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Dorothea Strecker

@dorothearrr@fediscience.org
mastodon 4.6.9
  • Open on fediscience.org

researcher and PhD student at Berlin School of Library and Information Science, Humboldt-Universität zu Berlin
research group Information Management
member of ScholCommLab, re3data Working Group, DataCite Metadata Working Group

data studies, infrastructure studies, rstats

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6 Posts
Joined November 08, 2022
ORCiD:
https://orcid.org/0000-0002-9754-3807
Open post
Dorothea Strecker @dorothearrr@fediscience.org
· 2mo ago
Replying to
@ztirfhtor@openbiblio.social Congratulations, Dr. Rothfritz! 🎓
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Open post
Dorothea Strecker @dorothearrr@fediscience.org
· 6mo ago

In this preprint, I investigate the simultaneous use of multiple metadata schemas at research data repositories. The analysis covers how eight disciplinary research data repositories from the geosciences and social sciences use disciplinary metadata schemas and the @datacite@openbiblio.social Metadata Schema, and how two metadata records describing the same dataset compare.

:arxiv: https://doi.org/10.48550/arXiv.2603.25468

#openScience
#researchData

doi.org
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Open post
Dorothea Strecker @dorothearrr@fediscience.org
· 6mo ago
Replying to
@dkz2r @thecarpentries Right this moment, I'm working on my dissertation using the template from this course. I had previous experience with LaTeX, but still found the course very helpful. Thank you for creating these materials!
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Open post
Dorothea Strecker @dorothearrr@fediscience.org
· 14mo ago

This @QSS_ISSI@scicomm.xyz paper analyzes the scope, structure, curation, mappings and use of 45 knowledge organization systems (KOS) for academic fields:

https://doi.org/10.1162/qss_a_00363

It provides a useful overview of KOS and identifies gaps: The findings show that there is a lack of field-specific KOS in certain areas, and that "there is currently no existing multifield KOS that simultaneously is comprehensive in topic coverage, granular, consistently updated, and openly accessible."

doi.org
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Open post
Dorothea Strecker @dorothearrr@fediscience.org
· 32mo ago

This preprint observes a citation advantage of papers reusing more than one dataset, based on publications reusing ICPSR datasets:
http://arxiv.org/abs/2402.05024

"Papers that used more than one dataset garnered 22%, 15%, and 15% more citations over 3, 5, and 10 years relative to papers that used a single dataset." The effect is higher for datasets that are rarely used in combination.

#researchdata #datareuse

arxiv.org
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Open post
Dorothea Strecker @dorothearrr@fediscience.org
· 32mo ago
Replying to
@vtraag @tklebel I found your sessions on causal inference at the CWTS Summer School very insightful. Thank you for this accessible introduction to the topic!
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