link to the color coded contour maps shown later in this exercise and in the lab manual. You can then show the PowerPoint so they can see the solution.
This activity includes a short video showing how to make a bathymetric profile from a contour map (copy of PowerPoint file shown in the video). If you want your students to follow along provide them with a print out of the chart and the graph paper (link to printable PDF). As a follow up to the video activity you can assign a second bathymetric profile exercise which you may choose to collect and grade, using the following handouts of the West Flower Garden Bank or your own contour maps.
The exercise explains vertical exaggeration in bathymetric profiles, but it is worthwhile to discuss the concept with the class. Introductory oceanography textbooks show bathymetric profiles, and with a poor understanding of vertical exaggeration students often think the sea floor is steeper than it actually is. You can drive home this point by either having the students, or you, calculate the angle of slope for the two examples given in the exercise. This will give them an opportunity to see trigonometry in action.
Activity 2.3 introduces students to the use of bubble charts. In oceanography some data sets make use of this style of chart to show how one or two variables changes as location changes. In these cases the bubbles are placed at the geographical location of a measurement, and the size and/or color of the bubble is used to indicate one or two variables. The choice of size or color to indicate a variable is more intuitive in some cases than in others. An example, given in the exercise, shows oil spill size indicated by the size of the bubble in one case, and the color of the bubble in the other. Since the scientist is trying to show the size of the spills, the choice of size of bubble makes more sense, although neither choice is “wrong”.
The reflection questions in this section ask students to ponder maritime disasters. Students are asked to think of a reason ships might sink in deep water, and if this variable would be effectively plotted on a bubble chart. If they choose storms as a reason, a variable like storm size or proximity of storm center to vessel would make an effective bubble chart. But if they choose a variable such as human error, flooding, or collision an effective bubble chart is not possible. These questions give students the opportunity to see that not all data products make sense for all types of data.
Activity 2.4 introduces a very important oceanographic data product, the station profile. Station profiles are useful at sea, where scientists examine them to make decisions about taking samples, and they are useful as a way of examining and illustrating water column structure.
Prior to this activity instructors should review the importance of scale on graphs. The activity asks students to compare temperature station profiles from two stations, one in the Irminger Sea and one from the Pioneer array. When students first access the activity the depth and temperature scales are not matched. As they work through the questions they are directed to match the two scales, done by checking two boxes. This is a nice illustration of how invalid comparisons may result if one doesn’t note the scales. If teaching this activity in the classroom you may use it as an opportunity to discuss the impact of latitude on temperature structure in the ocean.
One of the goals of Activity 2.4 is getting students to understand the oceanographic data may be plotted slightly differently than what they see in a typical math class. Common misunderstandings occur when students don’t understand why zero is at the top of a y-axis. Explain that zero is the surface of the ocean and increasing numbers on the y-axis represent depth. We typically use positive numbers increasing downward because it’s understood that in oceanography we deal primarily with depth below sea level instead of height above sea level. Students will encounter this axes orientation on station profile and vertical section graphs.
This activity provides an opportunity to either teach about, or reinforce, the concept of the thermocline. Instructors may want to explain what a thermocline is and what it looks like on a station profile graph. A common source of confusion is that on station profiles the highest temperature gradient (the thermocline) is where the curve is the flattest. If using the activity in class you many do some math on the board to calculate the change in temperature with change in depth for the thermocline and for another part of the water column. Students don’t always realize that there’s variability within the water column in the oceans. As instructor you may want to draw on their previous knowledge about characteristics of a water column. For instance, ask if they ever jumped into a deep pool or water body in the summertime when the water may be warm on the surface but they hit a small thermocline and cooler water underneath.
Activity 2.4 mentions The Blob and The Ridiculously Resilient Ridge. If you are interested in more information this link provides a more complete description of this phenomenon. If, in your class, you emphasize the impact of climate change on the ocean the example of The Blob provides an opportunity for you to explore this topic through a particular example.
Activity 2.5 is an introduction to vertical sections, an important data product for visualizing the change in water column properties, with depth, over a horizontal distance. In this activity we explain the relationship between station profiles and vertical sections. Students sometimes have a hard time visualizing the station profile from the vertical section. Students may also confuse the vertical section contour lines for depth contour lines instead of the property such as temperature or salinity. You may choose to have students contour a vertical section in this activity. Provided here (PowerPoint file) is a salinity vertical section exercise from Penobscot Bay in Maine. The last slide may be printed out and given to the students. The PowerPoint provides some background, some instructions, and the solution. A color contour vertical section is also shown. You may choose to have your students color in their contoured data product.
Optional post-lab assessment
After completing Activities 2.1-2.5, student knowledge of the common graph types can be assessed with questions on this page: https://datalab.marine.rutgers.edu/ooi-lab-exercises/lab-2-the-display-of-oceanographic-data/lab-2-6/. Note that there is no direct link to Activity 2.6 from the student pages. Instructors may supply students with this URL or use select questions from the collection.
Extensions of these activities
Upper-level classes may want to add on to this lab by making their own graphs from the raw data. Instructors can provide raw data from one of the data explorations (below each exploration you may “download data” to provide it to students) and have the students plot the data in Excel or another software tool.
Upper-level research classes may want to explore a research question on their own and download data direct from the Ocean Observatories Initiative via Python. The Data Nuggets collection are a good starting point, as well as examples in the Data Lab Blog.
Other videos that might be useful in teaching the scientific method and sampling in oceanography can be found at Tools of Science YouTube channel.
A recommended reading for instructors that examines the differences between expert (you) and novice (your student) interpretations of data visualizations:
- Kastens, K. A., Shipley, T. F., Boone, A. P., & Straccia, F. (2016). What Geoscience Experts And Novices Look At, And What They See, When Viewing Data Visualizations. Journal of Astronomy & Earth Sciences Education (JAESE), 3(1), 27-58. https://doi.org/10.19030/jaese.v3i1.9689