ArticleGigaScience2022
Making Common Fund data more findable: catalyzing a data ecosystem.
Article in GigaScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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.
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.
Who cites it
17 citing papers in PubMed.
- Training Perspectives from the NIH T32 Artificial Intelligence for Precision Nutrition Programs.The Journal of nutrition · 2026Article
- The Common Fund Data Ecosystem (CFDE).bioRxiv : the preprint server for biology · 2026Article
- Aggregation of gene regulatory information and knowledge on FAIR principles enables discovery of pathogenic gene regulatory variants.Bioinformatics (Oxford, England) · 2026Article
- SEA CDM: Study-Experiment-Assay Common Data Model and Databases for Cross-Domain Data Integration and Analysis.Scientific data · 2026Article
- Making genomic data FAIR through effective Data Portals.Scientific data · 2025Article
- Creating an Interactive Web Interface for Networks Stored in Knowledge Graph Databases.Current protocols · 2025Article
- Balancing ethical data sharing and open science for reproducible research in biomedical data science.Cell reports. Medicine · 2025Article
- Playbook workflow builder: Interactive construction of bioinformatics workflows.PLoS computational biology · 2025Article
- NCI Cancer Research Data Commons: Core Standards and Services.Cancer research · 2024Article
- NCI Cancer Research Data Commons: Lessons Learned and Future State.Cancer research · 2024Review
- The DO-KB Knowledgebase: a 20-year journey developing the disease open science ecosystem.Nucleic acids research · 2024Article
- Navigating bottlenecks and trade-offs in genomic data analysis.Nature reviews. Genetics · 2023Review
- Ten lessons for data sharing with a data commons.Scientific data · 2023Article
- Maximizing the utility of public data.Frontiers in genetics · 2023Article
- Making Common Fund data more findable: catalyzing a data ecosystem.GigaScience · 2022Article
- Getting Started with LINCS Datasets and Tools.Current protocols · 2022Article
- Gene and drug landing page aggregator.Bioinformatics advances · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
42 authors.
Funding
Abstract
The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables researchers to discover datasets from across the US National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. This system is centered on a catalog that integrates detailed descriptions of biomedical datasets from individual Common Fund Programs' Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by individual DCCs and can readily describe nearly all forms of biomedical research data. We detail its use to ingest and index data from 11 DCCs.
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What OpenQuestion holds
Registered trials
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.