Wednesday, May 13, 2026

SELECTION AND APPRAISAL OF DATA

Digital Curation Cycle
Digital Curation Life Cycle Diagram

INTRODUCTION

The National Archives and Records Administration of the United States of America (NARA) (2020) has defined appraisal as the process of determining the value of records to determine the preservation period of the resource. The value can be temporal or permanent. It can also be administrative, legal, research or historical. Despite an explosion in generation of information, Yeo (2018) envisioned a future where all records were to be preserved for eternity as an aftermath of digital curation reality. Nonetheless, Sucha-xaya (2024) argues that there is a need to appraise records and archives to ensure efficient and effective records and archives management whilst offering effortless search and retrieval regimes of the preserved resources. It should be noted that appraisal is conducted during the inception and life of borne resources. Review of the appraised resources can be conducted to weed those resources which no-longer possess value for preservation or to ascertain the currency of the file format for migration if necessary to ensure continued access of the preserved resources (Niu, 2014).

METHODS OF SELECTING RESOURCES

There are three methods which can be used for selecting resources for curation. The first one is Statistical Sampling Method. The method involves sampling to select resources for curation. Two kinds of sampling can be used to select resources for digital curation. The first one is Systemic Sampling that selects every nth item from a population and the second one is random sampling that selects items from a population with equal probability regardless of their values. The second method is Risk Analysis. The method involves assessment of the kinds of risks that could possibly happen to digital resources, as well as the probability and consequence of each risk. Commonly mentioned risks during selection processes include risk of obsolescence of file format and storage media, risk of loss caused by not preserving the digital resources and by storing resources in an unsafe area. The third method for selection of resources for digital curation is appraisal which involves ascertaining the value of resources that are to be considered for digital curation.

APPRAISAL ASPECTS

Appraisal has got three main aspects. One of such aspects is Objects of Appraisal. The objects include context of resources qualifying for curation also known as macro-appraisal (Shepherd & Yeo, 2003); the appraisal of the resources also referred to as micro-appraisal which looks at content, physical conditions and technical characteristics of the resources with an eye on curation feasibility and cost; significant properties of the resources; metadata and documentation (Niu, 2014).

The second appraisal aspect is Appraisal Criteria which has such evaluation factors as mission alignment, value of digital resources, cost and feasibility of the resources to be part of a repository despite being resources of value (Niu, 2014). 


The final appraisal aspect is Curators Decisions which involves deciding on resources to be included for curation, retention period of curated resources, decommissioning of resources from curation after reviews and format migration for perpetual access of curated resources whenever necessary (Niu, 2014).


REFERENCES

National Archives and Records Administration of the United States of America (NARA). (2020). Federal records management: Appraisal policy of the national archives. NARA. https://www.archives.gov/records-mgmt/scheduling/appraisal#appendix1.

Niu, J. (2014). Appraisal and selection for digital curation. The International Journal of Digital Curation, 9(2), 65-82. https://doi.org/10.2218/ijdc.v9i2.27272

Shepherd, E. & Yeo, G. (2003). Managing records: A handbook of principles and practice. Facet.

Sucha-xaya, N. (2024). Finding values, building communities: development of an archival appraisal system for the Thai public sector. Archival Science, 24, 329-349. https://link.springer.com/content/pdf/10.1007/s10502-024-09433-1

Yeo, G. (2018). Can we keep everything? The future of appraisal in a world of digital profusion. In: C. Brown (Ed.), Archival futures, pp 45–64. Facet. 

Wednesday, May 6, 2026

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


Tuesday, December 16, 2025

INFORMATION LITERACY MODEL - THE BIG6

INTRODUCTION

A model can be defined as a philosophical basis that uses well-grounded ideas to explain a phenomenon like information literacy.  Information literacy models serve as guidelines for inculcating information literacy skills to individual in formal and informal settings.

