Research Data Management: Storing Data

In the realm of research, managing vast amounts of data efficiently is paramount. Effective data storage solutions not only safeguard data but also enhance accessibility and collaboration among researchers. Let’s delve into some real-world case studies that shed light on best practices and lessons learned in storing research data.

Monash University’s Large Research Data Store (LaRDS)

Monash University in Australia established the Large Research Data Store (LaRDS) in 2006 to provide a reliable and secure environment for research data storage. LaRDS offers thousands of terabytes of storage capacity, catering to the diverse needs of researchers across various disciplines. The system automatically backs up data to tape in two physically diverse data centers, ensuring redundancy and data protection. Researchers have utilized LaRDS for routine data backups, collaboration through platforms like Confluence wiki and the Sakai virtual research environment, and publishing data via the Monash Research Repository, ARROW. (dcc.ac.uk)

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Panasonic’s Data Governance Framework

Panasonic’s Smart Mobility Office faced challenges in managing massive volumes of data, including connected IoT, weather, and geospatial data, amounting to 3TB per week. To address data discovery and accessibility issues, Panasonic implemented Secoda, a centralized data governance platform. This platform enabled data lineage tracking and visualization, allowing the company to monitor data flow from origin to destination. Additionally, Secoda’s role-based data governance ensured that users accessed only data relevant to their roles, establishing business-unit-specific schemas and improving structured data ingestion. (research.aimultiple.com)

Unilever’s Master Data Management Strategy

Operating in nearly 190 countries with over 400 brands, Unilever required a master data management strategy to handle complex global operations. The company partnered with a master data management solutions provider to digitize its management operations across vendor, customer, and product channels. This initiative led to centralized and documented data points from diverse categories and locations, resulting in increased efficiency, data quality, and speed. The implementation of a new vendor data management process also streamlined HR operations, reducing vendor onboarding time from days to hours. (research.aimultiple.com)

Stanford University’s Data Backup Practices

Stanford University Libraries emphasizes the importance of creating multiple backup copies of research data to prevent loss due to unforeseen events. A poignant example involves a researcher who had processed notes stored in three copies, all of which were destroyed in a fire. This incident underscores the necessity of not only creating backups but also ensuring they are stored in different locations to mitigate risks. (guides.library.stanford.edu)

Virginia Tech’s Data Management Training

A case study at Virginia Tech demonstrated how targeted training in data and project management can lead to substantial improvements in research data quality for field research projects. The training emphasized the importance of data quality to field workers and provided consultative support from Data Services in the University Libraries. This approach resulted in enhanced data management practices and improved research outcomes. (datascience.codata.org)

Key Takeaways

These case studies highlight several best practices in research data storage:

• Centralized Data Storage: Implementing centralized storage solutions, like Monash University’s LaRDS, facilitates efficient data management and access.

• Data Governance Frameworks: Establishing robust data governance frameworks, as seen with Panasonic’s Secoda platform, ensures data integrity and accessibility.

• Comprehensive Data Management Plans: Developing detailed data management plans, including backup strategies and training programs, is crucial for maintaining data quality and security.

By learning from these examples, researchers can develop and implement effective data storage strategies tailored to their specific needs, ensuring the longevity and reliability of their research data.

References

• Monash University. (n.d.). Bringing it all together: a case study on the improvement of research data management at Monash University. Digital Curation Centre. (dcc.ac.uk)

• Aimultiple. (2024). 10+ Data Governance Case Studies: Real-Life Examples. (research.aimultiple.com)

• Stanford University Libraries. (n.d.). Store & backup files – Data best practices and case studies. (guides.library.stanford.edu)

• Data Science Journal. (2019). The Impact of Targeted Data Management Training for Field Research Projects – A Case Study. (datascience.codata.org)