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The CEDAR Workbench: An Ontology-Assisted Environment for Authoring Metadata that Describe Scientific Experiments.

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TLDR
The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored as discussed by the authors, and the CEDAR Workbench is a suite of Web-based tools and REST APIs that allows users to construct metadata templates, fill in templates to generate high-quality metadata, and to share and manage these resources.
Abstract
The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored. The software we have developed—the CEDAR Workbench—is a suite of Web-based tools and REST APIs that allows users to construct metadata templates, to fill in templates to generate high-quality metadata, and to share and manage these resources. The CEDAR Workbench provides a versatile, REST-based environment for authoring metadata that are enriched with terms from ontologies. The metadata are available as JSON, JSON-LD, or RDF for easy integration in scientific applications and reusability on the Web. Users can leverage our APIs for validating and submitting metadata to external repositories. The CEDAR Workbench is freely available and open-source.

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TL;DR: A group of international scientists give a detailed description of FoodOn, a-consortium-driven project to build a comprehensive food ontology that covers vocabulary from farm to fork, and addresses current gaps in food terminology and focuses on human and domesticated animal food description.
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The variable quality of metadata about biological samples used in biomedical experiments.

TL;DR: Overall, the metadata the authors analyzed reveal that there is a lack of principled mechanisms to enforce and validate metadata requirements, and significant aberrancies that are likely to impede search and secondary use of the associated datasets.
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COPO: a metadata platform for brokering FAIR data in the life sciences

TL;DR: COPO is a computational system that attempts to address some of these challenges by enabling scientists to describe their research objects using community-sanctioned metadata sets and vocabularies, and then use public or institutional repositories to share them with the wider scientific community.
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Re-curation and rational enrichment of knowledge graphs in Biological Expression Language

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The variable quality of metadata about biological samples used in biomedical experiments

TL;DR: In this paper, the authors present an analytical study of the quality of metadata about samples used in biomedical experiments and reveal that there is a lack of principled mechanisms to enforce and validate metadata requirements.
References
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TL;DR: The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data and provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-power gene expression and genomic hybridization experiments.
Journal ArticleDOI

The FAIR Guiding Principles for scientific data management and stewardship

TL;DR: The FAIR Data Principles as mentioned in this paper are a set of data reuse principles that focus on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals.
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From core referencing to data re-use: two French national initiatives to reinforce paleodata stewardship (National Cyber Core Repository and LTER France Retro-Observatory)

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BioPortal: ontologies and integrated data resources at the click of a mouse

TL;DR: BioPortal not only provides investigators, clinicians, and developers ‘one-stop shopping’ to programmatically access biomedical ontologies, but also provides support to integrate data from a variety of biomedical resources.
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