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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 early in the research process, before you start collecting data. The following recommendations apply to a project at any stage 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. 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.

Useful resources:

Data Types and File Formats

What kind of data is going to be recorded in your study?

There are lots of possible kinds of data, any recorded observation can be considered data, whether it’s produced by a finely-tuned sensor or on pen and paper. Some examples are: tabular, experimental, microscope images, and physical samples. Give some context for where the data is coming from and how you are recording it.

What file types will your data be stored in?

Open file type formats are better than propietary types, because more programs can open and edit them. For instance, for storing tabular or spreadsheet data, .csv files are preferred over .xslx files (from Excel), because .csv files can be opened by non-Microsoft text editors and spreadsheet programs.

The FAIR Principles for data management and stewardship offer guidelines for optimizing your data with open formats to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. 

The links below lead to DataONE, which has some best practices and information on file format

Preferred File Formats

  • TAR
  • GZIP
  • ZIP
  • XML
  • CSV
  • SHP
  • DBF
  • GeoTIFF
  • NetCDF
  • MOV
  • MPEG
  • AVI
  • MXF
  • WAV
  • AIFF
  • MP3
  • MXF
  • JCAMP
  • CSV
  • ASCII
  • DTA
  • POR
  • SAS
  • SAV
  • TIFF
  • JPEG
  • PDF
  • PNG
  • GIF
  • BMP
  • RTF
  • ODT
  • XML
  • HTML
  • ASCII
  • UTF-8

Spreadsheet - Best Practices

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 thing...you 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

File Naming Conventions - Best Practices

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

For additional information and guidance see:

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?

If you have additional questions about storage platforms available through Trinity or how to store your data correctly and safely, contact the helpdesk@trincoll.edu or security@trincoll.edu.