Find your issue, and check it is measured
Nothing, or a vague sense of what interests you. That is the normal starting position and it is fine.
- An environmental issue you can state in a sentence
- Proof that somebody measures it: one file, opened, not a page saying it exists
- A rough sketch of the system involved
- A note of who publishes those numbers, and where they live
You are not choosing your dataset here. You are finding out whether anybody has one.
This step ends with a file open: a check, not a commitment. Step 4 is where a file becomes the dataset you can defend.
You cannot leave this step without all three
Something that is happening, to something, because of something. Shark control is a topic. White sharks, a protected species, caught on the nets and drumlines Queensland sets off its beaches for swimmers' safety, is an issue.
Numbers you can change in a spreadsheet, covering the years and the places your issue is about. Not a page saying the data exists. The file. You are not choosing your final dataset yet, and you may open three before one survives: that work is step 4.
What enters, what leaves, what accumulates, what loops back.
Everything below is how we suggest you actually do it.
Choose the issue and the data at the same time
Choose a place and a file, and neither one without the other. Doing one after the other is what costs students two weeks.
Most environmental issues are not measured with the depth you need, near the place you care about, for long enough to see anything.
So work at both ends at once. Have an issue you can state in a sentence, and before you settle on it have a file open that describes it. If you cannot find one of them, change the other instead of pushing on.
I want to investigate microplastics in the Rhône. Several hours later: a handful of one-off studies, a news article, and no series anyone can download.
The issue was fine. Nothing measures it in a form you can use.
I want to investigate what the nets and drumlines of Queensland's Shark Control Program do to white sharks, a protected species. The Queensland Government publishes every animal the programme's gear has caught since 1996, beach by beach and month by month, as one spreadsheet.
The issue matched data that already exists.
This is not letting a dataset decide what you care about: the catalogue is organised by issue, so choosing a file is still choosing an issue. Just do not commit to a question before you know someone has measured it.
Twenty-two real arguments to start from
Each one is happening now, and somebody is doing something about it. Open one to see what you could put in a spreadsheet. None of this proves the data exists: the gallery is where you check that.
The three lines
Every investigation in this guide has the same shape, and it runs one way: from what people do to what happens to nature, with somebody's plan acting on one of them.
Your independent variable is a column of what people do.
Your dependent variable is a column about a population, an ecosystem, a water body or the soil. One individual can do, named as a limitation.
A real plan changes what people do, protects what happens to nature, or is what people do. At the IB minimum it may act elsewhere, if its connection to the question is stated.
Humans are part of the environment, so an investigation involving people is not off-syllabus. What Criterion A (Research question and inquiry) asks is that you identify an environmental issue and its impact on natural systems. The three lines are the shape I suggest for meeting that: something people do, and what it does to a population, an ecosystem, a water body or the soil.
The IB's own example of what does not work is the correlation between GDP and electricity usage: two columns of what people do, and nothing on line 2.
A column goes on the line of what it measures, never on the line of who caused it. Temperature is nature, even where people warmed it. A pollutant in a river is line 1, because it is what people put there; what it does to the river's insects or fish is line 2.
Line 3 is step 3's job, but have it in mind from the start: a real-world strategy somebody has made for this place.
GDP per capita against electricity use per person, for sixty countries.
A real relationship, and nothing on line 2: none of it is what happens to nature.
The invertebrate index in Geneva's rivers, against the ammonium in them.
Ammonium is what people put in the water. The insects are what happens to nature.
The fix is usually small. Keep the human driver you were interested in as line 1, and find a column about nature for line 2. Then check the direction: nature acting on people, such as floods reaching houses or wolves taking sheep, runs the wrong way. You can lay yours out on the three lines and see where it stands.
Does anyone measure this?
Three questions, and they take about ten minutes between them. They are the reasons investigations on this route fail, and all three can be answered before you have committed to anything.
You want stations and they publish national totals. You want months and they publish decades. In a national annual figure, the variation you wanted to analyse has already been averaged away.
A strategy introduced in 2015 needs data before and after 2015. A series that begins in 2018 cannot tell you what it changed, however good it is.
Plenty of things are measured well somewhere else. If the monitoring stops at a border and your issue does not, that is a limitation you will be writing about for the rest of the report.
If all three answers are yes, you have an investigation. If one is no, it is usually easier to move the question a little than to find different data: the same file will often answer a neighbouring question perfectly well.
The mark scheme says data may be primary or secondary, the criteria are identical, and this route reaches the same top band.
What it is not is a literature review. If you summarise what other people concluded, rather than working something out from their numbers, the method criterion is capped at the bottom band.
You can go bigger, and it costs something
The real advantage of this route is scale. One download can hold fifty years, or fifteen cities, or every country in the world. Questions that would take a research group a decade to measure are open to you today.
