Best Practices in Data Organisation Using Spreadsheets: Glossary

Key Points

Introduction

  • Good data organisation is the foundation of any research project.
Organising data in spreadsheets

  • Never modify your raw data. Always make a copy before making any changes.

  • Keep track of all of the steps you take to clean your data in a plain text file.

  • Organise your data according to tidy data principles.

  • Record metadata in a separate plain text file (such as README.txt) in your project root folder or folder with data.
Common spreadsheet errors

  • Include only one piece of information in a cell.

  • Avoid using multiple tables or spreading data about multiple tabs within one spreadsheet.

  • Record zeros as zeros.

  • Avoid spaces, numbers and special characters in column headers.

  • Avoid special characters in your data.

  • Use an appropriate null value to record missing data.

  • Record units in column headers.

  • Place comments in a separate column.

  • Do not use formatting to convey information.
Dates as data

  • Use extreme caution when working with date data.

  • Splitting dates into their component values can make them easier to handle.
Quality assurance and control

  • Always copy your original spreadsheet file and work with a copy so you do not affect the raw data.

  • Use data validation to prevent accidentally entering invalid data.
Exporting data

  • Data stored in common spreadsheet formats will often not be read correctly into data analysis software, introducing errors into your data.

  • Exporting data from spreadsheets to formats like CSV or TSV puts it in a format that can be used consistently by most programs.
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Glossary

cleaned data
data that has been manipulated post-collection to remove errors or inaccuracies, introduce desired formatting changes, or otherwise prepare the data for analysis
conditional formatting
formatting that is applied to a specific cell or range of cells depending on a set of criteria
CSV (comma separated values) format
a plain text file format in which values are separated by commas
factor
a variable that takes on a limited number of possible values (i.e. categorical data)
metadata
data which describes other data
null value
a value used to record observations missing from a dataset
observation
a single measurement or record of the object being recorded (e.g. the weight of a particular mouse)
plain text
unformatted text
quality assurance
any process which checks data for validity during entry
quality control
any process which removes problematic data from a dataset
raw data
data that has not been manipulated and represents actual recorded values
rich text
formatted text (e.g. text that appears bolded, colored or italicized)
string
a collection of characters (e.g. “thisisastring”)
TSV (tab separated values) format
a plain text file format in which values are separated by tabs
variable
a category of data being collected on the object being recorded (e.g. a mouse’s weight)