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  • Creator/Author: <Researcher name/ORCiD>

  • Subject/title: <Name of the data>

  • Description: <Short paragraph describing the data and how they got to this state e.g., image taken, data processed, etc.>

  • Contributor(s)/Collaborator(s): <Names of people associated with the project>

  • Date: <use a format that is standardized across all the data e.g., YYYYMMDD>

  • Original Format/File types: <.txt .csv .png .sql>

  • Relation: <list any relating files/folders>

  • Location: <e.g., Latitude & Longitude in decimal degrees>

  • Rights: <funder grant number, or open source>

Straight Code - No context

Code Block
Limit to 16 lines in the example. 














This is the end

Same Thing With Images

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Two Column Tables are nice ways to separate content/ Background info along with an image example on the same “Slide”. Please notice the table width. This should stop scroll bars from appearing

  • Bullets are nice to include for distinct points

  • yep

  • they

  • sure

  • are

    This is 14 lines

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image-20240514-000033.pngImage Removed

Alternatively No Table

image-20240514-000127.pngImage Removed

Finally The End

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Link to Previous sub-module or Home Module

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Metadata File Types / README

Metadata can be recorded in multiple ways including in a filename, in a spreadsheet, in an XML file, or into a database. However, a very common type is a simple text file called a README file. A README provides information about a data file and is intended to help ensure that the data can be correctly interpreted, by yourself at a later date or by others when sharing or publishing data. In general a good README should include several things in addition to what is listed above:

General Items

Optional Items

Other Recommendations

  • File naming system (with examples)

  • Folder structure

  • Relationships and dependencies between files

  • Other documentation files of interest within dataset (notes, companion files)

  • For each major file, short description of contents

  • Date of creation of each major file

  • Experimental & environmental conditions of collection (if appropriate)

  • Standards and calibration for data collection (if applicable)

  • Uncertainty, precision and accuracy of measurements (if appropriate)

  • Methods used for data processing

  • Software used in data collection and processing, including version numbers

  • File formats used in the dataset & recommended software

  • Quality control procedure applied

  • Description of file versioning system if appropriate

  • Dataset changelog

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README Example

Luckily for UWYO researchers the University Data Librarians provide an extensive sample README that can be downloaded directly from their website. Below is an example of what the beginning of the file looks like:

Code Block
This DATSETNAMEreadme.txt file was generated on YYYY-MM-DD by NAME
GENERAL INFORMATION
1. Title of Dataset: 
2. Description or abstract of dataset:
3. Author Information
	A. Principal Investigator Contact Information
		Name: 
		Institution: 
		Address: 
		Email: 
4. Date of data collection (single date, range, approximate date) <suggested format YYYY-MM-DD>: 
5. Geographic location of data collection <latitude, longiute, or city/region, State, Country, as appropriate>: 
6. Information about funding sources that supported the collection of the data: 
7. Keywords for dataset: 
8. Discipline of dataset:
9. License for dataset:

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How to Download the Libraries' README on ARCC HPC

ARCC recommends researchers to download the Libraries README file into the project directory for High Performance Computing (HPC) projects when they initially get the project setup. That way the file can be maintained throughout the process, so that when it comes to the publishing phase of the Research Data Life-cycle, the metadata is already recorded and can be shared quickly.

Here is an example of a Linux command to run to download the Libraries README file:

Code Block
#To Download 
wget https://uwyo.libguides.com/ld.php?content_id=61572044  

#To rename as README.txt
mv 'ld.php?content_id=61572044' README.txt

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Next Steps

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Research Data Management Life-cycle

Workshop Home

Intro to Data Management

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Data Value and Safety