There are six information literacy models. The models are as follows:

1.     Big6 Information Skills developed by Eisenberg and Berkowitz in 1990

2.     Seven Pillars of Information Literacy developed by SCONUL Advisory Committee in 1999

3.     Pathways to Knowledge developed by Pappas and Tepe in 2002

4.     PLUS model developed by Herring in 1996

5.     Seven Faces Information Literacy developed by Bruce in 1997

6.     Information Search Process Model developed by Kuhlthau in 2004

BIG6 INFORMATION SKILLS

The model is one of the widely used information problem solving skill which is used by individual of all ages. The model was developed by Mike Eisenberg and Bob Berkowitz in the United States of America in 1990. The information inquiry involves information search with systematic use of technological tools to find, use, apply and evaluate information for specific needs and tasks. The use of technology in information searching makes the model relevant in this era of digital explosion.

BIG6 INFORMATION SKILLS STEPS

1.     Task Definition

An individual defines a problem from an information point of view. The person understands that there is need of information to solve the problem. The individual understands the need to search for the information to solve the problem.

2.     Information Seeking Strategies

Upon defining an information problem, the individual singles out information sources which are relevant in bringing about the needed information.

3.     Locating and Access

The individual locates the required information from print, non-print and electronic resources and accesses the specific information for retrieval.

4.     Use of Information

The individual engages with the selected information resources to check their relevance in resolving the information gap. Once satisfied of information resources trustworthiness, the individual then employs skills to use the information.

5.     Synthesis

The individual integrates the information with his or her own knowledge to bring about new form of the retrieved information.

6.     Evaluation

The individual assesses if the information problem solving processes has brought forth the desired information in resolving a perceived information gap.

Below is a figure summarizing the process. 

The picture illustrates that each of the stages in the information problem inquiry is iterative in nature until the relevant information is found to fill the information gap.

Tuesday, December 2, 2025

INFORMATION LITERACY

 Definition

It is one’s ability to identify an information gap, find, evaluate and use the information effectively and efficiently whilst following ethical obligations of using such information in resolving the information gap (ALA, 1989).

Importance

1.      Independent learning

It enables learners to learn new things with little or no guidance.

2.       Life Long Learning

It helps individual to keep on updating their mental faculties with regards to developments in fields of their interests.

Characteristics of an Information Literate Individual

The following behaviour is evident in an information literate individual:

1.       Gauging the right quantity for the information need.

2.       Locating and retrieving the right information with ease within the shortest time span.

3.       Evaluating the credibility of the retrieved information sources

4.       Making connections between ideas and new concepts for assimilation

5.       Citing and referencing consistently when using borrowed information to fulfill a perceived purpose.

Information Literacy Competency Standards

These are frameworks that are used to assess information literacy skills of individuals with the use of outcomes. The standards are as follows:

1.       Nature and Quantity of Information

The individual is able to identify the type of exercise at hand thereby identifying the nature and quantity of information needed.

2.       Accessing Needed Information

The person is able to locate, find and retrieve the needed information with much ease and within a limited time span.

3.       Evaluation

The individual is able to assess the credibility of the retrieved information using an established criterion.

4.       Use

The person is able to apply the information to fulfill a particular identified purpose.

5.       Ethical Use

The individual cites and references the borrowed information since the person understands the legal, economic and moral value of information.

Tuesday, November 11, 2025

INFORMATION SEEKING AND MYTHS

For decades, information professionals were concerned about the systems that had to be set in place for a researcher to easily find information being searched to resolve a particular information gap. The concern was to provide for the information which would be sought after by the users of a particular library setting without understanding the needs and information seeking behaviours of the patrons. Such an arrangement brought about irrelevant information resources that had to be weeded or information systems that had to be redesigned. We are now in the era where patrons’ needs and information seeking patterns have to be understood before developing any information system or purchasing an information resource. The centre has now shifted from systems to the user of the systems. The aim is satisfy the needs and wants of patrons being served.

Serving users with relevant information has got some myths which an information professional has to aware of to avoid unprofessional conduct. The myths include more information is always better, objective information can be transmitted out of context, only formal sources are essential, there is relevant information for every need, it is always possible to make information available or accessible, individual situations and context can be ignored, only objective information is valuable.

SELECTION AND APPRAISAL OF DATA

Digital Curation Life Cycle Diagram INTRODUCTION The National Archives and Records Administration of the United States of America (NARA) (...