Lecture 7 the nature of digital knowledge

Jashapara, Knowledge Management: An Integrated Approach, 2nd Edition, © Pearson Education Limited 2011

Slide 7.1

Analysis 1: Evidence and the Nature of Knowledge in the Digital Age

Topic: The Nature of Digital Knowledge

Topic Number: 7


Slide 7.2

LEARNING OBJECTIVES

• To explain the differences between ontology and taxonomy tools for organising knowledge

• To describe cognitive mapping and information retrieval tools for capturing knowledge

• To distinguish between different tools for evaluating knowledge

• To assess the different tools for sharing knowledge• To explain technologies for storing and presenting

knowledge


Slide 7.3

Questions to think about during the session

• What types of knowledge or information do I use in my everyday life?

• What types of technology do I use to manage this knowledge? You may wish to consider the types of technologies you use to capture, organise, evaluate, store and share knowledge


Slide 7.4

COMPONENT TOOLS TYPOLOGY

Figure 7.1 A typology of knowledge tools and component technologies


Slide 7.5

DIFFERENT FORMS OF KNOWLEDGE

Figure 7.2 Different forms of knowledge


Slide 7.6

ORGANISING KNOWLEDGE: ONTOLOGY & TAXONOMY

Figure 7.3 Ontology and taxonomies


Slide 7.7

ONTOLOGY GENERATION TECHNOLOGIES

• Manually• ‘Part of speech’ tagging• ‘Word sense disambiguation’• ‘Tokeniser’• ‘Pattern matching’• Semi-automatic generation with machine learning


Slide 7.8

INTEGRATING ONTOLOGIES

(see Ding & Foo, 2002)

Figure 7.4 Ontology integration techniques


Slide 7.9

CAPTURING KNOWLEDGECognitive Mapping Tools

• Used principally in mapping strategic knowledge

• Use ‘oval mapping’ technique in groups

• Develop concepts, links and clusters

• ‘Decision Explorer’ – can develop complex levels of analysis


Slide 7.10

CAPTURING KNOWLEDGEIndexing a Text Database

Figure 7.8 Indexing a text database


Slide 7.11

CAPTURING KNOWLEDGEInformation Retrieval Tools

• Desire for precision and recall• Differences between an author’s and user’s vocabulary• Use of inverted files for indexing text to speed up search –

assumes text as sequence of words – easy to compress• Develop inverted index including vocabulary search, list of

occurrences and processing of occurrences to solve phrases, proximity and Boolean operations

• Suffix Trees & Indicies – allows more complex queries. Sees text as long string with each position as a suffix

• Signature files – cuts text into blocks. Not as good as inverted index

• Manipulation algorithms such as BNDM and BMS for Boolean queries


Slide 7.12

CAPTURING KNOWLEDGERetrieval Process

Figure 7.9 Information retrieval process


Slide 7.13

CAPTURING KNOWLEDGEText Processing

• Lexical analysis to identify words from characters• Eliminating stopwords occurring frequently• Stemming e.g. Connect is stem for connected,

connecting, and connections• Full text indexing • Thesaurus index terms synonyms and near synonyms• Text compression to cope with information overload


Slide 7.14

CAPTURING KNOWLEDGESearch Engines: Crawler Indexer

Figure 7.10 Search engine: crawler-indexer architecture


Slide 7.15

CAPTURING KNOWLEDGESearch Engines: IR and the Web

• Centralised crawler-indexer architecture. Crawlers (software agents) traverse web sending back pages for indexing. Indexer – deals with query from user and new info. from crawler

• Decentralised gatherers-brokers architecture. Gatherers collect and extract indexing info. from lots of servers. Brokers provide indexing and query interface

• Metasearchers are Web servers that send query to several search engines

• Most common query on the Web is 2.3 words


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CAPTURING KNOWLEDGEPersonalisation

• Device provides needs and wants of consumer

• Solution lies in data mining in terms of analysing user’s clickstream and making recommendations

• Use of agents and machine learning


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EVALUATING KNOWLEDGECase-based reasoning

• Capture and store past experiences as organisational knowledge

• System searches for stored cases with similar profile to new problem

• Adds unsuccessful cases to aid learning• Built on artificial intelligence technology


Slide 7.18

EVALUATING KNOWLEDGEOLAP: On-line analytical processing

• Provides multidimensional analysis of data to allow user to see data in different ways using multiple dimensions

• Main technique is to rotate a data cube

• Also called ‘slice and dice’


Slide 7.19

EVALUATING KNOWLEDGEData mining

• Uses variety of neural network, decision trees and genetic modelling algorithms

• Use sophisticated data search capabilities using algorithms to discover patterns and correlations in vast amounts of data


