Addressing Research Data Management PROBLEM at Princeton University
The cure to cancer is on a disk somewhere.
John Wiggins, IT Manager @ Princeton Neuroscience Institute
Find More
John Wiggins, the IT manager at the Princeton Neuroscience Institute, introduced us to this quote that represented this sad reality and it blew our minds. Due to the lack of research data management best practices being implemented in researcher workflows, there is a mass of data being unused, inaccessible to those who can transform it into groundbreaking advancements in their fields.
Find More
Do you have data that's messy?
Researchers deal with data and make sense of it, but they have the same problem that you do. Their data is a mess!
Learn More
Research Data can vary in different sizes and formats. Some filetypes can range from spreadsheets to geo spatial data. Some files may be as small as 10Kb while some may be even over 50Gb. With such wide variety of data, managing it all becomes a huge challenge for researchers.
Learn More
What is Research Data Management?
The process of giving data the proper labeling, storage, and access at every stage of a research endeavor is known as research data management.
..but why manage data?
Research data management is essential for maintaining data accuracy, reliability, and accessibility throughout the research lifecycle. It enhances collaboration, ensures compliance with regulations, and maximizes the impact of research by making data reusable and easily shareable.
AT PRINCETON,
How might we transform research data management to enhance meaningful collaboration, optimize storage, and improve efficiency, ensuring enduring research value?
We started with...
Understanding the Research Data Management Landscape
Despite our client's initial evaluations revealing the need for a centralized system, our in-depth research uncovers critical insights that underscore and amplify the importance of this endeavor, identifying the underlying issues plaguing data management.
We had a real-world problem to solve, but as designers, it’s our responsibility to address more than just today’s challenges. Our solutions not only tackle current user pain points but also contribute to scaling and maturing the TigerData tool.
We asked ourselves, how do we balance futuristic solutions with real-world problems? How can we bridge the gap between today and tomorrow through our solutions?
