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Research Data Management

Managing your data

Start early and follow a plan

One of the most important things you can do to manage your data is to plan how you're going to do it early on, before you start collecting data. These recommendations apply to a project at any stage, and can be implemented whenever, but we recommend planning ahead if possible.

Make a data management plan (DMP)

The first step of managing your data is to make a DMP that will cover how you will be collecting and storing your data (this is covered earlier in the guide). Most funders require a DMP with your grant submission and some of the sections will with other data management tasks.

Create a data dictionary

Unlike a DMP, a data dictionary is a record of each variable and data field that you are going to collect in your project. A data dictionary can be a text file or a spreadsheet, and it should contain variable names (both machine-readable and plain language), the format of the data (numeric, text, multiple choice answers), measurement type (kg or lb?),  why you are collecting this data, and how you are collecting this data.

DataONE Best Practices - Planning Data Management

Create a file naming convention

Before you start generating lots of files, create a file naming convention that you will use to name all of your files. This will stop confusion about what file is more recent or contains the data from which experiment, and makes it easiesr to analyze your data.

  • Avoid special characters in a file name
    So don't name a file WBS+-+Final.docx 
  • Use capitals or underscores instead of periods or spaces
    Example: SurveyResponseData.csv
  • Use documented & standardized descriptive information about the project/experiment
    Have a standard for your research group so things can easily be found and shared
  • Use 25 or fewer characters
  • Use date format ISO 8601: YYYY-MM-DD
    The year first format makes it easy to find newest/oldest files
  • Include a version number
    Example: dataMgmtNotesv5.txt, instead of dataMgmtNotesFinalAgainReally.txt

See Stanford University's File Naming Best Practices + Exemplar Handout

Setup your data storage system

One part of some DMPs is estimating how much data will be collected over the course of the project and how it will be stored. This is a good practice in any research project: try to estimate how much storage will be required, and how you will store data. Do you need a new external hard drive, or can all your data be stored on the cloud. Are there any privacy concerns with your data?

There are resources available to all Temple researchers, and ITS can also help with securely storing sensitive data.

Temple ITS Storage Comparison Chart

LabArchives and Lab notebooks

Temple now subscribes to LabArchives, an Electronic Lab Notebook (ELN). Find more information about LabArchives at the Office of the Vice President for Research. You can login here, just use your AccessNet credentials. More information about LabArchives will be coming later in 2023.
If you are running experiments in a lab, here are some best practices for lab notebooks.
In the Pages
  • Permanently bound book, pages numbered
  • In ink
  • Add things chronologically, date entries
  • Entries should be in first person with clear details of who did what
  • Abbreviations should be explained
  • Don’t remove pages or portions of pages
  • Put a line through blank space
Notebooks Themselves
  • Index completed notebooks & keep in a single location
  • Notebooks should be “checked out”
  • Originals stay with lab, copies go with researchers
  • Keep for at least 5 years after study is complete, longer under various conditions, i.e.: patents


Electronic Lab Notebooks (ELN)

  • Prior to adopting an ELN, check with your dean or department head
  • ELN Features Matrix from Harvard Medical School
  • Johns Hopkins University ELN template on the Open Science Framework



When storing data in spreadsheets, follow these best practices.

  • Top row should be headers with labels
    If labels aren't clear, include a ReadMe or a Data Dictionary
  • Each row under that is a single record
  • Each column is a single variable
  • Every column should be consistent
    All numbers, all dates, all text, all coded values for the same get the idea
  • Every column should also be consistent in format
    All dates recorded the same way, all numbers with the same decimal places, standard ways of entering text/names of things