Arthur C. Jones Thesis Committee Mike McNeese (thesis advisor) - PDF document

Thesis Defense Presentation THE INFORMATION-TECHNOLOGY- PEOPLE ABSTRACTION HIERARCHY: A TOOL FOR COMPLEX INFORMATION SYSTEM DESIGN Arthur C. Jones

Thesis Committee • Mike McNeese (thesis advisor) • Steve Sawyer • Dan Lorence

Abstract This work presents a general model for developing the requirements and constraints for the construction of information systems. The model is based upon Rasmussen’s [1986] abstraction hierarchy model, but substitutes the elements of information, technology, and people as peers in place of the traditional whole-part hierarchical decomposition. The resulting I-T-P Abstraction Hierarchy is shown to have utility for information systems engineers and is demonstrated by applying the model to the design of a system for emergency services dispatch operations.

Who is this guy? • Long time computer enthusiast (hardware, networking, programming, database designer) • Paramedic – instructor (various environments) • IST student

Outline of presentation • Some preliminary information, definitions, etc. • Abstraction Hierarchy Models • The Information-Technology-People trichotomy • My model, the general I-T-P AH • Demonstration – WDA – Domain-specific model – Implications – Prototype construction • Conclusion & Future Work

What are “Information Systems” • Information System = coordinated activity involving information, technology, people. • I-T-P Trichotomy exists throughout literature, but using different names.

What are “Critical Incidents” • The term “critical incident” as applied here is an extension of Flanagan’s [1954] concept: “…defined as extreme behavior, either outstandingly effective or ineffective with respect to attaining the general aims of the activity.” The extension applied to this definition is in consideration of the response to unforeseen circumstances, and an acknowledgement that some circumstances can not be foreseen.

Critical Incident Information Management Systems • Importance • Complexity • Potential for failure • Results of failure • Motivation for better systems

What is “better?” • “Better” ? more complex system – Trauma shears – The “splashback” problem [Vicente 2004] • “Better” = able to adapt – Requires a more complex design process

Abstraction Hierarchy Models Whole-Part Structural Decomposition Hierarchy Functional Total System Sub-System Subassembly Component Unit Functional Most abstract form; overall reason for the system Purpose Abstract Causal network, the flow through the system Function Means – Ends Generalized Concept over implementation Abstraction Function Hierarchy Physical Representation of physical processes of the system Function Physical Most “concrete” form Form

Abstraction Hierarchy Models • From Rasmussen [1986] • Abstraction hierarchy along vertical axis – Choice of layers can vary depending on domain and approach • Structural decomposition hierarchy (“whole- part”) along horizontal axis – Choice of labels can vary here as well • Why-What-How relationships between strata • Each layer is a complete representation of the same system

Abstraction Hierarchy Models Whole-Part Structural Decomposition Hierarchy Functional Total System Sub-System Subassembly Component Unit Functional Washing specifications; Purpose Energy Waste requirements Abstract Energy, water, and detergent Function flow topology Means – Ends Generalized Washing, draining, drying, Abstraction Function heating, temperature control Hierarchy Mechanical drum drive; pump Physical and valve function; electric/gas Function heating circuit Physical Configuration and weight, size, Form “style” and color

Abstraction Hierarchy Models • Serve as models for Work Domain Analysis • Cell contents are objects (nouns) which represent the system (the work domain) • Task analysis can be mapped onto AH models, as tasks take place within a work domain, but task analysis can not be used to complete the model.

Ecological Interface Design (EID) • From Rasmussen and Vicente [1994] • Ecological = natural = uncontrolled. • Contrasted with intentional (well defined) systems. • Uses AH’s why-what-how relationships to define human-computer interaction needs and constraints. • Examples applied to nuclear power plant monitoring and control, manufacturing plants, etc.

Information, Technology, and People • Part of the foundational philosophy of the School of IST. • Sawyer, S. & Chen, T.; 2002; Conceptualizing Information Technology and Studying Information Systems: Trends and Issues; in Myers, M. & Wynn, E. & DeGross, J. (Eds.) Global and Organizational Discourse About Information Technology ,London: Kluwer, 109-131 • Vicente [2004]: “soft technologies” • Xia & Lee [2004]: “organizational factors” • Consider: – Computer science: efficiency is measured in human-centric terms – Library science: Dewey Decimal system = technology – HCI: the purpose of humans interfacing with computers is information transfer

My Thesis: • Adapting the abstraction hierarchy model to complex information systems design can aid in achieving the ability for those systems to adapt to novel or extraordinary circumstances. (Critical Incident Information Management Systems) • Demonstration application: CIIMS for Emergency Services Dispatch

Approach: • An abstraction hierarchy (AH) was developed which targets the composition of a comprehensive information system. In contrast to the typical abstraction hierarchy’s whole-part decomposition of systems into sub-systems, units, assemblies, and components, I have implemented a decomposition of the system into the three peer elements of information, technology, and people.

General I-T-P AH Model Structural Decomposition Information Technology People Purpose / Overall outcome improvement Goal Level of Abstraction Abstract Description of environment and conveyance of Understanding and manipulation of environment Function decision makers’ wishes Refined or transformed data Organization, transformation, Understanding of variables Generalized which accurately describe refinement, storage, describing actual and desired Function relevant conditions and users’ movement, presentation, etc. conditions wishes in a timely fashion of data Representation of Real-World Presentation of data to users, and Analysis of conditions and exhaustive set of available interpretation of users’ directions direction of activity Function details Data communications / storage / processing Real-World capabilities, interface hardware / software, Raw Data Users Form database structure, decision support algorithms, etc.

Approach: • Work Domain Analysis • Populate AH model’s cells • Infer needs of CIIMS from the model • Develop initial prototypes • Enter development cycle

Work Domain Analysis • Literature Review: EMD, ATC, Emergency Medicine (for both content and methodology) • Prior involvement • Site visits to interview/observe EMD activity

Beaver Stadium EMS • ~108K spectators + surrounding parking areas making it the 3 rd largest population center in PA (http://wpsx.psu.edu/ourtown/statecollege/1.html) • >40 response teams with varying capabilities • 10-20 incidents per game, with large variation in number and type

Site Visits • Four centers • Represent different environments • Familiar to author • Interviews with administrators and dispatchers + observation

Findings of WDA • Diversity of approach to mission. • Technology is homogenous, implementation varies tremendously. • Current information systems work well for normal operations, though human element must learn and adapt the most. • ESD is a “gateway” to ES jobs; not so much other ESD jobs (probably due to operational differences between centers)

Findings of WDA • Great deal of “free” information movement between personnel, as well as loosely- formed information held by personnel outside of technology. • Critical incidents inside the ECC do not necessarily equate to critical incidents in the field. • Technology can hide information.

Findings of WDA • Overall goal is appropriate resource allocation. • This is approached on an incident-by- incident basis. • Current technology-based systems do not support real-time aggregation of incident data to reveal overall resources/needs status.

WDA – Interesting Observation