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3M.1.DEMO: Searching: Search Representative Metadata Across Catalogs and Data Storage Endpoints Using a Pilot UI and Resolving to Data on the Cloud


The full stacks demonstrate how to search metadata fields for GTEx datasets in several of their storage systems. Depending on the stack implementation, the search can occur via machine friendly interfaces like APIs or via human friendly interfaces like point and click websites. The ultimate result of the searches are cloud URLs pointing to data files relevant to the search query. These features relate to both KC3 (Findability) and KC4 (Software stacks).

What they achieved

In general, the teams showcased the first stages of search capabilities for GTEx and other datasets. Each interface is unique, and will be useful for different types of use cases. For example, DERIVA provides search and browse, data export, and virtual collection capabilities for the GTEx and EBI datasets. The exported output data of the search can be sent through a workflow and eventually analyzed using JupyterHub.

Why is this valuable?

These services give scientists and researchers a way to query the metadata for GTEx and other datasets in a reliable, consistent way for each stack and return links to data that can be analyzed via a computational workflow on the stacks, downloaded, or shared with colleagues. This is a first step towards our goal of making an ecosystem of data, tools and resources available to the research community.