Metadata in the BioSample Online Repository are Impaired by Numerous Anomalies

08/03/2017
by   Rafael S. Gonçalves, et al.
0

The metadata about scientific experiments are crucial for finding, reproducing, and reusing the data that the metadata describe. We present a study of the quality of the metadata stored in BioSample--a repository of metadata about samples used in biomedical experiments managed by the U.S. National Center for Biomedical Technology Information (NCBI). We tested whether 6.6 million BioSample metadata records are populated with values that fulfill the stated requirements for such values. Our study revealed multiple anomalies in the analyzed metadata. The BioSample metadata field names and their values are not standardized or controlled--15 not specified in the BioSample data dictionary. Only 9 out of 452 BioSample-specified fields ordinarily require ontology terms as values, and the quality of these controlled fields is better than that of uncontrolled ones, as even simple binary or numeric fields are often populated with inadequate values of different data types (e.g., only 27 the metadata in BioSample reveal that there is a lack of principled mechanisms to enforce and validate metadata requirements. The aberrancies in the metadata are likely to impede search and secondary use of the associated datasets.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

08/17/2018

The Variable Quality of Metadata About Biological Samples Used in Biomedical Experiments

We present an analytical study of the quality of metadata about samples ...
03/21/2019

Using association rule mining and ontologies to generate metadata recommendations from multiple biomedical databases

Metadata-the machine-readable descriptions of the data-are increasingly ...
09/25/2020

A review of metadata fields associated with podcast RSS feeds

Podcasts are traditionally shared through RSS feeds. As well as pointing...
06/20/2019

Cleaning Noisy and Heterogeneous Metadata for Record Linking Across Scholarly Big Datasets

Automatically extracted metadata from scholarly documents in PDF formats...
05/23/2017

Calidad en repositorios digitales en Argentina, estudio comparativo y cualitativo

Numerous institutions and organizations need not only to preserve the ma...
04/30/2021

Content-based subject classification at article level in biomedical context

Subject classification is an important task to analyze scholarly publica...
03/19/2019

Aligning Biomedical Metadata with Ontologies Using Clustering and Embeddings

The metadata about scientific experiments published in online repositori...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.