carmengg
commented
9 months ago Here is some information about how the Data Carpentries, NEON lectures, Earth Lab Lessons, and the Data Management Training Clearinghouse (DMTC) add metadata for archiving and organizing their modules.
Data Carpentries
Date Carpentries lessons are organized into episodes.
Each episode’s YAML header must contain: the episode’s title time estimates for teaching and exercises motivating questions lesson objectives a summary of key points
For example, this is the YAML for the Using RMarkdown episode:
---
source: Rmd
title: "Using RMarkdown"
teaching: 10
exercises: 2
questions:
- "How to write a lesson using RMarkdown?"
objectives:
- "Explain how to use RMarkdown with the new lesson template."
- "Demonstrate how to include pieces of code, figures, and challenges."
keypoints:
- "Edit the .Rmd files not the .md files"
- "Run `make serve` to knit documents and preview lesson website locally"
---NOTES:
I really like the teaching and exercises timing information. It could also serve to distinguish between modules where participants mostly work on exercises and modules where there’s more lecturing. However, I would change teaching and exercises to something like teaching-time and exercises-time to make it explicit it is the timing (at first I thought exercises: 2 meant there were 2 exercises).
NEON teaching modules
NEON teaching modules are part of the Quantitative Undergraduate Biology Education and Synthesis (QUBES) lesson repository. According to their website,
The QUBES platform hosts hundreds of teaching materials, reference materials, and cloud-based software free to use and adapt using open Creative Commons licenses.
In the filters tab in the QUBES lesson browser, there are three main tags associated with each lesson. These are the tags with the corresponding subtypes:
-
Resource Type:
- Teaching material
- Reference material
- Dataset
-
Audience level:
- High School
- Undergraduate
- Graduate
- Faculty
-
Activity length:
- Less than 1 hour
- 1 Hour
- More than 1 hour
- Extended Project
Other less used tag categories are:
- Software Used
- Inclusive Pedagogy for Life Science Education
- QUBES Universal Design Tagging Ontology
- Open Science and Education Practices Ontology.
The NEON teaching modules use the first three tags and call these “alignments”. Here's an example module. Most modules have further subcategories for each alignment. For example:
-
Audience Level
- Undergraduate
- Introductory
- Non-majors
- Majors
- Advanced
- Introductory
- Undergraduate
-
Resource Type
- Teaching material
- Homework
- Lecture
- Lab
- Online course
- Dataset
- Raw
- Cleaned
- Teaching material
The NEON teaching modules also include a citation with information about author, year of publication, title, version number and doi. Example:
Lesley Bulluck (2019). Testing hypotheses about the role of wildfire in structuring avian communities. NEON Faculty Mentoring Network, (Version 2.0). QUBES Educational Resources. doi:10.25334/R2S1-4S62
NOTES: I really liked the core three alignments: audience level, resource type and activity length. The activity length could complement the other time-tracking metadata about lecturing and exercises. I was surprised the “software used” tag wasn’t as used. This would be good to include for us too. Having software used = None for non-technical modules could also be an option.
Earth Lab Lessons
The Earth Lab only hosts resources developed by Earth Lab at University of Colorado, Boulder. The lessons are organized into the following topics:
LESSONS BY TOPIC:
- Remote sensing
- Earth science
- Social science
- Time series
- Data exploration and analysis
- Spatial data and gis
- Reproducible science and programming
- Find and manage data
- File formats
NOTES: Having a topic tag could be good and these are some possible values for it.
Data Management Training Clearinghouse (DMTC)
According to their website:
Data Management Training Clearinghouse (DMTC) is a registry for excellent online learning resources focusing on data skills and capacity building for research data management, data stewardship and data education.
Learning resources can be browsed using the following filters:
Filters
- Keywords
- Author Organization(s)
- Authoring Person(s) Names
- Original Languages
- Additional Languages
- Target Audiences
- Access Cost
- License
- Accessibility Features
- Subject Discipline
- Media Type
- Educational Purpose
- Educational Frameworks
- Publication Status
Additionally, these are the tags from the metadata Matt shared:
- title
- status
- pub_status
- modification_date
- resource_modification_date
- url
- access_cost
- submitter_name
- submitter_email
- authors
- author_names
- author_org
- contact
- abstract_data
- keywords
- license
- usage_info
- citation
- locator_data
- locator_type
- publisher
- version
- created
- published
- accessibility_features
- accessibility_summary
- language_primary
- languages_secondary
- ed_frameworks
- target_audience
- purpose
- completion_time
- media_type
- lr_type
- creator
- md_record_id
- ratings
- rating
- id
- contributors
- contributor_orgs
- score
- country_of_origin
- credential_status
- notes
NOTES: Many of the tags in the complete metadata are about submission to the module to DMTC, so these would be needed. Others, like access_cost, license, language_primary, and language_secondary, will probably be the same for all the modules we develop, so we could keep these out for now. Keywords, target_audiece, completion_time, and title are some we could add right away. Once the module becomes stable we could include url, citation and authors.
mbjones
We will want to distribute our lessons widely, and it will be helpful to have structured metadata for the lessons to be used in search and discovery. The ESIP Data Management Training Clearinghouse has an established metadata vocabulary for courses, and would make a good starting point for our work -- see below for an example of that metadata. But we also should evaluate metadata vocabularies used in other related initiatives, including the Carpentries (see their example format for lessons), the NEON modules, and EarthLab courses.
Here's an example metadata record from the DMTC for a DataONE lesson on metadata:
Each lesson in the DMTC has an identifier, and with that , you can downloaded the lesson metadata from the DMTC API (see DMTC API documentation) using the following command: