SELECTION AND APPRAISAL OF DATA FORM EDITH HOPE CHAVULA (MLIS0225)

 

SELECTION AND APPRAISAL OF DATA.

Introduction

Selection and appraisal serve as the foundational gateway within the digital curation lifecycle, directly dictating which data assets merit long-term preservation infrastructure. The rapid expansion of information generation renders the preservation of all digital assets financially and operationally impossible (Higgins, 2018; Whyte & Wilson, 2010). Digital curation systematically mitigates this information overload by employing objective criteria to separate transitory data from materials with enduring secondary research value (Lee & Tibbo, 2021). Consequently, appraisal functions not merely as a passive storage filter, but as an active workflow ensuring that limited organizational resources support authentic, accessible, and high-value historical records (Madu & Enyinnah, 2021; Niu, 2016).

Establishing Policy and Compliance Safeguards

The first phase of appraisal requires establishing formal institutional guidelines that harmonize with broader regulatory mandates. Selection decisions must respect legal property constraints, public record directives, organizational collection policies, and privacy boundaries (Madu & Enyinnah, 2021; Niu, 2016; Whyte & Wilson, 2010). Curators utilize these mandates to construct collection profiles that prevent arbitrary or biased retention behaviors.

Evaluating Core Data Characteristics

Curators evaluate incoming assets using a strict framework consisting of evidential, informational, and historical values (Niu, 2016; Tallman & Work, 2022). A dataset is only selected if its provenance is clear, its structural integrity is intact, and it contains rich administrative and technical metadata (Lee & Tibbo, 2021). This ensures the resource remains understandable to future user groups independent of the original creator (Chawinga & Zinn, 2020).

Assessing Technical Viability and Long-Term Costs

Modern curation policies prioritize the technological feasibility of long-term preservation over simple historical interest. Materials reliant on proprietary or rapidly decaying software applications incur unsustainable maintenance costs [Higgins, 2018]. Curators weigh the anticipated research value against the technical complexities of format transformation, migration pathways, and emulation before committing resources (Chawinga & Zinn, 2020; Tallman & Work, 2022).

Executing Early-Lifecycle Intervention

Unlike paper-based practices, appraisal in digital ecosystems must happen close to the time of data creation. Waiting until a project concludes often results in severe context loss, missing metadata, or corrupted file states (Chawinga & Zinn, 2020; Higgins, 2018; Whyte & Wilson, 2010). Early validation allows curation practitioners to capture data while the links, dependencies, and internal logic remain functional.

Figure 1 Data curation cycle

Conclusion

In conclusion, the appraisal and selection stages function as the critical architectural filter for trusted digital repositories. By balancing legal constraints, user demands, and technical sustainability, information professionals systematically insulate archives from digital clutter while preserving authentic cultural assets. As data sets expand, these rigorous selection paradigms remain essential for maintaining a highly discoverable and useful digital heritage for the future.

References

Chawinga, W. D., & Zinn, S. (2020). Research data management at an African medical university: Implications for academic librarianship. The Journal of Academic Librarianship, 46(4), 102161.

Higgins, S. (2018). Digital curation: The development of a discipline within information science. Journal of Documentation, 74(6), 1361–1376. doi.org

Lee, C. A., & Tibbo, H. R. (2021). Research data curation and management bibliography. LLRX. llrx.com.

Madu, U. W., & Enyinnah, A. U. (2021). Research data curation and management: Emerging roles for academic libraries in Nigeria. In Libraries in the Era of Digital Technologies (pp. 348–363). Zeh Communications Limited.

Niu, J. (2016). Appraisal and selection for digital curation. International Journal of Digital Curation, 11(2), 65–75. doi.org

Tallman, N., & Work, L. (2022). Appraisal and selection for digital preservation: Framing criteria for selecting digital content. Pennsylvania State University Libraries. nathantallman.com

Whyte, A., & Wilson, A. (2010). How to appraise and select research data for curation. Digital Curation Centre. dcc.ac.uk