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Vol.1 , No. 1, Publication Date: Aug. 8, 2014, Page: 1-5
. The matrix is a four-quadrant representation for a visual mental model of how one might think about the complexity and variety that make up information attributes for assessing the competing interests and goals of information oriented problem identification, specification and definition. The matrix is offered as a tool for managers and researchers seeking a framework to clarify understanding of problem sets in the domains of data analytics and information retrieval, further classified as knowledge management and knowledge discovery. The goal of the matrix is to serve as a reference model for improving problem definition and goal prioritization in the pursuit of information oriented applications.&picture=http://www.aascit.org/aascit/decorators/img/journal/912.jpg)
| [1] | Harvey Hyman, Harvey Hyman, Florida Polytechnic University, 4700 Research Way, Lakeland, Florida 33805. |
This paper proposes a matrix for an information science framework for identifying and evaluating goals and objectives in the information problem space. The framework offers a model to represent four constructs within information science: knowledge discovery, knowledge management, data analytics and information retrieval. As a conceptual framework, the model supports the goals of understanding, evaluating and combining the four identified constructs into an integrated information science matrix (ISM). The matrix is a four-quadrant representation for a visual mental model of how one might think about the complexity and variety that make up information attributes for assessing the competing interests and goals of information oriented problem identification, specification and definition. The matrix is offered as a tool for managers and researchers seeking a framework to clarify understanding of problem sets in the domains of data analytics and information retrieval, further classified as knowledge management and knowledge discovery. The goal of the matrix is to serve as a reference model for improving problem definition and goal prioritization in the pursuit of information oriented applications.
Keywords
Information Science Model, Information Retrieval, Data Analytics, Knowledge Discovery, Knowledge Management
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