Supporting Collaboration

Managing Information Resources

Data, Information and Knowledge Data

Facts devoid of meaning or intent e.g. structured data in DB

Information Data that has meaning (data in context) Content: term for the Web age

Information presented electronically in a variety of media: charts, text, voice, sound, graphics etc.

Knowledge Information with direction or intent

The Three-level Database Model The three-level database model

Level 1: the conceptual level Containing the various "user views" of the corporate data that

each application program uses Level 2: the logical level

Logical views of an organizations data as under the control of the DBAs

Level 3: the physical level Specifying the way the data is physically stored

Advantages Level 2 absorbs changes made at level 3 Data only needs to be stored once in level 2

Different programs can draw on it and vary the relationships among the data

Getting Corporate Data into Shape The Problem: management can not get consistent

view across the enterprise Incompatible data definitions from application to application

The Cause: an application-driven chaos Getting applications running as quickly as possible

The Solution: a data-driven approach ERP is one of the main driving force for getting data into

shape in many companies

What is Data Warehouse?

“A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management’s decision-making process.”—W. H. Inmon

Data Warehouse vs. Heterogeneous DBMS Traditional heterogeneous DB integration: A query driven

approach Build wrappers/mediators on top of heterogeneous databases

Data warehouse: update-driven, high performance Information from heterogeneous sources is integrated in advance

and stored in warehouses for direct query and analysis

Why have a separate data warehouse Promote the high performance of both systems An OLAP operation needs no concurrent transaction support Structures, content and uses of data are different in two systems

Document Management

Estimated that 90% of an organization’s information is in documents rather than structured databases

Types of Documents Contracts and Agreements Reports Manuals and Handbooks Correspondence Memos Drawings and Blueprints …

Content Management

Traditional “home-grown“ content management The Webmaster was the

publishing bottle neck

3 phases of content management life cycle Input-process-output

XML & Web Content Management XML is used to put tags on data giving that data

meaning Computers use the meanings to manipulate the data

and perform work

Use of XML moves Web content from being in a human-only readable format to being in a computer-readable format The content can be passed to back-end transaction

processing systems and cause an action to take place e.g. ordering a book or configuring a new computer Manipulating the content to work with transaction applications

– the basis for e-commerce

Managing Operations

Main Shift in the Operations Viewpoint

What’s New in Operations?

Companies have "cleaned their operational house" Y2K problem moved company from a survival mode to a

planning mode More operations managers are managing outward

CIOs does not relinquish responsibility for operations Ensure their people are properly managing relationships

Operations are being "simplified" Centralizing applications in one place rather than distribute

them on PCs Server based computing (thin client)

Certain operations are being offloaded e.g. Microsoft offloaded webcasts to Netpodium

Outsourcing IS Function

Outsourcing means turning over a firm's computer operations, network operations, or other IT function to a vendor for a specified time

The focus of CIOs in operations is changing In the past, ensuring they had the in-house expertise

to keep systems and networks up and tuning Now, determining where best to perform the various

kinds of operations In house or with a third party and manage it accordingly

The Driving Forces Behind Outsourcing 70% of US economy had global competition in

1970s Companies had to focus on core business, which led

to huge amount of merger and acquisition activity Companies were priced based on their shareholder

value

Focus and value Management must stress value, they must consider

outsourcing in all their nonstrategic functions

Outsourcing

Transitional outsourcing Best-of-breed outsourcing Shared services Business Process Outsourcing (BPO) E-business outsourcing Utility Computing

The Balance Between Security and Risk Information Security is a balancing act between

ease of access to information and protecting that information from increasing threats

The Information Security Manager must Constantly bear in mind the organization's appetite for

risk Assess where the "appropriate" balance lies Be prepared to press their case "strenuously" when

they believe the risk is not within acceptable bounds.

Security's Six Pillars

A secure system should provide: Nonrepudiation – a transaction cannot be denied by any of

the parties to it Confidentiality – data or services are protected from

unauthorized access Integrity – data or services are delivered as intended Assurance – (authentication) the parties to the transaction

are who they say they are Availability - the system will be available for legitimate use;

no DOS. Auditing – the system tracks activities within it at levels

sufficient to reconstruct them

Technologies for Developing Systems

The Evolution of System Development

2000

1980

1950

1970

1990

1960

High-levellanguages

Data structures,algorithm, objects

Modules, systemorganization

Architecturalelements

Software architecture

NATO SE conference

Programming-in-the-large

Software development environments

Subroutines

Separate compilation

Integrated product linesComponent-based systems

Information hiding

InheritanceAbstract data typesobject

s

PackagesRDBMS & SQL

Sequence of instructions

Web services & SOA…

The Spiral Model

Structured System Development Some elements of the structured system

development Hand coding in third generation language "Structured programming" development methodology DBMS Development of mostly mainframe applications Various automated, but not well integrated software

tools User participation mainly in require definition and

installation phases

4th Generation Language (4GL) A programming language closer to human

languages than 3GL 4GL specifies the purpose without details on

procedures E.g. SQL

SELECT NAME, SCORE FROM STUDENT

Internet-based Systems

Internet-based systems must be: Scalable Reliable Integrated with systems of customers or business

partners

Three cornerstones for Internet-based systems Application servers Java Web service

