ReviewCancer journal (Sudbury, Mass.)
Progress Toward Cancer Data Ecosystems.
Review in Cancer journal (Sudbury, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Data Science and Precision Oncology Nursing: Creating an Analytic Ecosystem to Support Personalized Supportive Care across the Trajectory of Illness.Seminars in oncology nursing · 2023Article
- Towards self-describing and FAIR bulk formats for biomedical data.PLoS computational biology · 2023Article
- PLCOjs, a FAIR GWAS web SDK for the NCI Prostate, Lung, Colorectal and Ovarian Cancer Genetic Atlas project.Bioinformatics (Oxford, England) · 2022Article
- From biomedical cloud platforms to microservices: next steps in FAIR data and analysis.Scientific data · 2022Article
- The National Cancer Institute's Role in Advancing Health-Care Delivery Research.Journal of the National Cancer Institute · 2022Article
- The NCI Genomic Data Commons.Nature genetics · 2021Article
- Blockchain for genomics and healthcare: a literature review, current status, classification and open issues.PeerJ · 2021Article
- Insights from Adopting a Data Commons Approach for Large-scale Observational Cohort Studies: The California Teachers Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Using big data in pediatric oncology: Current applications and future directions.Seminars in oncology · 2020Review
- Data Lakes, Clouds, and Commons: A Review of Platforms for Analyzing and Sharing Genomic Data.Trends in genetics : TIG · 2019Review
- Article
- The Veterans Precision Oncology Data Commons: Transforming VA data into a national resource for research in precision oncology.Seminars in oncologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
One of the recommendations of the Cancer Moonshot Blue Ribbon Panel report from 2016 was the creation of a national cancer data ecosystem. We review some of the approaches for building cancer data ecosystems and some of the progress that has been made. A data commons is the colocation of data with cloud computing infrastructure and commonly used software services, tools, and applications for managing, integrating, analyzing, and sharing data to create an interoperable resource for the research community. We discuss data commons and their potential role in cancer data ecosystems and, in particular, how multiple data commons can interoperate to form part of the foundation for a cancer data ecosystem.
Indexed as
Identifiers
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.