Rory attended the in-person iRODS User Group Meeting back in July at KU Leuven, Belgium. iRODS is an open-source data management software that virtualizes where the data is stored, which enables a useful layer of abstraction: users are able to access their data no matter the device it is stored on, and links to resources are more robust. In addition, iRODS has an extensive plugin architecture that includes authentication, databases, and a powerful API.
You can view Rory's lightning talk on the planned integration between RSpace and iRODS in the video above!
A full list of the presentations, including links to videos and slides, are available on the event page.
RSpace is a fully integrated sample management and electronic lab notebook solution. Build a record of your research in an ELN that connects with the research tools you already use: request a demo or contact us to learn more.
February 20, 2023
RSpace Inventory is now publicly available for all enterprise and teams customers at no additional cost! This post includes a short video providing an overview of Inventory's key features and details on what lies ahead!
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Research Space and iRODS Partner to Enable Virtual File Storage and Meta-Data Solutions for Institutional Research Data ManagementNovember 28, 2022
We are announcing an integration with iRODS, a data discovery, workflow automation, secure collaboration, and data virtualization platform!
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RSpace @ Supercomputing 2022!November 15, 2022
RSpace is attending Supercomputing 2022 and presenting a poster on 'Building a Machine-Actionable Pipeline for Research Data' in collaboration with UCL ARC. We're also giving a presentation on the iRODS-RSpace integration and are available to chat during the event!
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Building enhanced FAIR Workflows through use of PIDs within and between interoperable research toolsOctober 4, 2022
Rory presented at an RDA session on tool interoperability in research as part of RDA's 19th Plenary, detailing how RSpace and Inventory aim to enable workflows supporting experimental reproducibility and comprehensive capture of sample data.
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