Vol. 1 No. 2 (2016) 

Resource Description and Access (RDA): enhancing information discovery through effective description

Catherine Thuku
Library of Congress, Nairobi

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Rationale of Study – Resource Description and Access (RDA) is the new cataloguing content standard providing instructions and guidelines for creating effective bibliographic data for information resources in all formats of content and media. It replaces the Anglo-American Cataloguing Rules, 2nd edition (AACR-2). This paper seeks to draw the attention of librarians to RDA as a means of promoting its application. 

Methodology – This study was conducted as a literature review analysing the origins and rationale of RDA, its structure, benefits, relationship with AACR-2, and how to implement it in libraries in developing countries such as Kenya. 

Findings – RDA is founded on established cataloguing principles, standards and models. It is schema-neutral and can work with the existing cataloguing formats such as Machine-Readable Cataloguing (MARC), formats for interchange of data over the Internet such as Extensible Markup Language (XML) and other structures that may be developed in the future. It is user-focused utilising terminology that is widely used and describes resources in a way that promotes specific user tasks - find, identify, select and obtain information resources as a way of enhancing their use. 

Implications – This paper can be used by librarians to understand the benefits of RDA as a cataloguing platform and adopt the same to enhance the findability of information resources through effective description and access.  

Originality – Although this paper relies on existing scientific literature, it provides new perspectives for the Kenyan context. To that extent, it is original. 


Resource Description and Access, descriptive cataloguing, metadata, Functional Requirement of Bibliographic Records, cataloguing



A Conceptual Data Mining Model (DMM) used in Selective Dissemination of Information (SDI): a case study of Strathmore University library 

Mr. Ambayo Jackson Alunga
Assistant Lecturer, The Technical University of Kenya
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Prof. Ismail Ateya Lukandu
Academic and Research Director, Strathmore University

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Rationale - The process of locating and acquiring relevant information from libraries is getting more complicated due to the vast amount of information resources one has to plough through. To serve users purposefully, an academic library should be able to avail to users the tools and services that lessen the task of searching for information. 

Design - The research proposed a two-phase data mining through analysing the access behaviour of users. In the first phase, the Ant Colony Clustering Algorithm was used as the data mining method and separated users into several clusters depending on access records used. The clusters were in the form of course groupings. Users who have similar interests and behaviour were collected in the same cluster. In the second phase, the user records in the same cluster were analysed further. The second phase relied on association which was used to discover the relationship between users and information resources, users’ interests and their information access behaviour. 

Findings - It was ascertained that although users were able to locate and retrieve the information they needed, it was not up to the degree of satisfaction they expected. Furthermore, it took them some time to acquire the information. Using data mining together with selective dissemination of information would enable users to access relevant information without promptly thus saving time and other resources.  

Practical implications - The mining of user data within library databases would facilitate a better understanding of user needs and requirements leading to the development and delivery of specialised and more fulfilling services. 

Originality - The proposed DMM model is original as it is one of a kind that suggests integrating SDI with data mining in libraries. 


Data mining, bibliomining, Selective Dissemination of Information (SDI), information needs, knowledge discovery in databases (KDD), academic libraries 



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