In July, we announced the initial step in our collaboration with the Galaxy community, making the RSpace Gallery a native file source for Galaxy workflows. With RSpace version 1.113, we're adding the ability to upload data from RSpace documents directly to Galaxy and track computational workflows that use this data.

Connecting Experimental Data with Computational Analysis

Mounting RSpace as a file source in Galaxy makes it easier for researchers to transfer data between platforms, but researchers still need to manually maintain experimental context when moving data into computational workflows. The new functionality available with the latest RSpace version uploads data from RSpace documents directly to Galaxy, where it creates a new computational workspace (called a History) with systematic naming based on the originating RSpace document and field identifiers.

The data is annotated with URLs and RSpace identifiers so it can be traced back to its experimental origin. Researchers can then invoke any workflow provided by theirGalaxy instance. When complete, the results can be exported back to RSpace manually or through the existing pyfilesystem integration. This allows for the export of individual datasets or full workflow provenance objects, such as workflow RO-crates or BioCompute Objects.

How It Works: Data Upload and Workflow Tracking

The integration appears as a Galaxy icon in the RSpace document editor. Researchers can select data attached to their documents, upload it to Galaxy where a new systematically named History is created and linked to the RSpace document, then track any workflows that use this data from within RSpace. Results can be imported back using manual export or the pyfilesystem integration.

Example: Forest Analysis Through Image Segmentation

To demonstrate this integration, we've prepared a video showing a Voronoi segmentation workflow for analyzing forest imagery. The video shows how a researcher can

• Document field work with images attached in RSpace
• Upload selected images directly to Galaxy from within the RSpace document
• Use Galaxy's Voronoi segmentation tools for analysis while RSpace maintains the connection between the original field documentation and computational workflow history
• Monitor the workflow progress from within the original RSpace document
• Export analysis results back to RSpace

The workflow example in the video utilises the pyfilesystem solution and integration into Galaxy 25.0 and the newly added RSpace functionality for data upload and workflow tracking. While researchers manually configure and run workflows within Galaxy, the integration reduces manual steps in moving data between platforms and helps maintain provenance throughout the analysis process.

Looking ahead

Future developments will include improvements to the pyfilesystem as described earlier, automated reporting of results back to RSpace, enhanced RO-Crate support for standardized metadata exchange, and improved templating in RSpace for sharing and reusing specific workflow configurations. This work is part of our broader effort to connect research documentation with computational workflows and reduce friction in FAIR data management.

Get Started

RSpace 1.113 with the enhanced Galaxy integration is available now. For detailed instructions and documentation, visit our Galaxy integration documentation.