Empowerment: The Final CADRE Pillar

1/23/20
This week, we are introducing the final pillar in this series.

We know that CADRE is working to provide affordable, sustainable access to a broad community of users who want to work more effectively with big data, all while promoting reproducible research through high-quality data and data-analytics tools.

All of this is done in service of empowering anybody, whether it’s a bibliometric researcher or a member of the general public, to work effectively with big data. After all, we consider CADRE to be a science gateway to standardized text- and data-mining services for big bibliometric datasets.A group of pillars that read: Community, Access, Data, Reproducibility, and Empowerment. Illustration.

Our final pillar in this series, Empowerment, completes the CADRE foundation that includes: Community, Access, Data, Reproducibility, and Empowerment.

Similar to the motives behind each of our other pillars, we know that by lowering the technological barriers for big data analytics, we are advancing data-driven research for those who may not have otherwise been able to perform their research without CADRE.

A major part of empowerment through CADRE comes from the community of users who take part in the platform. Users establish and work from shared standards, create and share helpful tools for other users to take advantage of, and build off of each other's work.

Empowering researchers

The platform also empowers researchers by giving users data in the form best-understood by them, whether that’s in a graph-based, relational, or native format.

Additionally, CADRE’s tools that ensure everyone is capable of working with the data are provided in an accessible way for platform users. Analytics tools and data processing and querying software can be accessed from users’ private cloud and local compute resources. The Jupyter coding environment on the platform, along with community-built analytics and visualization tools, ensure users have the option to manually code their tools or work in a guided interface.

As you can tell from this series, CADRE’s mission doesn’t boil down to a simple solution. Instead, the multitude of CADRE features -- all offered in an intentional way -- are coming together to solve major big data issues increasingly faced by researchers.

If you are interested in going back to read the rest of our pillar series or to learn more about CADRE, visit our blog page. Want to know what CADRE can do for you? Let us know or follow us on Twitter at @CADRE_Project.