USING AND REUSING DATA



Data has become one of the most valuable resources in modern research and knowledge production. However, the true value of data is not realized simply through collection, but through its continued use and reuse over time. Within the field of data curation, the processes of organizing, preserving, documenting and maintaining datasets are essential for ensuring that data remain accessible and meaningful for future applications (Wilkinson, 2016). Effective data curation therefore plays a central role in enabling sustainable data reuse across disciplines.

Using data refers to the direct application of datasets for research, decision making or problem solving. Reusing data on the other hand involves employing existing datasets for new purposes beyond the original study or project. Data reuse has become increasingly important because it saves times, reduces research costs and minimizes duplication of effort. According to Faniel and Yakel (2017), reusing well-curated datasets can significantly improve research efficiency and encourage scientific collaboration. Researchers are able to validate research findings, conduct comparative analyses and generate new knowledge without repeatedly collecting similar information.

The growing emphasis on open science has further increased the importance of reusable data. Curated datasets stored in digital repositories can support interdisciplinary research and innovation by allowing scholars from different fields to access and interpret shared information (Mosha & Ngulube, 2026). Wilkinson (2016), highlight the importance of the FAIR principles which state that data should be Findable, Accessible, Interoperable and Reusable. These principles have become widely accepted as a foundation for responsible data management and long-term usability.

Despite these benefits, data reuse presents several challenges. One major issue is the lack of adequate metadata and documentation. Without clear descriptions of how data were collected, processed and structured, secondary users may struggle to interpret datasets correctly (Seaton et al., 2023). Poor data quality and inconsistent formatting can also limit reuse potential. Ethical and legal concerns further complicate data sharing especially when datasets contain sensitive or confidential information (Chawinga & Zinn, 2019). Researchers and institutions must therefore balance openness with privacy protection and intellectual property considerations.

To maximize the value of reusable data, several best practices should be followed. First, researchers should create detailed metadata and documentation throughout the data lifecycle. Second, datasets should be stored in trusted digital repositories that support long-term preservation and accessibility. Third, adopting standardized file formats and data management frameworks improves interoperability between systems and disciplines. Finally, institutions should invest in training data curators and researchers in proper data management practices to strengthen the overall culture data stewardship (Wilkinson, 2016).

In conclusion, using and reusing data are critical components of modern data curation. Effective curation enhances the long-term value, reliability and accessibility of datasets allowing them to support future research and innovation. As the volume of digital information continues to expand, institutions and researchers must prioritize sustainable data management practices that promote responsible and meaningful data reuse.

https://www.youtube.com/watch?v=6-LeIwUhRKo

 

REFERENCES

Chawinga, W. D., & Zinn, S. (2019). Global perspectives of research data sharing : A systematic literature review. Library and Information Science Research, 41(April), 109–122. https://doi.org/https://doi.org/10.1016/j.lisr.2019.04.004

Faniel, I. M., & Yakel, E. (2017). Practices Do Not Make Perfect Disciplinary Data Sharing and Reuse Practices and Their Implications for Repository Data Curation. In L. R. Johnson (Ed.), Curating Research Data, Volume 1: Strategies for your Digital Repository (Vol. 1, pp. 103–126). Association of College and Research Libraries.

Mosha, N. F., & Ngulube, P. (2026). The utilisation of open research data repositories for storing and sharing research data in higher learning institutions in Tanzania. 44(8), 566–580. https://doi.org/10.1108/LM-05-2023-0042

Seaton, K.-L., Laužikas, R., Mckeague, P., & Almeida, V. M. De. (2023). Understanding Data Reuse and Barriers to Reuse of Archaeological Data . A quality-in-use methodological approach.

Wilkinson, M. D. (2016). Comment : The FAIR Guiding Principles for scienti fi c data management and stewardship. 1–9. https://doi.org/10.1038/sdata.2016.18

 

Comments

Post a Comment

Popular posts from this blog

SELECTION AND APPRAISAL OF DATA

Image
Selection and appraisal of data are central activities in data curation because they determine the quality, reliability and long-term value of data used for research, decision making and preservation (Niu, 2014) . In data curation, selection refers to the process of identifying data that should be retained, preserved or shared while appraisal involves evaluating the significance, authenticity, usability and relevance of data. These processes are important because not all data generated during research have equal value and institutions often face limitations related to storage capacity, funding and long term preservation resources. Effective selection and appraisal therefore ensure that valuable datasets are maintained for future access and reuse while redundant or low quality data are excluded (Harvey, 2008) . Data curation scholars emphasize that appraisal should begin early in the research lifecycle rather than after data creation. According to Yakel (2007), proactive appraisal hel...
Read more

DATA CURATION PRESERVATION ISSUES (ORGANIZATIONAL ISSUES)

Image
  Digital curation has become a critical function in libraries, archives, research institutions and government organizations seeking to preserve digital assets for long-term access and use (Akers & Doty, 2013) . While technological challenges often receive significant attention, organizational issues are equally important determinants of successful digital preservation. Effective digital curation requires not only technical infrastructure but also strong governance structures, adequate resources, skilled personnel and institutional commitment (Erima & Maseh, 2025; Zareef & Jabeen, 2025b) . Without these organizational foundations, preservation initiatives may struggle to achieve sustainability and long-term impact. One of the major organizational challenges involves policy development and implementation. Digital preservation policies provide a framework for managing digital assets throughout their lifecycle including acquisition, storage, access and disposal. However, m...
Read more

DATA COLLECTION AND REPOSITORIES SUMMARY

Image
          Data collection and repositories are essential components of modern research and information management. Data collection refers to the systematic process of gathering, measuring and analyzing information to answer research questions, test hypothesis or support decision making. Depending on the nature of the study and type of data required, researchers use surveys, observations, interviews, experiments and document analysis as methods of data collection (Leavy, 2023) . Effective data collection is essential because the quality, reliability and validity of research findings largely depend on the accuracy and consistency of collected data (Taherdoost, 2022) . In the digital age, the rapid growth of scientific and institutional research has increased the need for proper data storage, preservation and sharing. This has led to the development of research data repositories which are digital platforms designed to store, manage, preserve and dissemina...
Read more