Dataset Information

FAIRness and Usability for Open-access Omics Data Systems.

ABSTRACT: Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

SUBMITTER: Berrios DC

PROVIDER: S-EPMC6371294 | biostudies-other | 2018

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

FAIRness and Usability for Open-access Omics Data Systems.

Berrios Daniel C DC Beheshti Afshin A Costes Sylvain V SV

AMIA ... Annual Symposium proceedings. AMIA Symposium 20181205

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The ran ...[more]

PMID: 30815061

Similar Datasets

Project description:Background: Latin American countries show a fast-growing rate of non-communicable diseases (NCDs) and diet is a critical risk factor that must be properly assessed. Automated dietary assessment tools to collect 24-h dietary recalls (24HR) are lacking in Argentina. Objective: This study aimed to develop an open-access automated tool (MAR24) for collecting 24HR using a multiple pass method and a database containing foods and recipes commonly consumed in Argentina. Methods: MAR24 was developed based on data from 1,285 24HR provided by male and female participants aged 18 to 68 years from the six Argentinian geographical regions. The main structure and interface of the tool were designed using Visual Basic for Applications programming language in Excel Microsoft Office 365, integrating the five steps of the United States Department of Agriculture (USDA) Automated Multiple-Pass Method (AMPM) for the application of 24HR in Spanish. The tool underwent alpha testing and expert assessment to address structural and usability issues. Critical feedback and face validation from researchers and experienced dietitians, and repeated testing to collect 24HR were used to adjust and improve the tool. Results: A total of 968 food items and 100 standard Argentinian recipes were added to its database. MAR24 allows the estimation of the nutrient profile of dietary intake. The analytic food composition includes energy and 50 nutrients including water, macronutrients, total dietary fiber, total sugar, 10 minerals, 19 vitamins, eight fatty acids, cholesterol, ethyl alcohol, caffeine, and theobromine. MAR24 includes a user manual and technical manual to guide users to apply changes (e.g., add foods or recipes, or change food designation according to local terms) to fit different research and clinical applications. Conclusions: MAR24 is the first tool that uses the AMPM methodology for 24HR applications in Argentina. The tool may be used in clinical practice and clinical trials for monitoring purposes, and in validation of food frequency questionnaires (FFQ) for nutritional epidemiology studies addressing dietary-associated risk factors for NCDs.

Dataset Information

FAIRness and Usability for Open-access Omics Data Systems.

Publications

FAIRness and Usability for Open-access Omics Data Systems.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets