Using and Reusing data-Summary

 

Using and Reusing data-Summary

Borgman (2015) defined using and reusing data as the process of applying collected information for decision-making, research, problem-solving, and innovation, while also allowing existing data to be used again for purposes different from the original intention. In modern organisations, academic institutions and governments, data is considered an important asset as it supports evidence-based planning hence improving efficiency. Data use involves analysing and interpreting information to meet specific objectives while data reuse involves accessing previously collected datasets for secondary analysis, validation of results, or new research studies (Johnson, 2017).

The reuse of data has become increasingly important in research and information management because it helps save time, reduce research costs and avoid duplication of effort. Researchers can reuse data from earlier studies to compare findings, identify trends or answer new research questions without repeating data collection processes. Data reuse also promotes transparency and accountability because other researchers can verify and replicate findings, which improves the reliability and credibility of research outcomes (Johnston, 2017). In scientific research, governments, healthcare, education, and business sectors, reused data contributes to innovation and informed policy development.

Cox and Tam (2018) noted that proper data management practices are essential for data to be effectively used and reused. Data should be carefully organised, accurately documented, securely stored and made accessible to authorised users. Metadata, which describes the content, structure and context of data, is critical as it helps users understand how the data was collected and how it can be reused appropriately (Cox & Tam, 2018). Many institutions are adopting digital repositories and cloud-based systems to preserve data and improve accessibility for future use (Borgman,2015).

Despite the benefits, several challenges affect data use and reuse. These include poor data quality, lack of standard formats, inadequate technological infrastructure and limited technical skills which can reduce the effectiveness of reused data (Kim and Stanton, 2016). Ethical and legal concerns such as privacy, confidentiality, and intellectual property rights also influence the willingness of researchers and organisations to share data openly. In some cases, researchers fear misuse of their data or lack of recognition when others reuse their work (Wilkinson et al, 2016).

To address these challenges, organisations and institutions should implement strong data governance policies, encourage open data sharing and provide trainings in research data management. International guidelines such as Findability, Accessibility, Interoperability and Reusability (FAIR principles) are widely recommended to improve the quality and usability of data over time (Wilkinson et al., 2016). Therefore, institutions need to maximise the value of data and support sustainable research and development in order to promote effective data management and sharing practices.

Summary of using and reusing data

References

Borgman, C. L. (2015). Big data, little data, no data: Scholarship in the networked world. MIT Press.

Cox, A. M., & Tam, W. W. T. (2018). A critical analysis of lifecycle models of the research process and research data management. Aslib Journal of Information Management, 70(2), 142–157.

Johnston, L. R. (2017). Curating research data: Practical strategies for your digital repository. Association of College and Research Libraries.

Kim, Y., & Stanton, J. M. (2016). Institutional and individual influences on scientists’ data sharing practices. Journal of Computational Science Education, 7(1), 47–56.

Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J. W., da Silva Santos, L. B., Bourne, P. E., et al. (2016). The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 3(1), 1–9.