Tutorial for using the netCDF Data Curation Primer

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

This document is a supplemental primer to the main IMLS-Data-CurationFormat Profile-netCDF primer (http://hdl.handle.net/2027.42/145724). Within this primer, the NCAR Global Climate Four-Dimensional Data Assimilation (CFDDA) Hourly 40 km Reanalysis dataset from the Research Data Archive (RDA) at the National Center for Atmospheric Research (NCAR) is used to demonstrate how to assess a netCDF-based dataset according to the main primer’s instructions. In particular, Panoply, a curation review tool that is recommended by the main primer, is used to examine the dataset in order to help answer the questions outlined in the “Key Questions for Curation Review” section of the main primer.
This work was created as part of the Data Curation Network “Specialized Data Curation” Workshop #1 co-located with the Digital Library Federation (DLF) Forum 2018 in Las Vegas, Nevada on October 17-18, 2018.

More information about the collection of Data Curation Primers can be found at:  http://hdl.handle.net/11299/202810.

Interactive primers available for download and derivatives at: https://github.com/DataCurationNetwork/data-primers.
 

Authoring Person(s) Name: 
Sophie Hou
Access Cost: 
No fee
Citation - format of the preferred citation for the learning resource: 
Hou, Sophie. (2019). Tutorial for using the netCDF Data Curation Primer. Data Curation Network. Retrieved from the University of Minnesota Digital Conservancy, http://hdl.handle.net/11299/202825.
Primary language(s) in which the learning resource was originally published or made available: 
English
More info about
Keywords - short phrases describing what the learning resource is about: 
Data access
Data archiving
Data curation
Data recipes for Earth science data
Data visualization
Geoscience data
How-to data recipes
Subject Discipline - subject domain(s) toward which the learning resource is targeted: 
Physical Sciences and Mathematics: Earth Sciences
Physical Sciences and Mathematics: Environmental Sciences
Published / Broadcast: 
Tuesday, April 9, 2019
ID - identifier that provides the means to locate the learning resource or its citation: 
http://hdl.handle.net/11299/202825
Type - namespace prefix for the citable locator, if any: 
Handle
Publisher - organization credited with publishing or broadcasting the learning resource: 
Data Curation Network
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Interactive Resource - requires a user to take action or make a request in order for the content to be understood, executed or experienced.
Contributor Organization(s): 
Name: 
Institute of Museum and Library Services (IMLS)
Type: 
Funding and sponsorship
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Instruction - detailed information about aspects or processes related to data management or data skills.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Learning Activity - guided or unguided activity engaged in by a learner to acquire skills, concepts, or knowledge that may or may not be defined by a lesson. Examples: data exercises, data recipes.
Target Audience - intended audience for which the learning resource was created: 
Citizen scientist
Data professional
Early-career research scientist
Educator
Graduate student
Librarian
Mid-career research scientist
Repository manager
Research faculty
Research scientist
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
Up to 1 hour