Chapter 1: Introduction to Knowledge Identification - Coggle Diagram
Chapter 1: Introduction to Knowledge Identification
Data Information Knowledge
Information is a subset of data, only including those data that possess context, relevance and purpose.
e.g: Information involves manipulation of raw data.
A justified true belief (Nonaka and Takeuchi)
Knowledge is at the highest level in a hierarchy with information at the middle level, and data to be at the lowest level
Components of Knowledge
Ground Truth and Truth Maintenance
Experiential Knowledge and Knowledge Scripts
Values, Assumptions and Belief
CATEGORY OF KNOWLEDGE
Unwritten, unspoken, and hidden vast storehouse of knowledge
e.g: Like the submerged part of an iceberg it constitutes the bulk of what one knows, and forms the underlying framework that makes explicit knowledge possible.
Everything that you can read.
e.g: manuals, documents, how-to videos, etc
Types of Knowledge:
A set of particular and objective facts about an event or simply structured records of transaction.
e.g: Data represents raw numbers or assertions.
The Five C’s
Methods of creating information by adding meaning to data.
It was proposed by Davenport and Prusak
for converting data to information.
5C of data Transformation
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Definition: Performing the activities involved in discovering, capturing, sharing, and applying knowledge to enhance, in a cost-effective fashion, the impact of knowledge on the unit’s goal achievement.
leveraging core business competencies.
accelerating innovation and time-to-market.
innovating and delivering high-quality products.
improving cycle times and decision-making.
strengthening organizational commitment.
building sustainable competitive advantag.
(Davenport and Prusak 1998).