Reproducibility: The Fourth CADRE Pillar

1/17/20
Before jumping into the next part of the CADRE Pillar series, let’s take a step back and review what we’ve covered so far.

Our Community Pillar represents how CADRE is built upon shared resources and ideas by a diverse group of stakeholders for a broad range of users. Our Access Pillar is defined by our effort to provide affordable, sustainable infrastructure and a user-friendly enviornment with community-based tools for academic libraries and researchers that want to work with big bibliometric data.

Lastly, our Data Pillar shows how CADRE solves major technological barriers in working with big data, such as with the “Four V’s of Big Data.”A sign that reads

The data and tools we are setting out to create, however, are focused especially on facilitating reproducible research, bringing us to our fourth pillar: Reproducibility.

When we promote high-quality data and data-analytics tools, we are improving reproducibility across research. By creating an infrastructure where researchers can compare, collaborate, and build on each other’s work from shared standards, we will be creating a platform that advances research and discovery.

The path to reproducibility

Scientific reproducibility begins with the data researchers incorporate into their work, which must be collected, cleaned, parsed, and updated in the same way.

Thanks to CADRE’s shared cloud storage, researchers will be able to work with a standardized version of data to make their end products more comparable across studies, encouraging reproducibility and replicability. Researchers can additionally attach unique Digital Object Identifiers (DOIs) to their work. These DOIs play an important part in data provenance, which ensures reproducibility by documenting and archiving researchers’ computing environments, data, analyses, and software.

While we will automatically archive the documentation for each user’s research assets, they will have the opportunity to choose which level of sharing they’d like to participate in on the platform, such as private research assets, sharing permissions to individuals or groups, or publicly shared research assets.

Another role reproducibility plays in CADRE is through the tools CADRE users will use to work with their own or other researchers' data. Users can reproduce the code, queries, algorithms, results, visualizations, workflows, and more that other users have shared into the RAC Marketplace.

Our commitment to reproducibility drives CADRE to provide standardized, high-quality data and tools, both of which we know will promote and accelerate scientific discovery.

Don’t want to miss the final pillar in this series? Be sure to follow us on Twitter to see when the next and final post goes live.