Lab data management
SciPhys helps labs preserve the context around every file: who measured it, what sample it came from, which project it belongs to and what the analysis concluded.
Each researcher can manage their own data and reports.
Runs are grouped by project, material system and sample.
Principal investigators can review progress across the group.
What it does
A raw file without context is hard to trust later. SciPhys makes sample, preparation, measurement and project fields part of the upload flow so the archive is useful after the week of measurement is over.
The advisor view is designed around research questions, not administration. It surfaces missing metadata, unusual results, active projects and cross-run trends.
Once files share consistent metadata, SciPhys can compare runs across dopant ratio, annealing temperature, synthesis batch, instrument settings and time.
Workflow
Create projects, samples and upload context.
Filter or ask questions across runs and metadata.
Compare related experiments and find trend-level signals.
FAQ
Yes. Students can start with a personal workspace and add lab organization later when they need shared review or group data management.
The lab workspace is designed so advisors can view data across students, projects and samples while students still have their own working area.
Metadata makes experimental files searchable, comparable and reusable. It is the foundation for natural language search and multi-data analysis.