Making genomic data FAIR through effective Data Portals

Genomic data portals collect, annotate, and make data files available to researchers and, increasingly, AI algorithms. They are run by, among others, broad data archive repositories or consortium-specific Data Coordination Centers. Their design may seem a niche topic, but these portals realize the open data principles by making millions of data files findable, accessible, interoperable, and reusable (FAIR). Almost every researcher uses them, yet, we are unaware of published guidance on how web data portals should be funded, built, and run. We present lessons we have learned from creating genomics-focused data portals. We highlight the importance of funders in defining rules, human data wranglers as liaisons, a flexible and simple metadata schema, and a user-centered engineering process. We also present concrete suggestions on accessions, metrics, testing, controlled access, and licenses. Finally, we discuss the unsolved problems of interoperability, portal reuse, and long-term stability. We hope these guidelines can help funders and creators of new data portals develop a better understanding of the unique challenges they may face and possible solutions.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2025-11-28
DOI
https://doi.org/10.1038/s41597-025-06142-x
Citations
2
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
8.34

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Making genomic data FAIR through effective Data Portals

Clay Fischer, Tim Harris, Marc D. Perry, Parisa Nejad et al.
2 citations
Scientific Data
Scientific Computing and Data Management
8.34
article

Making genomic data FAIR through effective Data Portals

Clay Fischer, Tim Harris, Marc D. Perry, Parisa Nejad, Mark Diekhans, Benedict Paten, Matthew L Speir, Maximilian Haeussler, Wei Kheng Teh, W. James Kent, Richard D. Schwartz
article en
2 citations

Abstract

Genomic data portals collect, annotate, and make data files available to researchers and, increasingly, AI algorithms. They are run by, among others, broad data archive repositories or consortium-specific Data Coordination Centers. Their design may seem a niche topic, but these portals realize the open data principles by making millions of data files findable, accessible, interoperable, and reusable (FAIR). Almost every researcher uses them, yet, we are unaware of published guidance on how web data portals should be funded, built, and run. We present lessons we have learned from creating genomics-focused data portals. We highlight the importance of funders in defining rules, human data wranglers as liaisons, a flexible and simple metadata schema, and a user-centered engineering process. We also present concrete suggestions on accessions, metrics, testing, controlled access, and licenses. Finally, we discuss the unsolved problems of interoperability, portal reuse, and long-term stability. We hope these guidelines can help funders and creators of new data portals develop a better understanding of the unique challenges they may face and possible solutions.

Scientific DataVol. 12(1)
European Bioinformatics Institute (GB), University of California, Santa Cruz (US)
Silicon Valley Community Foundation, Alex's Lemonade Stand Foundation for Childhood Cancer, California Department of Public Health, National Heart, Lung, and Blood Institute
Openalex Percentile: Top 2%
Scientific Computing and Data Management
8.34
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.