The cost arrives at step 3. A strategy always belongs to somebody and operates somewhere. The bigger your question gets, the harder it is to find one that acts on all of it. Ask about deforestation across five countries, and the honest answer to "whose plan is this?" is that there are five of them, or none.
Match the scale of your question to the scale a strategy operates at: national law, a river-basin agreement, a cantonal programme, a city policy. Stay inside one rather than spreading across several.
| A question at this scale | Wants a strategy of this kind |
|---|---|
| One catchment, one canton | A municipal or cantonal programme |
| A river that crosses a border | A treaty or a basin-wide agreement |
| One country over decades | National legislation |
| Every country in the file | A treaty, and only if it names what it controls |
Smaller is usually the better choice. A question about one canton has a named plan, a named authority and people who have publicly disagreed about it, which is three of the four things Criterion B (Strategy) is asking for.
A global question is fine when the global strategy is specific. Most are not. When every country sets its own target, you cannot show that the agreement changed any particular country's numbers. A question built on one ends in a paragraph of uncertain claims.
The test is whether the strategy decides the thing your column records. An agreement that names a substance and gives each country a date passes it. Ask it of whichever agreement you were about to reach for.
The study on this route passes it at a much smaller scale. Queensland's Shark Control Program chooses which gear goes in the water, nets or drumlines, and the gear is a column in its own file. That is why the study can set one gear against the other and name whose decision it is comparing.
Sketch the system
The job is to show that your variable sits inside something larger, with things entering, leaving, accumulating and looping back.
You did not collect your numbers yourself, so how you got them shows nothing about whether you understand what they describe. A systems diagram is the quickest proof, and diagrams sit outside the word count.
White sharks pass along the Queensland coast in winter and spring: most of those caught were caught from June to October. Off about 85 beaches the programme sets nets and drumlines (baited hooks on buoys). A shark that meets the gear is caught, and the file records whether it was alive when the gear was checked, and whether it was released, died or was killed. The same gear catches other sharks all year round, and turtles and marine mammals as well.
Drawn as a labelled flow, with the sharks moving along the coast on one side and the beaches on the other, that is one figure and no words at all. It also makes the strategy clear. The programme acts on one arrow only, the gear: which kind, and where it is set. It cannot choose which animals swim past, only what is in the water when they do.
Draw the path your measured quantity takes to get to the place it is measured, and mark where your strategy acts on it. On this route that path is the thing you did not see for yourself, and putting it in a diagram is what turns a downloaded column into an environmental system.
The diagram above has a filter built into it: the file counts only the sharks that met the gear. How many were caught depends on how much gear was in the water, and for how long, as well as on how many sharks swam past. So a column of catches can fall while the sharks do not, and rise while they decline.
Whenever your indicator sits upstream of the harm rather than measuring it, say so in your background and again in your conclusion. It is the difference between "how many white sharks there are" and "how many white sharks were caught", and only the second one is in the file.
Background, and the document nobody reads
The rule: every paragraph is there because your question needs it, and a general essay about the subject followed by an unrelated question costs marks on both strands at once.
One source almost nobody cites, and should: your dataset's methodology page or codebook, which says how the numbers were produced, by whom and with what definitions. Reading it is where most of your eventual evaluation comes from.
The file's title on the dataset page is the first warning: "Number caught by area, calendar year and species group". It is a table of counts, not a list of animals. A row is one kind of animal, on one gear, at one beach, in one month, with how many were caught, and 591 of the 4,299 rows in the study record more than one. So you add up the NumberCaught column. Counting rows undercounts.
The same page lists the files published beside this one, among them the programme's equipment locations and biological information from caught animals, and gives the licence and the credit line to cite. None of that is in the spreadsheet, and it matters later. The catch file cannot say how much gear was in the water, and those two neighbouring files are where the evaluation's improvements come from.
Read your dataset's documentation before you write your background, and cite it. It is the one source that is definitely about your data rather than about your topic, and the questions it answers are the ones step 7 will ask you.
It can help you understand the basics of an unfamiliar issue and suggest what a dataset of the kind you want is usually called. Often, that name is all you need to find it.
It cannot tell you that a dataset exists. It names plausible repositories with complete confidence. Only mention a dataset you have opened yourself.
Ready for step 2?
Secondary data checklist0 of 15The one about having opened the data, rather than found a page saying it exists, decides whether the next seven steps are possible at all. The three about a natural system are what stop a pair of downloaded columns from being a social science investigation.
Step 2 turns your issue into something your file can answer. On this route the sentence has to name the indicator and its units, because those are things you chose from a list rather than things you decided to go and measure.
The white shark investigation used on the secondary-data route of this guide is the author’s own analysis of a published dataset: the Queensland Shark Control Program’s record of every animal caught on its nets and drumlines, published by the Queensland Government under CC BY 4.0 and downloaded on 26 September 2026. The choice of the four areas, the analysis and the conclusions are the author’s, not the Queensland Government’s.