CORAL: A framework for rigorous self-validated data modeling and integrative, reproducible data analysis.

ABSTRACT:

Background

Many organizations face challenges in managing and analyzing data, especially when relevant datasets arise from multiple sources and methods. Analyzing heterogeneous datasets and additional derived data requires rigorous tracking of their interrelationships and provenance. This task has long been a Grand Challenge of data science and has more recently been formalized in the FAIR principles: that all data objects be Findable, Accessible, Interoperable, and Reusable, both for machines and for people. Adherence to these principles is necessary for proper stewardship of information, for testing regulatory compliance, for measuring the efficiency of processes, and for facilitating reuse of data-analytical frameworks.

Findings

We present the Contextual Ontology-based Re

SUBMITTER: Novichkov PS 

PROVIDER: S-EPMC9575582 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature