With RSpace, we offer a platform for researchers involved in sample collection, processing and archiving projects: the powerful connected nature of Inventory and the Electronic Lab Notebook (ELN) systems makes RSpace an ideal environment for documenting, note-taking, recording experimental details, and more.
✔ Toggle views and columns in Inventory based on what most suits your current activity: list, card, tree, and grid/visual view for containers. What is more, you can collapse the right-hand panel for an enhanced card view:
✔ Connect samples to experimental records with ease using Lists of Materials, which enable you to associate samples with a specific field of an experimental document. Decrement item quantities directly from the ELN as you execute the experiment, view core information at-a-glance, and navigate to the Inventory record with a click.
Gather data & collect samples with ease, thanks to features such as the upcoming RSpace ↔ FAIMS integration. The Field Acquired Information Management System is specifically designed to facilitate field research workflows by allowing for offline and FAIR-compliant data capture, so the ability to import data collected using FAIMS directly into RSpace as structured data can only supercharge FAIRness!
An intuitive and visually driven sample management system with powerful capabilities including offline data capture through FAIMS, easy import/export, and automatic population of templates, helps to support your field data collection and removes the need for duplicate workflows.
Learn more about the upcoming integration:
We have recently introduced support for ontologies in the RSpace ERN, through the ability to import ontology files as CSVs, which generates corresponding tags within RSpace. The PI can choose to enforce the use of ontology-only tags across the lab to ensure consistency, or researchers can enter new tags when needed for full flexibility. Tags are an incredibly powerful way to organise and aggregate research documents, as RSpace's advanced search makes tagged documents easy to locate.
What is more, we have started working with Nick Garabedian, Team Leader of the "Linked Tribological Data" group, and Alexander von Humboldt postdoctoral fellow at KIT. The group is working to develop FAIR data collection solutions within tribology and materials science that are accurate, sustainable and well-suited to the domain.
We are excited to work with Nick on developing new applications and support for ontologies, especially for samples!
You can also get in touch directly by emailing us at firstname.lastname@example.org.