SUMMARY OF DATA STORAGE IN DATA CURATION--DORA BANDA (MLIS0122)

SUMMARY OF DATA STORAGE IN DATA CURATION Data storage is essential to the foundation of data curation, serving as the means by which research data and digital resources are preserved, accessed and reused for both scholarly and societal advancement. In modern digital contexts, storage strategies go beyond simple data protection, they encompass interoperability, sustainability and adherence to open science principles. Successful storage systems must therefore integrate technical resilience with institutional policies to address both immediate research demands and long-term preservation requirements. Relevance of Data Storage The significance of data storage lies in its function across the entire lifecycle of data curation. Without reliable storage infrastructures, curated datasets risk becoming in accessible or obsolete. Minamiyama et al. (2024) highlight that interdisciplinary data sharing necessitates standardised storage frameworks capable of accommodating diverse research practices while ensuring consistency and reusability. This emphasise the importance of adaptable infrastructures that can support collaboration across disciplinary boundaries. Storage lifespan Storage practices are inherently dynamic, evolving to meet retrospective, present and future needs. Parmiggiani et al. (2024) explain this process as an anticipatory generification, whereby storage systems designed to preserve historical datasets, manage ongoing collections and anticipate future reuse. This temporal orientation highlights that storage is not simply about archiving but about maintaining data in a state of readiness for unforeseen applications, thereby enhancing its long-term scholarly value. Furthermore, institutional repositories provide structured environment for the long term preservation of research data. The effectiveness of the Data Curation Networks cross institutional model, which demonstrates how collaborative infrastructures can sustain storage and curation practices across multiple institutions, such repositories ensure that storage is incorporate within broader knowledge infrastructures, thereby reinforcing the collective responsibility for data stewardship. Challenges and Future Directions Regardless of notable progress, challenges persist in ensuring scalability, metadata integration and compliance with evolving standards. Vassilakopoulou et al. (2019) emphasise the temporal unfolding of infrastructures, noting that storage systems must continually adapt to shifting technological and organisational context. Effective storage solutions therefore require not only technical innovation but also governance frameworks aligned with open science mandates. As research data continues to expand in volume and complexity, storage infrastructures must evolve to support interdisciplinary collaboration and long term sustainability (Minamiyama et al.,2024 ;Parmiggiani et al,. 2024) References Johnston, L. R., et al., (2018), Data Curation network: a cross-institutional staffing model for curating research data .International Journal of Digital Curation, 13(1), Minamiyama, Y., et al. (2024) a study on formasig the knowedge of data curation activities scross different fields.PLOS ONE. 19(4), e0301772 Pamiggiani, E., Amagyei, N .K., and Selebo Kollerud, S. K.(2024). Data curation as anticipatory generification in data infrastructure. European Journal of Information Systems, 33(5), 748-767. Vassilakopoulou, P., Grisot, M., & Ellingsen G. (2019). The temporal unfolding of data infrastructures: the case of environmental monitoring. Information Systems Journal, 29(1), 207-234.

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