lc-intro-data-curation
Science Score: 44.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (7.6%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: LibraryCarpentry
- License: other
- Default Branch: main
- Homepage: https://librarycarpentry.github.io/lc-intro-data-curation/
- Size: 9.28 MB
Statistics
- Stars: 0
- Watchers: 5
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Introduction to Curating for Reproducibility
This lesson introduces key concepts in reproducibility and data curation, laying the groundwork for understanding and managing research compendia. It is designed for research data support professionals and library and information science practitioners who are new to the ideas behind curating reproducible research.
Rendered Lesson:
View the rendered lesson at: https://ucla-data-science-center.github.io/lc-data-curation-foundations
Contributing
Please see the CONTRIBUTING.md file for details on how to contribute to this lesson. We welcome improvements, additional examples, and updates.
Maintainer(s)
The current maintainers of this lesson are:
- Thu-Mai Lewis Christian
- Florio Arguillas
- Limor Peer
Acknowledgements
We gratefully acknowledge the input and suggestions from our broader community and the inspiration provided by The Carpentries lesson templates.
{alt='IMLS'}
The CuRe Curriculum was made possible in part by the Institute of Museum and Library Services under grants RE-87-17-0074-17 and RE-36-19-0081-19. The Institute of Museum and Library Services is the primary source of federal support for the nation's libraries and museums. We advance, support, and empower America's museums, libraries, and related organizations through grantmaking, research, and policy development. Our vision is a nation where museums and libraries work together to transform the lives of individuals and communities. To learn more, visit www.imls.gov and follow us on Facebook and Twitter.
Citation
For citation information, please see the CITATION.cff file.
License
This lesson is published under a CC BY 4.0 license.
Contact
If you have any questions or feedback about this lesson, please get in touch with the maintainers at contact\@example.com.
Owner
- Name: Library Carpentry
- Login: LibraryCarpentry
- Kind: organization
- Email: team@carpentries.org
- Website: http://librarycarpentry.org/
- Repositories: 38
- Profile: https://github.com/LibraryCarpentry
Software and data skills for people working in library- and information-related roles
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: Introduction to Curating for Reproducibility
message: >-
If you use this dataset, please cite it using the metadata
from this file.
type: dataset
authors:
- given-names: Thu-Mai
family-names: Lewis Christian
orcid: 'https://orcid.org/0000-0002-3658-9692'
affiliation: University of North Carolina at Chapel Hill
- orcid: 'https://orcid.org/0000-0002-2000-3722'
given-names: Florio
family-names: Arguillas
affiliation: Cornell University
- orcid: 'https://orcid.org/0000-0002-3234-1593'
given-names: Limor
family-names: Peer
affiliation: Yale University
repository-code: 'https://github.com/LibraryCarpentry/lc-intro-data-curation'
url: 'https://librarycarpentry.github.io/lc-intro-data-curation/'
abstract: >-
This lesson introduces the principles of data curation for
reproducibility, providing foundational knowledge and
strategies for managing research data assets. Learners
gain essential skills to support reproducible research
through effective curation workflows.
keywords:
- reproducibility
- data curation
- research data
- data quality
- library carpentry
license: CC-BY-4.0
version: v2025-03-15
date-released: '2025-03-15'
GitHub Events
Total
- Issues event: 3
- Issue comment event: 2
- Member event: 2
- Push event: 44
- Pull request event: 4
- Create event: 7
Last Year
- Issues event: 3
- Issue comment event: 2
- Member event: 2
- Push event: 44
- Pull request event: 4
- Create event: 7
Dependencies
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