Metadata integrity in bioinformatics: Bridging the gap between data and knowledge

被引:2
|
作者
Caliskan, Aylin [1 ]
Dangwal, Seema [2 ]
Dandekar, Thomas [1 ]
机构
[1] Univ Wurzburg, Dept Bioinformat, Bioctr, D-97074 Wurzburg, Germany
[2] Stanford Univ, Stanford Cardiovasc Inst, Dept Med, Sch Med, Stanford, CA 94305 USA
关键词
Meta-data; Error; Annotation; Error-transfer; Wrong labelling; Patient data; Control group; Tools overview; CONTROLLED VOCABULARIES; GENE-EXPRESSION; CELL; CHALLENGES; ONTOLOGIES;
D O I
10.1016/j.csbj.2023.10.006
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
In the fast-evolving landscape of biomedical research, the emergence of big data has presented researchers with extraordinary opportunities to explore biological complexities. In biomedical research, big data imply also a big responsibility. This is not only due to genomics data being sensitive information but also due to genomics data being shared and re-analysed among the scientific community. This saves valuable resources and can even help to find new insights in silico. To fully use these opportunities, detailed and correct metadata are imperative. This includes not only the availability of metadata but also their correctness. Metadata integrity serves as a fundamental determinant of research credibility, supporting the reliability and reproducibility of data-driven findings. Ensuring metadata availability, curation, and accuracy are therefore essential for bioinformatic research. Not only must metadata be readily available, but they must also be meticulously curated and ideally error-free. Motivated by an accidental discovery of a critical metadata error in patient data published in two high-impact journals, we aim to raise awareness for the need of correct, complete, and curated metadata. We describe how the metadata error was found, addressed, and present examples for metadata-related challenges in omics research, along with supporting measures, including tools for checking metadata and software to facilitate various steps from data analysis to published research.
引用
收藏
页码:4895 / 4913
页数:19
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