Library Guides: Data Management Plan (DMP) Guide: 1. Data identification

Step 1. Identify your research data

The first step of data management is an easy one: make a data inventory. Your data inventory should cover:

What the data describes and what type it is.
How the data is collected, generated, etc.
How much of it there will be (i.e. volume estimates).
How it will be saved (file formats)
What software will be used (file types).

Creating a complete inventory is an important first step as your answers define the kind of care and facilities will be needed. This section can be completed as a narrative or table.

Writing prompts

What type of data is it?

Examples: Spatial, temporal, observational, experimental, survey responses, genomic sequences, interview transcriptions, etc.

How will the data be collected?

Examples: recorded interviews, surveys, models, sensors, image analysis, DNA sequencing, word counts, camera traps, etc.

How will the data be saved and opened?

(i.e. file types and file formats)

Example file types: text, spreadsheets, databases, digital images, sound files, digital video, computer code, algorithms, etc.
Example file formats: PDF (portable document format), .csv (comma separated values), .docx (Microsoft Word), .txt (plain text), etc.

Tips

A good effort should be made to use open file formats over proprietary formats. Not only will it increase your data's shelf life, it will also make data preservation and sharing much easier.
A database is a tool to organize data but it can really complicate data reuse. If you plan to create a database you will need to consider how others will be able to access and export data from it.

For more information and examples see:

Define expected data outcomes and types (DataOne)

Step 1 Example: Jazz songs from the 1930's

Example data identification summary:

This project will create spreadsheets of word frequencies found in jazz songs from the 1930's. For each song a plain text document containing a transcript of the lyrics will be generated and stored as a .txt file. Word counts for each song analyzed will be recorded in spreadsheets, one for each song. Another spreadsheet will contain the details about each of the songs that were analyzed (such as year written, singer, producer, etc.). A final spreadsheet will combine the word counts from all of the songs analyzed. The spreadsheets will be saved as both Microsoft Excel and .csv files.

Notes:

.txt is a plain text (no formatting) file type for all types of text (including code and prose).
.csv is a plain text file used to store tabular (spreadsheet) data. Each column value is separated by a comma which is why it is called Comma Separated Values, or CSV.

decorative image
Need help?

Data Management Questions
datashare@iastate.edu

IT Questions
researchit@iastate.edu

Quick Access

DMPTool