Note - this was an internal funding request solicited by the Center for Open Science. It's been funded!

Brief: We propose to integrate OSF into Galaxy as a data store. For this purpose, we request 3 months of funding (6 months, half-time) for one developer, plus travel.

Introduction and summary: Galaxy is a commonly used open source biomedical/biological sequence data analysis platform that enables biologists to put together reproducible pipelines and execute analyses locally or in the cloud. Galaxy has a robust and sophisticated Web-based user interface for setting up these pipelines and analyzing data. One particular challenge for Galaxy is that on cloud instances, data storage and publication must be done using local filesystems and remote URLs, which adds a significant amount of complexity for biologists interested in doing reproducible computing. Recently, Galaxy gained a data abstraction layer that permits object stores to be used instead of local filesystems. The Center for Open Science’s Open Science Framework (OSF), in turn, is a robust platform for storing, manipulating, and sharing scientific data, and provides APIs for accessing such data; the OSF can also act as a broker for accessing and managing remote data stores, on e.g. cloud providers. Integrating the OSF’s object store into Galaxy would let Galaxy use OSF for data persistence and reproducibility, and would let Galaxy users take advantage of OSF’s data management interface, APIs, and authentication to expand their reproducible biomedical science workflows. This integration would also rigorously test and exercise newly developed functionality in both Galaxy and the OSF, providing valuable use cases and testing.

Our “stretch” goal would be to expand beyond Galaxy and work with Project Jupyter/IPython Notebook’s data abstraction layer to provide an OSF integration for Project Jupyter.

We note with enthusiasm that all groups mentioned here are robust participants in the open source/open science ecosystem, and all projects are full open source projects with contributor guidelines and collaboration workflows!

Broader impacts: If successful, the proposed project addresses several broader issues. First, the OSF would have an external consumer of its APIs for data access, which would drive the maturation of these APIs with use cases. Second, the OSF would expand to support connections with a visible project in a non-psychology domain, giving COS a proof-of-concept demonstration for expansion into new communities. Third, the Galaxy biomedical community would gain connections to the OSF’s functionality, which would help in execution, storage, and publication of biomedical data analyses. Fourth, the Brown Lab would then be able to explore further work to build their Moore-DDD-funded data analysis portal on top of both Galaxy and the OSF, leveraging the functionality of both projects to advance open science and reproducibility. Even a partial failure would be informative by exposing faults in the OSF or Galaxy public APIs and execution models, which could then be addressed by the projects individually. This project would also serve as a “beta test” of the COS as an incubator of open science software projects.

Longer-term outcomes: the Brown Lab and the COS are both interested in exploring the OSF as a larger hub for data storage for workflow execution, teaching and training in data-intensive science, and hosting the reproducible publications. This proposed project is a first step in those directions.