Slide 7.20

SHARING KNOWLEDGEInternet/Intranet

• Share knowledge with knowledge providers across the world – some free

• Intranet provides same but restricted access from outside

• Uses HTML and XML – a metalanguage that allows definition of tags and allows distribution of knowledge to call phones, pagers and PDAs


Slide 7.21

SHARING KNOWLEDGEGroupware tools

• Allows to work on same document by multiple users• Maintain and update identical data on numerous PCs• Organising discussions• Storing information• Moving and tracking documents of groups• Preventing unauthorised access of data• Mobile use to access corporate network


Slide 7.22

SHARING KNOWLEDGE

• E-mail• Text-based conferencing• Yellow Pages• Computer-based training/e-learning• Security


Slide 7.23

WEB 2.0 PLATFORM

• Shift to dynamic social web applications• Network effects critical to their success• Provide customer services free – Google ($200bn),

YouTube ($1.6bn), Facebook ($50bn)• Indirect network effects from use of products or

services that have influence on related goods and services


Slide 7.24

TIPPING POINTWORD OF MOUTH EPIDEMICS

• ‘Connectors’ – social glue• ‘Mavens’ – information brokers on best deals etc.• ‘Salesmen’ – good at convincing you and getting you to

act• Amazon is reliant on ranking of reviewers to develop

trust with customers• Six degrees of separation


Slide 7.25

WEB 2.0 PLATFORM

Figure 7.11 Web 2.0 platform tools


Slide 7.26

BLOGS

• Blogs – adding thoughts or diary of events• Podcasts – audio blogs• Vlog – video blog• Trackbacks – allows bloggers to see who’s linking to

them• Can act as alternative to face-to-face meetings to

engage in problem solving• Engage with customers across boundaries• Twitter – micro-blogging site


Slide 7.27

SYNDICATION & RSS FEEDS

• Information from articles and photos repackaged for different customers

• RSS (Really Simple Syndication) format to publish frequently updated content on websites

• Organisations can place feeds showing latest offerings or consumer information such as traffic news or weather forecasts

• RSS viral distribution engine for bloggers – receive new material posted by favourite bloggers


Slide 7.28

MASHUPS

• Allows content from different sources to combine with applications for different business processes

• E.g. Getting insurance quote from website• E.g. Starbucks helps customers locate nearest café

once they’ve entered postcode• Information from external sources can be inaccurate

or may change significantly in future; even close down

• Prone to threats from malware


Slide 7.29

WIKIS

• Web pages that can be viewed and modified by anyone

• Allows to create or change web content• Places power and freedom in hands of users rather

than external ‘expert’• Works in progress on virtual ‘white boards’• Agendas and minutes can be placed on wikis• Can be open to manipulation and vandalism• Maintenance can be time-consuming


Slide 7.30

ONLINE SOCIAL NETWORKS

• Individuals interact with others in community• Social network sites (SNS): Facebook, MySpace,

LinkedIn, Friendster• SNS tend to support pre-existing relationships rather

than new ones• Benefit from social capital and self-presentation• Risk over privacy from third party securing personal

information• Allows interaction with different people in network


Slide 7.31

3-D VIRTUAL WORLDS

• Computer-simulated worlds where users interact in real time through ‘avatars’

• Avatars are 3-D electronic cartoons of users; form of alter ego

• Second Life has over 15m users and internal currency of Linden dollars (L$)

• Conduct meetings, workshops and recruitment• Multinationals such as IBM, Dell, Ericsson, Bain• Strathclyde and Coventry Universities bought islands


Slide 7.32

STORING KNOWLEDGEData Warehouse

• Database with query and reporting tools• Stores current and historical data from internal and

external sources• Data mart – subset of data warehouse which contains

summarised or highly focused data for certain users


Slide 7.33

PRESENTING KNOWLEDGEVisualisation

• Modelling – way of representing objects e.g. journal covers, weather maps, flows of citations

• Rendering – makes computer generated image look like photograph e.g. texture mapping

• Virtual reality


Slide 7.34

Reading and preparatory work to be done

Read:• Jashapara, A. (2011) “ Knowledge Management:

An Integrated Approach” Pearson Education, Chapter 7

Work to be done before the seminar:• Carry out all the reading above• Answer the questions on the hand-out• Bring your work to the seminar

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Slide 7.35

Essential work for next week

• Please consult the OLE for details of:– Essential readings*– Seminar/workshop preparation work*– Recommended further readings– Any additional learning

* Essential readings and preparation work must always be completed in time for the next session

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Lecture 7 the nature of digital knowledge

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Transcript of Lecture 7 the nature of digital knowledge