2.1 Data inventory

Now that we’ve talked about types of data and why we should manage data, we’re ready to move on to our data management essentials! But first, we always suggest one of the best things you can do before starting a project is to brainstorm all the data types and forms you’ll be producing. One way you can do this is to conduct a data inventory of all the activities or instruments that will produce, collect, manipulate, or analyze data during your project.

Making a data inventory part of your planning stage can you help you improve the choices you make for organization, storage, and the other best practices we’ll cover here because you’ll have a better understanding of the scope of your data as well as any big changes that will happen to it during the project.

2.2 File naming and organization

Having a good file naming and organization method is one of the simplest things you can do to make a huge impact on your data management! However, it can also be one of the hardest things to change in your data management practices, because it’s often something we do by hand and changing our personal habits can be difficult.

Though it can be difficult to implement, a good file naming convention and folder organization method can make quick improvements to your research process. It makes your data easier to search through and it makes it easier to distinguish similar files or versions from one another. It also provides built-in description about the contents of the file and can make it easier to share documents with collaborators, as they’ll be able to find and understand the file.

File Naming Best Practices

One of the most important things for file naming is to develop a naming convention, or a template of standard information you’ll use in most file names, and to always use that convention anytime you have multiple related files in a folder. Without a set convention, you may end up recording haphazard information, or not capturing enough important information, each time you create a file. This will make it harder to remember what keywords you can use to search for the file.

There is not one recommended naming convention that will work for everyone. Each project and person are different, but below we’ve laid out some suggestions for creating a file naming convention.

How to create a file naming convention:

Example filename: Mendota_Buoy6_20180711_v2

The best naming convention for your files will vary from project to project, based on the type of research you’re doing, and what the most important pieces of information to capture about your data are. Working to implement a good naming convention will make a huge difference when searching for, working with, and collaborating on files.

2.3 Hierarchical organization or folder best practices

Another key component of an effective file management strategy is establishing a well-organized hierarchical folder structure to go along with your file naming conventions.

While there’s no easy answer as to how many folders you should have or how to best organize them, the trick is to create a structure that balances breadth versus depth.

Try to limit the number of top-level folders you create and try to limit the number of folders nested within those as well. You don’t want to create so many layers in your hierarchy that accessing the actual data files becomes difficult. However, you also don’t want to have too many files within each folder that may also make finding your data more difficult.

Below we provide some examples and further tips for creating an organized and useful folder structure.

Examples:

Best Practices:

• Apply your naming conventions to your folder names. Make sure each folder has a brief but descriptive name. Avoid folder names that are ambiguous or overlap with the names of other folders. In the examples above, the folder names are clear and indicate the category or subject of the files within.
• Group by similarity, function, or topic instead of by file type.
  • If you collect a lot of data in a certain file type, like images, you can end up with a folder with too many files in it. Notice that in the examples, none of the folders are specific file formats or types.
  • Example 1 instead uses a “WaterQuality” folder under a “Data” folder. With this structure, we can tell right away that everything within that folder is data we’ve collected and it relates to the water quality. The file name then provides further information about the location and date.
• Distinguish between past and active work. Create archive or yearly folders that you can put past work in. This can help clean up your folder structure quite quickly!
  • In example 2, you can see the use of a “past” folder which archives work from previous years. Using this type of structure means you’re narrowing your search scope and looking among a smaller set of folders to locate data.
  • In example 2, the folder structure archives past work by the year that work was done—you can choose to organize your “past” folder in whatever way is most effective for you.
• Create folders to keep your raw data separate from your processed data. This will prevent you overwriting your raw data and losing any important information.
  • This is illustrated in example 2, which has a “Data” folder. This is a great way to ensure that you always know where to look for your data files.

2.4 Lesson Review