What is MIS?(And How We Figured It Out)

A definition of the MIS field

MIS 696a/797 Fall 1998

Agenda

The ProcessThe Areas of MISIndividual Paper PresentationsLessons Learned DiscussionDinner

The Process

Brainstorming Session I via GroupSystemsFaculty Survey and InterviewsResearching areas of MISBrainstorming Session II: MIS areas

From areas to categories Splitting up the work

Which paper to choose?

Which Paper to Choose?

Backtrack through paper referenceUse overview booksWeb siteswebofscience.comInterviews

The Seven Pillars of MIS

A Breakdown of the MIS Field

MIS Foundations & Methodology

Science & Scientific PracticeTheoretical Background

Systems Theory Cognitive Science Social Psychology etc.

Methodologies

Database Technology

Physical Logical Conceptual Application

Modeling Applications

Operational

Special Applications (MM, web, temporal/ spatial)

Decision Support

Key Researchers• Peter Chen• E. F. Codd• Bill Inmon

• Bhawani Thuraisingham• Arie Segev• S. B. Navathe

Storage Structure

DBMS

Query Processing

DBMS Interoperability

Metadata Management

Transaction Management

Key Researchers• Jennifer Widom• Jeff Ulmann• Hector Garcia Molina

• Benjamin Wah• Richard Snodgrass• Umesh Dayal

Software Development and Engineering

Models (waterfall, et al)System engineeringWorkflow management/Process modelingBusiness Process ReengineeringCASE tools

Technical Aspects of MIS

Artificial IntelligenceAlgorithms & Data StructuresGroup Support Systems

Human-Computer Interaction

Human-Computer Interaction

Human-Computer Interaction

Human-Computer Interaction

Organizational/Behavioral

System ManagementJudgment and Decision Making (individual

and group)Organizational ChangeEthical, Social and Legal IssuesInternational Issues

Decision Sciences

Operations Research/ Operations ManagementDecision Support Systems/ Executive Support

SystemsEconomics of Information Systems

Individual Paper Presentation

A Sample of Selected Papers

Ethics: Authorship of Papers1) Conception of idea & design of experiment

2) Actual execution of experiment; hands-on lab work

3) Analysis & Interpretation of data

4) Actual writing of manuscript ICMJE: Each author = able to defend work publiclyAlternatives: Credits & ContributorsQuestion of “Guarantee” Important to ensure: Accountability with Credit

[sources: B. J. Culliton, Science Vol. 242 p.658; R. Smith, BMJ Vol. 314 p.992]

Presented by: Faiz Currim

Usable Knowledge: Social Science and Social Problem Solving C.E.Lindblom & D.K.Cohen, 1979

The problem: the dissatisfaction from the social sciences as an instrument of social problem solving

L&C’s contribution: they discuss issues that social scientists should consider if they wish to be useful for social problem solving. e.g.,

How to define useful, success, or failure Misconceptions that social scientists have about social

science Includes a long bibliography section

Presented by: Irit Askira Gelman

The Entity-Relationship Model - Toward a Unified View of Data

Who/Where? – Author: Peter Pin-shan Chen – Sources: ACM Transactions on Database Systems (1:1), 1976

What?– A conceptual data model entities + relationships– Commonly used for database design & analysis– ER diagram is used to visually represent data objects

Why?– Unify the network and relational database views– Lead to a proliferation of theoretical extension (e.g. EER)– Map well to the relational model– Simple and easy to understand with a minimum of training

Presented by: Dongwon Lee

A Comparative Analysis of Methodologies for Database Schema Integration

Who/ Where/ When? Batini C., Lenzerini, M., Navathe S. B. [ACM Computing Survey,

1986]

What? Provide uniform framework for schema integration Comparative review of work done Strengths and weaknesses of existing methodologies General guidelines for future improvement

Why? Ties together various disparate frameworks Paves way for future work

Presented by: Vijay Khatri

Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases

Who/ Where / When? Authors: Amit P. Sheth & James A. Larson [ACM Computing

Surveys, 1990]

What? Define a reference architecture for distributed DBMS. Show how various FDBS architectures can be developed. Define a methodology for developing one architecture of an FDBS. Discuss critical issues on developing and operating an FDBS.

Why? Provide a reference architecture. Itself is extensively referenced.

Presented by: Huimin Zhao

Software Engineering

The Capability Maturity Model for Software

Paulk, M. C., B. Curtis, & et al. (July, 1993). Capability maturity model, version 1.1. IEEE Software, 18-27.

