The FAIR (Findable, Accessible, Interoperable and Reusable) principles were proposed to guide researchers to describe and share their data to increase data reuse and research reproducibility. Creating FAIR data can be challenging for multi-omics researchers due to a lack of tooling and a diverse landscape of (meta)data standards differing across -omics types. In X-omics, we develop a FAIR Data Cube – a set of tools and services that help researchers in different stages of the Research Data Life Cycle including the Creation and publish of multi-omics and metadata, Querying multi-omics studies, Analyzing access-protected dat
Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories r...
This presentation was given during the Festival of Genomics and Biodata 2022. Putting FAIR principle...
Findable, accessible, interoperable and reusable (FAIR) data are an increasingly important aspect of...
The FAIR (Findable, Accessible, Interoperable and Reusable) (FAIR) principles were proposed [1] to g...
In current biomedical and complex trait research, increasing numbers of large molecular profiling (o...
The increase in personal genome data generated in diagnostics and research holds great promise for a...
In 2016, a consortium of scientists (cheminformaticians, bioinformaticians, biologists, data scienti...
Data sharing and reuse are crucial to enhance scientific progress and maximize return of investments...
Data sharing and reuse are crucial to enhance scientific progress and maximize return of investments...
The key scientific output of the EATRIS-Plus project is to develop a Multi-omic Toolbox available fo...
The broad sharing of research data is widely viewed as of critical importance for the speed, quality...
Presentation given for X-omics online workshop series part 1 – "Data standards and multi-omics data ...
Physical samples with informative metadata are more easily discoverable, shareable, and reusable. Me...
A presentation highlighting how the `FAIR principles` are influencing the data management practice i...
Data stewardship is an essential driver of research and clinical practice. Data collection, storage,...
Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories r...
This presentation was given during the Festival of Genomics and Biodata 2022. Putting FAIR principle...
Findable, accessible, interoperable and reusable (FAIR) data are an increasingly important aspect of...
The FAIR (Findable, Accessible, Interoperable and Reusable) (FAIR) principles were proposed [1] to g...
In current biomedical and complex trait research, increasing numbers of large molecular profiling (o...
The increase in personal genome data generated in diagnostics and research holds great promise for a...
In 2016, a consortium of scientists (cheminformaticians, bioinformaticians, biologists, data scienti...
Data sharing and reuse are crucial to enhance scientific progress and maximize return of investments...
Data sharing and reuse are crucial to enhance scientific progress and maximize return of investments...
The key scientific output of the EATRIS-Plus project is to develop a Multi-omic Toolbox available fo...
The broad sharing of research data is widely viewed as of critical importance for the speed, quality...
Presentation given for X-omics online workshop series part 1 – "Data standards and multi-omics data ...
Physical samples with informative metadata are more easily discoverable, shareable, and reusable. Me...
A presentation highlighting how the `FAIR principles` are influencing the data management practice i...
Data stewardship is an essential driver of research and clinical practice. Data collection, storage,...
Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories r...
This presentation was given during the Festival of Genomics and Biodata 2022. Putting FAIR principle...
Findable, accessible, interoperable and reusable (FAIR) data are an increasingly important aspect of...