The big picture
Riffyn is designed to serve as an open platform for:
Experimental method design.
Data capture and automated contextualization.
Automated structuring and integration of data for mining and analytics.
Openly sharing methods and data.
Laboratory data system of record
Riffyn can serve as your laboratory data system of record. It permanently stores everything you put into it with 5X backup and 3X real time failover redundancy. It has an audit log, is CFR 21 Part 11 compliant for preclinical and clinical data, and is ISO27001:2013 compliant.
Open data ecosystem
Riffyn is designed to be an open ecosystem. You can access your Riffyn data via the app and programmatically through the Riffyn API. Either route gives you the ability to read and write data in a structured, computable format. Using the Riffyn API offers tremendous extensibility for data analytics and for integration with other data and automation systems.
Getting data in
Riffyn offers four primary routes for data capture:
Manual data entry — much like a spreadsheet and with some unique features
File parsing — configurable parsing of Excel, Tab, and CSV files of almost any shape and size
Data Agent — live data capture from relational databases, like MySQL, and data historians, like OSI Pi Server
API — RESTful API for programmatic reading and writing of data to and from other data and automation systems, or analytical pipelines
Data visualization & analysis
The magic of Riffyn is that it automatically integrates and assembles all of your data for visualization and analysis across time, operation, scientific domain, and collaborating teams.
But it may come as a surprise that Riffyn has limited built-in data analytics and visualization. This is intentional — we believe there are a huge number of awesome tools already out there for analysis (JMP®, Spotfire, Tableau, Minitab, R, Jupyter, Spark,... the list goes on). Why reinvent the wheel?
So we prioritized making your data instantly available to these external programs in a form that's ready for visualization and machine learning. You can get your data by clicking Export within the Riffyn user interface (UI), or making a call to the API to fetch the same data. Then you can pipe it directly into your favorite analysis tool.
Data analysis packages
If you have some flexibility on your choice of analysis tool, Riffyn strongly recommends JMP®. After 15 years working with scientific data, we think JMP offers more than just about any other analysis tool. We also built a powerful RiffynTools AddIn package for JMP that automates many of the most common scientific data analyses and actions — everything from plate data normalization to pivoting to hit-picking and tagging of data.
What about Excel?
We strongly recommend you to have at least one data analysis package to pair with Riffyn that is NOT Excel! Excel is just not up to the job of deep data analysis in today's world.
Over the coming months and years, we'll build more and more data analysis tools into Riffyn — not to reinvent the wheel, but to give you faster and more seamless access to key tools for interpretation and decision support.
When making your first new process and experiment start simple!
We have found that new users get going faster, learn faster, and gain more value with less effort when they start with modest initial processes and experiments, or even just capturing a portion of a larger experimental process.
It's like any new thing, take baby steps and gain some success on something small and easy before trying to tackle the complex.
For example, make a single-step process to capture your final assay data. Once that's working, add a few upstream sample prep steps and reactions to capture more of your experimental process. You'll be building confidence and a useable dataset of increasing sophistication the whole way along.
Help improve the Riffyn app
We never stop working to make Riffyn better, easier, and more powerful. To learn more about how we improve Riffyn, read the product release notes.
Share your ideas and requests
Read a few help pages, particularly the Getting Started section . An hour spent upfront on orientation may save you many hours later.
To see what you can create in Riffyn, explore public processes curated by the Riffyn Team.
While you work, make use of In-App Help.
If you get stuck, find solutions in our Best Practices and FAQs.
Use the discussion forums to post questions and help each other with best practices, solutions and ideas
Explore our Quick Tutorials for New Users.