System Integration

Three traditional integration approaches DBMSs

A data-centered approach, allowing applications to share data stored in a single or distributed database

Enterprise Resource Planning (ERP) An application-centered approach, all applications come

from a single vendor and are specifically designed to communicate with each other

Middleware A third-party approach, applications communicate with

each other through a third-party translation software

The Traditional Project Management Triangle The three competing

constraints Increased scope typically

means increased time and increased cost

A tight time constraint could mean increased costs and reduced scope

A tight budget could mean increased time and reduced scope

QUALITY

SCOPE

TIME

COST

Supporting Decision Making

Technologies Supporting Decision Making Computer technologies that support decision

making Decision support system (DSSs) Data mining Executive information systems (EISs) Expert systems (ESs) Agent-based modeling

Multidisciplinary foundations for DS technologies Database research, artificial intelligence, statistical

inference, human-computer interaction, simulation methods, software engineering etc.

DSS Architecture (1)

Knowledge Discovery (KDD) Process Data mining—core of

knowledge discovery process

Data Cleaning

Data Integration

Databases

Data Warehouse

Task-relevant Data

Selection

Data Mining

Pattern Evaluation

Architecture: A Typical Data Mining System

data cleaning, integration, and selection

Database or Data Warehouse Server

Data Mining Engine

Pattern Evaluation

Graphical User Interface

Knowledge-Base

DatabaseData

WarehouseWorld-WideWeb

Other InfoRepositories

Architecture of an ES

InferenceEngine

KnowledgeBase

User

Interface

Description of a problem

Advice and explanation

User

Knowledge Representation

In AI, the primary aim of knowledge representation is to store knowledge so that programs can process it and achieve the verisimilitude of human intelligence The representation theory has its origin in cognitive

science

Knowledge can be represented in a number of ways Case-based reasoning Artificial neural networks Stored as rules

Agent-based Modeling

Simulate the behavior that emerges from the decisions of a large number of distinct individuals Computer generated agents, each making

decisions typical of the decisions an individual would make in the real world

Trying to understand the mysteries of why businesses, markets, consumers, and other complex systems behave as they do

Supporting Collaboration & Knowledge Work

Organization Structure---Demise of Hierarchy

Command-and-control hierarchical bureaucracies

Coordinated, collaborative self-managed groups

Characteristics of Groups (1)

Collaboration is all about getting work done in a group rather than individually

Characteristics that differentiate groups include: Membership

Some groups are open, some are closed. Interaction

Some groups are loosely coupled (salespeople with their own territories)

Others work closely together (project team)

Characteristics of Groups (2)

Hierarchy Some groups have a chain of command (tiers of committees)

Location Some members are co-located, some are dispersed

Time Some groups are short-lived, some are ongoing Some group member works full time on the group's work,

other groups only require intermittent work

These characteristics illustrate that providing computer-based support for groups is not uniform From inter-company groups to global teams

Community of Practice (2)

Three characteristics of CoPs are crucial The domain

An CoP has an identity defined by a shared domain of interest.

The community CoP members engage in joint activities and discussions,

help each other, and share information The practice

Members of a community of practice are practitioners. They develop a shared repertoire of resources: experiences, stories, tools, ways of addressing recurring problems—in short a shared practice

Group Activities and Supporting Tech Group activities

Communication and interaction Communication: transmitting information from one person to

others Interaction: back-and-forth communication over time

Decision making and problem solving Group members reach a decision or form a consensus

Supporting tech Communication: email, office systems Collaboration: CSCW (Groupware) Decision making: GDSS

The CSCW Matrix

Companies Want to Manage Knowledge (1) Controversial views on knowledge

management Knowledge can be captured in computer systems Knowledge can not be captured in a machine, it

only exists inside a person’s head Information VS. knowledge Knowledge management is a misnomer

Knowledge cannot be managed, but only shared The more people are connected, the more they exchange

ideas, the more their knowledge spreads and can thus be leveraged

Companies Want to Manage Knowledge (2) Tacit and explicit knowledge

Tacit knowledge exists within a person's mind and is private and unique to each person

Explicit knowledge has been articulated, codified, and made public

Effective knowledge management requires transferring knowledge between these two states Nurturing, cultivating and harvesting knowledge Knowledge management knowledge sharing

CoPs and Knowledge Management Traditional knowledge management captures

only the most explicit forms of knowledge Tacit knowledge is more related with day-to-day

activities and how work is done in practice

Communities are the critical building blocks of a knowledge-based company People, not processes, do the work Learning is about work, work is about learning, and

both are social Organizations are webs of participation