Collaborate on your data. Generate more results.
Rinocloud makes it easy to organise and discuss all your research data.
Get started Or watch the demoFor scientists that work with data.
Adding extra context to your data, like parameters, metadata, discussion, means that you can deduce more insights and generate more results.
Search
A familiar file system, with massively powerful search.
By querying all the parameters saved during an experiment or simulation, you can find exactly the data or notes you want, instantly.
Search returned 4 results.
| Name | Size | Owner | Updated | Metadata |
|---|---|---|---|---|
| spectrum.txt | 14kB | Susan | 2 days ago | sample_id: A3303, laser_power: 134.4, laser_units: uW |
| laser_exp.note | 26kB | Susan | 3 days ago | sample_id: A3303, laser_power: 134.4, laser_units: uW |
| uPL.txt | 1.8mb | John | 2 weeks ago | sample_id: A3303, laser_power: 134.4, laser_units: uW |
| time_gate.txt | 32mb | Susan | 2 weeks ago | sample_id: A3303, laser_power: 134.4, laser_units: uW |
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spectrum_fit.txt to laser_1404
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@michele Are you sure about the value of $\alpha$ - I thought it was around 400 ps.
by piedra on March 5th, 2016 -
Yeah I'm pretty sure its 120ps, I tested it yesterday in my lab
by sarah on March 5th, 2016 -
Hmmm, perhaps I need to revise some of my models.
by piedra on March 5th, 2016
Coming soon...
All your notes, next to your data.
With Rinocloud you can reference files, folders, collections and search results all from the notebook. With our markdown, or rich text-editor, you can embed search results, tables, graphs and equations.
Sample A3303 Notes.
Linear optical quantum computing has been proven to be computationally efficient with single photon sources and a series of beamsplitters and phase shifters. Although few photon gates have been demonstrated using bulk optics, scaling to more complex circuits requires integrated photonic technology.
$$E = mc^2 \mu^2 + \int_{x_1}^{x_2}[(\delta \alpha + a_n) x^{n+\delta}]dx$$
Example in python
1 import rinocloud 2 rinocloud.api_key = "your api key" 3 4 dataset = rinocloud.Object("new_laser") 5 6 dataset.laser_id = "A3303" 7 dataset.laser_power = 10 8 9 experiment.turn_on_laser(laser_power) 10 11 experiment.save_results(dataset.filepath) 12 13 dataset.save() 14
Programming integrations
Our integrations make it easy to organise your data automatically.
Plug into your experiments and simulations using our bindings for Python, MATLAB, LabView: Making it easy to save all data and parameters to a secure central location.
See our integrationsWe have many more integrations coming soon... request one!
Testimonials
Here's what some of our users are saying.
“ The Rinocloud LabVIEW integrations made it easier for us to point the data from a complicated lab control system to one place. It saves us lots of time each day. ”
Dr. Gediminas Juska. Photonics researcher, Tyndall Institute.
“ Previously I needed to manually search folders for my data, because I couldn't search by metadata; it wasn't available. Rinocloud lets me search all my crystallography data with instant results. ”
Bianka Seres. Biology PhD student, University of Cambridge.
“ The easy setup and the data flow from one program to the next is great. Instead of searching and manually importing into MATLAB, my data just appears where I want it to. ”
Rob Shalloo. Physics PhD student, University of Oxford.
Notes
Fitted gaussian with $\sigma = \lambda \alpha$, where $\alpha$ is the new value of 120 ps.
Dataset included in notebook laser_set_GaAs