Demo corpus. Scores are computed on a select set of biomedical paper/datasets and may be inaccurate for papers outside this corpus — DataRank relies on network effects that improve with scale. We aim to expand this into a fully open resource pending additional funding.

FAIRCDR: An Elixir Implementation Study to examine the FAIRness of the ELIXIR Core Data Resources

Faculty of 1000 Research Ltd(2019)10.7490/f1000research.1117014.1Source: DataRank Database

FAIRCDR: An Elixir Implementation Study to examine the FAIRness of the ELIXIR Core Data Resources is a research paper published in Faculty of 1000 Research Ltd (2019). On theSindex it has a DataRank of 0.

N/A

0DataRank · unranked

Open Access0 citations · base score 0

Cite:

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

Presentation of the ELIXIR Implementation study FAIRness of the current ELIXIR Core resources at the ELIXIR All Hands meeting 2019 in Lisbon, Portugal.

›Data sources & pipeline

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Pending

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

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Authors (1)

Michel J. DumontierORCID