DATA COLLECTION AND REPOSITORY

DATA COLLECTION

Kumar (2019) has defined Data Collection as a logical procedure of gathering data for supporting analysis and decision making. It involves accumulating data about a specific subject of interest for comparisons and decision making. Data is the smallest unit of information that does not make sense on its own (Bawden & Robinson, 2015). It must be processed to make sense for analysis and decision making. Several techniques can be used to gather data. The techniques include structured or unstructured observations; face to face or virtual interviews which might involve structured, semi structured or unstructured questions; paper based or online forms questionnaires and surveys; focus group discussions; case studies; document analysis and experiments (Cresswell, 2018).  The collected data has to be accurate, complete and from trusted sources to qualify as a productive resource for decision makers and analysts.

REPOSITORY

Repositories become quite handy in handling collected data. A repository is a central location for managing, preserving, discovering, sharing and reusing collected data (Erima & Maseh, 2025). Repository ensures that collected data abides by the Open Archival principles which are being Findable, Accessible, Interoperability and Reusability (FAIR). The repository ensures increased donor trust, visibility and productivity of collected data preserved in the repository (Lee & Stvilia, 2017). There are two main types of repositories. The first one is the Institutional Repository which captures and preserves data for one single institution (Lee & Stvilia, 2017). An example would be a repository owned by Mzuzu University. Disciplinary Repository is the second one. This kind of repository focuses on a particular subject of interest (Sharma, 2022). An example of such a repository would be Information Science Repository. There are several software which are used to build repositories. Some of the repository software include Ivenio, Roar, Fedora, DSpace, Greenstone and EPrints.

RELATIONSHIP BETWEEN DATA COLLECTION AND REPOSITORY

Data collection and repository are inseparable because of the values they bring to each other. Here are some of the bonding values of the two concepts:

1.      Data Collection Feeds the Repository

Data collection provides for the content to be kept into the database. Without the data, the repository would be empty. Data collection provides the input for the repository.

2.      Repository Organizes Collected Data

The repository provides an interface for the collected data to be classified and indexed using data about data so that it should be discoverable whenever need arises.

3.      Repository Drives Data Preservation

The repository provides long term storage for evidential and historical data.

4.      Repository Provides Data Access

Repository enables data access by providing an interface for the stored data to be retrieved, shared and analyzed.

5.      Repository Provides Data Trustworthiness

Repository ensures there is preserved contextuality of preserved data by ensuring access security and audit trials to the stored data.

SUCCESSFUL DATA COLLECTION AND REPOSITORY REGIME

Chawinga and Zinn (2021) argue that positive attitudes, availability of skills for data collection and maintenance of a repository and its infrastructure and availability of policies for Open Access would facility successful regimes of Data Collection and Repository at a particular time and space.

CONCLUSION

Data Collection and Repository provide an intersection of effective and efficient information management. The intersection of the two concepts ensures efficient and effective data retrieval and trustworthiness. 

REFERENCES

Bawden, D., & Robinson, L. (2015). Introduction to information science. Facet Publishing.

Chawinga, W., D., & Zinn, S. (2021). Research data management in universities: A comparative study from the perspectives of librarians and management research data management in universities: A comparative study. International Information and Library Review, 53(2), 97–111. https://doi.org/10.1080/10572317.2020.1793448

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications.

Erima, J., A., & Maseh, E. (2025). Digital records curation practices in Institutional Repositories (IRs) at selected public universities in Kenya. Archives and Records, 46(2), 119–135. https://doi.org/10.1080/23257962.2025.2508700

Kumar, R. (2019). Research methodology: A step-by-step guide for beginners (5th ed.). Sage Publications.

Lee, D. J., & Stvilia, B. (2017). Practices of research data curation in institutional repositories: A qualitative view from repository staff. Plos One, 12(3), 1 – 44. https://doi.org/10.1371/journal.pone.0173987

Sharma, P. (2022). Digital repository: Need of modern libraries/emerging trends of modern libraries. International Journal of Research Publication and Reviews, 14(10), 22615 – 22617. https://www.journalcra.com/sites/default/files/issue-pdf/44086.pdf