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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
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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 • From areas to categories • 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 • Systems Theory • Cognitive Science • Social Psychology • etc. • Methodologies
Physical Logical Conceptual Application Applications DBMS Operational Storage Structure DBMS Interoperability Decision Support Transaction Management Metadata Management Special Applications (MM, web, temporal/ spatial) Query Processing • Key Researchers • Jennifer Widom • Jeff Ulmann • Hector Garcia Molina • Key Researchers • Peter Chen • E. F. Codd • Bill Inmon • Bhawani Thuraisingham • Arie Segev • S. B. Navathe • Benjamin Wah • Richard Snodgrass • Umesh Dayal Database Technology Modeling
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
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., • 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 systems • G. Desanctis and R. Brent GallupeManagement Science, Vol. 33, March 1987 • What? • 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 H. Chen, O. Titkova, R. Orwig, J. F. Nunamaker • Information structure for visualization • Groupware and collaborative computing • Textual analysis • A SOM Based Information Visualization Tool for Groupware 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
Understanding of human information processing system design, analysis, and training The Psychology of Human-Computer Interaction (1983) Stuart K. Card, Thomas P. Moran (Xerox Parc) and Allen Newell (CMU) • Cognitive models of human interaction with computers • Used to explain and predict human behavior • GOMS Model, Keystroke Level Model, etc. Presented by: Rosie Hauck
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 changes Presented 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
Duchessi, P., and O’Keefe, R. A Knowledge-based Approach to Production Planning. J. Opl Res. Soc. 41(5), 1990. • 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
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 IntractabilityA Guide to the Theory of NP-Completeness Michael R. Garey and David S. Johnson • Shows how to recognize NP-Complete problems • Lists over 300 main entries 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?