A Special Issue on Data Standards is a research paper published in OMICS: A Journal of Integrative Biology (2006). On theSindex it has a DataRank of 2.9. It has been cited 56 times, with 36 citing works in its 1-hop citation network.
This special issue arose as a response to the ongoing proliferation of grass roots, communitydriven international data standardization activities. It is our hope that giving a range of participants in such activities the opportunity to contribute up-to-date descriptions of their efforts will help foster dialogue, raise awareness, and make a call for action on behalf of this rapidly growing community. This issue is not an exhaustive review of activities, but provides a snapshot of a range of activities at different stages of maturity and their growing interactions. It is organized into four groups of papers on data standardization activites in the fields of genomics, the postgenomic technologies of transcriptomics, proteomics and metabolomics and integrative activites, and other initiatives. Each invited piece contains details of the current status, future prospects, and successes and challenges of these efforts, making this issue a resource for those wishing to track, participate, or conform to any of these standardization activities, as well as those wishing to initiate new activities. In this foreword, we provide a brief background to the practice and methodology being adopted in the development of OMICS standards, review the content of this special issue, and attempt to highlight the growing interactions and synergies between groups.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.606
From this paper's citation signal
Citation Network Contribution
2.3
From 32 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 21% comes from its base citations and 79% from the citation network (32 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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