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Data Integration Approaches for Representing Stem Cell Studies.

Irena Parvanova1, Joseph Finkelstein1

  • 1Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Studies in Health Technology and Informatics
|June 24, 2020
PubMed
Summary
This summary is machine-generated.

This study reviewed online stem cell data repositories, finding current data integration methods lack standardization. Standardizing these approaches is crucial for effective stem cell research data sharing.

Keywords:
Data integrationdata sharingstandardizationstem cells

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Area of Science:

  • Biomedical research
  • Data science
  • Stem cell biology

Background:

  • Online data repositories are increasingly used for sharing stem cell research findings.
  • Existing methods for data sharing lack standardization, hindering reproducibility and collaboration.

Purpose of the Study:

  • To examine current methods for sharing stem cell research results in online data repositories.
  • To identify challenges and propose solutions for effective stem cell data integration and sharing.

Main Methods:

  • Conducted a PubMed search using MeSH terms to identify relevant repositories.
  • Performed a web-based search to supplement the database identification.
  • Reviewed identified databases for data integration approaches and organizational structures.

Main Results:

  • Identified 16 online stem cell data repositories created between 2010 and 2019.
  • Discovered 35 major rubrics organized within a five-module system across the repositories.
  • Observed wide variation in data integration approaches, including common data elements, visualization tools, and ontology mapping.

Conclusions:

  • Current stem cell data integration lacks standardization and reproducibility.
  • Standardization of data integration is essential to facilitate robust data sharing in stem cell research.
  • Developing standardized approaches will enhance the utility and accessibility of stem cell research data.