Define your workflow

A good first step in deciding how to structure a project is to ask yourself:

• What are the different project phases?

• What are the major activities in each phase?

An example of phases and activities

For example, a project might involve the following phases:

1. Clean an existing data set;

2. Build models with different hypotheses or features;

3. Fit each model to the data; and

4. Decide which model best explains the data.

The data-cleaning phase might involve the following activities:

• Obtain the raw data;

• Identify the quality checks that should be applied;

• Decide how to resolve data that fail each quality check; and

• Generate and record the cleaned data.

The model-building phase might involve the following activities:

• Perform a literature search to identify relevant modelling studies;

• Identify competing hypotheses or features that might explain the data;

• Design a model that implements each hypothesis; and

• Define the relationship between each model and the cleaned data.

Reflect this workflow in your project structure

You can use the phases and activities to guide your choice of directory structure. For this example project, one possible structure is:

• project/: the root directory of your project

  • input/: a sub-directory that contains input data;

    • raw/: the raw data before cleaning;

    • cleaned/: the cleaned data;

  • code/: a sub-directory that contains the project code;

    • cleaning/: the data cleaning code;

    • model-first-hypothesis/: the first model;

    • model-second-hypothesis/: the second model;

    • fitting/: the code that fits each model to the data;

    • evaluation/: the code the compares the model fits;

    • plotting/: the code that plots output figures;

  • paper/: a sub-directory for the project manuscript;

    • figures/: the output figures;