Presented by: Conan Albrecht

Lessons from a Dozen Years of Group Support Systems Research: A Discussion of Lab and Field Findings

Jay F. Nunamaker Jr., Robert O. Briggs, Daniel D. Mittleman, Douglas R. Vogel

Pierre A. Balthazard

Presented by: Karl Wiers

Georgakopoulos, D., Hornick, M., & Sheth, A. (1995).An Overview of Workflow Management: From Process Modeling to Workflow Automation Infrastructure. Distributed and Parallel Databases, 3(2), 119-153

•Distributed Object Management•Customized Transaction Management

•Business Process Reengineering•Business Process Modeling

•Increase workflow automation in complex real-world environments involving heterogeneous, autonomous and distributed database systems

Presented by: Jeff Perry

Process ModelingBill Curtis, Marc I. Kellner and Jim Over

Uses for Process Modeling Four Perspectives in Process Modeling

functional organizational behavioral informational

Comparison of Different Process Modeling Techniques

Presented by: Xiao Fang

Frameworks for Component-Based Client/Server Computing

Who/ Where? Authors: Scott M. Lewandowski [ACM Computing Survey, 1998]

What? Review of client/server computing and component technologies Comparative study on the use of CORBA, DCOM and Java for

client/server computing Discussion on the frameworks issue, especially on business objects as a

client/server framework and compound documents as a client framework

Why? Provides a comprehensive review on related topics Proposes a new model for client/server computing

Presented by: Yi Shan

A foundation for the study of group decision support systemsG. Desanctis and R. Brent Gallupe

Management Science, Vol. 33, March 1987What?

Goal of Group Decision Support Systems Measurement Three levels of the systems Taxonomy of systems: group size and member

proximity The role of task Research directions

Presented by: Dongsong Zhang

Information Visualization for Collaborative Computing

Information structure for visualizationGroupware and collaborative computingTextual analysisA SOM Based Information Visualization Tool for

Groupware

H. Chen, O. Titkova, R. Orwig, J. F. Nunamaker

Presented by: Bin Zhu

Agents that Reduce Work and Information OverloadPattie Maes

Discuss the basic concepts of autonomous agent

Popular examples: E-mail Agent, Meeting Scheduling Agent

Challenging future research direction Privacy, legal responsibilities

Presented by: Michael Chau

The Psychology of Human-Computer Interaction (1983)

Cognitive models of human interaction with computers

Used to explain and predict human behaviorGOMS Model, Keystroke Level Model, etc.

Understanding ofhuman information processing

system design, analysis, and training

Presented by: Rosie Hauck

Stuart K. Card, Thomas P. Moran (Xerox Parc) and Allen Newell (CMU)

The Impact of Sunk Outcomes on Risky Choice Behavior

Applied sunk cost research to sunk gains Integrated two major theoretical concepts

Problem framing• Mental accounting

• Editing rules - Prospect Theory Sunk outcomes

• Effects of prior gains and losses on risky decision making

Presented by: Gary Mahon

Kling, Rob. (1991). Computerization and Social Transformations. Science, Technology and Human Values, 16(3), 342-367.

RQ: To what extent does the use of computer-based systems transform the social order (and, if so, how)?

Computerization may restructure major social relationships, including interpersonal, intergroup and institutional ones

The social effects of computerization are more complex than many suspect

Different sectors are affected to different degrees and in different ways

Computerization is not always transformative Empirical studies have difficulty identifying substantial

social changesPresented by: Craig Erwin

Duchessi, P., and O’Keefe, R. A Knowledge-based Approach to Production Planning. J. Opl Res. Soc. 41(5), 1990.

Optimization techniques/heuristic approaches: lack credibility incur high cost of developing and using models require excessive data

A knowledge-based production planning system employs a set of production rules and inference mechanism to model the process of:

building plans, computing decision variable values, selecting combination of values for each period, and incorporating constraints and heuristics into the reasoning process.

Presented by: Poh-Kim Tay

This paper describes: one company’s experienced-based approach to

production planning and how it was incorporated into a knowledge-based system.

the production planning state-space use of common planning constraints and

heuristic procedures a prototype that develops production plans for

one product family

Duchessi, P., and O’Keefe, R. A Knowledge-based Approach to Production Planning. J. Opl Res. Soc. 41(5), 1990.

Reengineering the Corporation: A Manifesto for Business Revolution

What it’s aboutWhy I like it

Michael Hammer and James Champy (1993)

Presented by: Wayne Anderson

Computers and IntractabilityA Guide to the Theory of NP-Completeness

Shows how to recognize NP-Complete problems

Lists over 300 main entries

Michael R. Garey and David S. Johnson

Presented by: Gregory Lousignont

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The Seven Areas???

MIS Foundations & MethodologyDatabase TechnologySoftware Development and EngineeringTechnical Aspect of MISHuman-Computer InteractionOrganizational/BehavioralDecision Sciences

Lessons Learned

Group size (a problem)Organization (a problem)Definition (a problem)U of A MIS = General MIS Field?

Discussion