What is MIS? (And How We Figured It Out) A definition of the MIS field MIS 696a/797 Fall 1998

Agenda §The Process §The Areas of MIS §Individual Paper Presentations §Lessons Learned §Discussion §Dinner

The Process §Brainstorming Session I via GroupSystems §Faculty Survey and Interviews §Researching areas of MIS §Brainstorming Session II: MIS areas l From areas to categories l Splitting up the work §Which paper to choose?

Which Paper to Choose? §Backtrack through paper reference §Use overview books §Web sites §webofscience.com §Interviews

The Seven Pillars of MIS A Breakdown of the MIS Field

MIS Foundations & Methodology §Science & Scientific Practice §Theoretical Background l Systems Theory l Cognitive Science l Social Psychology l etc. §Methodologies

Database Technology PhysicalLogicalConceptualApplication 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 engineering §Workflow management/Process modeling §Business Process Reengineering §CASE tools

Technical Aspects of MIS  Artificial Intelligence §Algorithms & Data Structures §Group Support Systems

Human - Computer Interaction

Organizational/Behavioral §System Management §Judgment and Decision Making (individual and group) §Organizational Change §Ethical, Social and Legal Issues §International Issues

Decision Sciences §Operations Research/ Operations Management §Decision Support Systems/ Executive Support Systems §Economics of Information Systems

Individual Paper Presentation A Sample of Selected Papers

Ethics: Authorship of Papers 1) 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 publicly §Alternatives: Credits & Contributors §Question 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., l How to define useful, success, or failure l 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? l Batini C., Lenzerini, M., Navathe S. B. [ACM Computing Survey, 1986] §What? l Provide uniform framework for schema integration l Comparative review of work done l Strengths and weaknesses of existing methodologies l General guidelines for future improvement §Why? l Ties together various disparate frameworks l Paves way for future work Presented by: Vijay Khatri

Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases §Who/ Where / When? l Authors: Amit P. Sheth & James A. Larson [ACM Computing Surveys, 1990] §What? l Define a reference architecture for distributed DBMS. l Show how various FDBS architectures can be developed. l Define a methodology for developing one architecture of an FDBS. l Discuss critical issues on developing and operating an FDBS. §Why? l Provide a reference architecture. l 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, 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), 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 Modeling Bill 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? l Authors: Scott M. Lewandowski [ACM Computing Survey, 1998] §What? l Review of client/server computing and component technologies l Comparative study on the use of CORBA, DCOM and Java for client/server computing l Discussion on the frameworks issue, especially on business objects as a client/server framework and compound documents as a client framework §Why? l Provides a comprehensive review on related topics l Proposes a new model for client/server computing Presented by: Yi Shan

A foundation for the study of group decision support systems §G. Desanctis and R. Brent Gallupe Management Science, Vol. 33, March 1987 §What? l Goal of Group Decision Support Systems l Measurement l Three levels of the systems l Taxonomy of systems: group size and member proximity l The role of task l Research directions Presented by: Dongsong Zhang

Information Visualization for Collaborative Computing §Information structure for visualization §Groupware and collaborative computing §Textual analysis §A 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 Overload Pattie Maes §Discuss the basic concepts of autonomous agent §Popular examples: l Agent, Meeting Scheduling Agent §Challenging future research direction l 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 behavior §GOMS Model, Keystroke Level Model, etc. Understanding of human 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 l Problem framing Mental accounting Editing rules - Prospect Theory l 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), §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 changes Presented by: Craig Erwin

Duchessi, P., and O’Keefe, R. A Knowledge-based Approach to Production Planning. J. Opl Res. Soc. 41(5), §Optimization techniques/heuristic approaches: l lack credibility l incur high cost of developing and using models l require excessive data §A knowledge-based production planning system employs a set of production rules and inference mechanism to model the process of: l building plans, l computing decision variable values, l selecting combination of values for each period, and l incorporating constraints and heuristics into the reasoning process. Presented by: Poh-Kim Tay

§This paper describes: l one company’s experienced-based approach to production planning and how it was incorporated into a knowledge-based system. l the production planning state-space l use of common planning constraints and heuristic procedures l 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 about §Why I like it Michael Hammer and James Champy (1993) Presented by: Wayne Anderson

Computers and Intractability A 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

The Seven Areas??? §MIS Foundations & Methodology §Database Technology §Software Development and Engineering §Technical Aspect of MIS §Human-Computer Interaction §Organizational/Behavioral §Decision Sciences

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

Discussion