Where's the fanFAIR?

Choosing to create a FAIR (Findable, Accessible, Interoperable, Reusable) laboratory environment seems obvious. Who wouldn’t want to be able to find and reuse their data? But it’s not as easy as it sounds. The transformation requires scientific technical backbone and knowhow.

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Timothy Gardner
Riffyn delivers FAIR data for machine learning in R&D organizations

In a recent interview with Peta Crunch, Riffyn Founder and CEO, Timothy Gardner, shares what Riffyn has accomplished and what its future will hold. Tim provides six examples of how Riffyn has helped customers achieve significant breakthroughs. He also shares the exciting direction the company is moving - product lifecycle management (PLM ) and out-of-the-box data analytics and extensibility. Read the interview!

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Joann Calve
Riffyn makes machine learning in science an everyday reality

The barrier to unlocking the full potential of machine learning isn’t bad analytical tools or a fear of statistics: it’s bad data resulting from poorly designed studies and data systems. Using scientific blueprints to organize people, process, technology, and data, Riffyn aims to make machine learning in science an everyday reality.

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Joann Calve
What does reproducible science really mean?

The voluminous discussion and conflicting language on scientific reproducibility over the past decade has obscured its meaning. But in fact, there is a very clear scientific meaning for reproducibility—one that has been thoroughly developed by brilliant minds over the past 70+ years, and routinely practiced around the world every day.

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Timothy Gardner
Digital publishing isn't enough: the case for ‘blueprints’ in scientific communication

If modern software engineering worked like science, programmers would not share open source code; they would take notes on their work and then publish long-form articles about their software. Months or years later, their colleagues would attempt to reproduce the software based on the article. It sounds a bit silly, and yet even, this level of prose-based methodological discourse has deteriorated in science communication.

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Timothy Gardner
Riffyn SDE published in a ground-breaking study in the journal Scientific Data

Riffyn SDE was created to address the crisis in scientific reproducibility, and demands for more cost-efficient drug development. Its potential to transform the quality and reusability of scientific work was recently demonstrated in a study published in Scientific Data by Delft University of Technology that harnessed Riffyn SDE to execute a complex set of microbial fermentation experiments.

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Timothy Gardner
R&D Data as a Competitive Advantage

In recent years, several pharmaceutical companies have invested millions of dollars in collecting and storing ever increasing amounts of R&D data. However, these companies will only see a return on their investments if they can determine how to use these data to create a sustainable competitive advantage. Riffyn’s Doug Williams walks us through a use case of how data could be used to create a competitive advantage in R&D and explains where to start if you want to begin using all those data you collect in the most effective way.

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Douglas Williams
Riffyn Spotfire Starter Template

Tibco Spotfire is one of the most popular visualization applications within R&D organizations. Many Riffyn customers use it as their primary data visualization software.  To support these efforts, we have created the Riffyn Spotfire Starter Template to serve as a starting point for creating dashboards that import Riffyn data as a Data Tables.


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Douglas Williams
Your Assay Results May Be Wrong

Researchers often take assay data at face value, assuming it’s accurate because it came out of an instrument. Here we explain why that can be dangerous, and how assay validation can make your science faster and better.

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Timothy Gardner