Evidence map›Paper›PMID 40627613›Full record

ArticlePLoS computational biology2025

Ten quick tips for navigating intellectual property in FAIR educational resources.

Eva Maria Funk, Ulf Toelch, Rebecca Ludwig, Silke Kniffert

Abstract read
In one paragraph

Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Eva Maria FunkBerlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, QUEST Center for Responsible Research, Berlin, Germany.ORCID 0000-0003-3376-259X
Ulf ToelchBerlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, QUEST Center for Responsible Research, Berlin, Germany.
Rebecca LudwigEATRIS European infrastructure for translational medicine, Amsterdam, The Netherlands.
Silke KniffertBerlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, QUEST Center for Responsible Research, Berlin, Germany.ORCID 0000-0001-5084-3960

Funding

Einstein FoundationStiftung Innovation in der Hochschullehre
6 · The paper itself

Abstract

Open Educational Resources (OER) offer a transformative approach to education by providing freely accessible learning materials. However, creating OER that meet the FAIR principles-findable, accessible, interoperable, and reusable-while navigating the complexities of copyright law presents unique challenges. This paper serves as a practical guide for educators and institutions wishing to develop and share FAIR-compliant OER while respecting intellectual property rights. It presents 10 quick tips that guide the process of developing legally secure FAIR OER from planning to creation to publication, including considerations for AI-generated materials. These quick tips cover critical aspects such as understanding licensing options, cataloguing resources to ensure comprehensive attribution, and effectively managing copyright concerns. By following these guidelines, educators can improve the discoverability and reusability of their materials, streamline the creation process, and contribute to a more open and collaborative educational landscape. This comprehensive approach not only supports the widespread dissemination of knowledge but also empowers educators to innovate and share resources effectively, fostering a global community of open science and education practice, while adhering legal regulations.

Indexed as

Intellectual PropertyCopyrightHumans

Identifiers

PMID40627613
PMCPMC12237045

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.