Agent-Oriented Analysis of E-Government Information Systems

Philippe Massonet (phm@cetic.be)
Rue Clement Ader, 8, B-6041 Gosselies, Belgium

Category: Problem discussion

Introduction

The development of E-government systems [1] is a growing trend in governments worldwide. The general aim is to provide better service to the citizen, provide improved services for businesses and other government agencies, improve transparency and avoid corruption, empower the citizen through information, and provide efficient government purchasing by using new information technologies.

This position paper relates the experience of one such information system under development, which is in the analysis phase, and defends the position that an agent modeling approach to these kind of problems is suitable, even though the full power provided by agent systems is not currently needed. The system currently under analysis can be viewed as an application integration problem and will most likely be implemented using EAI or B2B technologies [2]. The information system requirements are already well known, and our work focuses on identifying the requirements of the partners, i.e. other federal or local government agencies, businesses and citizens and defining a common domain ontology.

Problem Statement

The federal government agency wants to integrate a number of its existing applications into a single information system for its own purposes and make it useful to others by transforming it into an open system. An open system provides access to the information system to its external partners. It also creates links with the data of the information systems of its external partners (so it cannot be viewed as simply a client-server type of information system).

The need for creating a new integrated is driven by the fact that the new federal agency is the result of the merger of several departments that each have their own information system:

An open system is needed because:

One of the main objectives of an open information system is to share data between its partners, and to avoid a chaotic situation where everyone would have their own redundant, and inconsistent data that could not be shared. The inability to share the data would hinder the ability to define business level processes across partner boundaries, e.g. between the federal and regional governments. The model that is proposed is centralized: partners interact with the federal government agency which owns the bulk of the shared data, but they do not interact directly (they can of course, but not with this information system).

Research Questions

Most current object-oriented analysis methodologies are aimed at modeling a single information system.A0 The above type of problem exhibits two characteristics that indicate that an agent modeling approach to these kind of E-government problems is suitable even though the full power provided by agent systems is not needed at the moment:

Since the information system currently focuses on sharing distributed data, existing integration technologies can be used for implementation. However, as the information system is deployed and users gain experience they may come to expect features more elaborate that agent technology can more easily provide. The agent approach provides many interesting modeling concepts for analyzing these kind of problems [3, 4, 5] such as goals, roles, organizations, and ontology. An important issue is whether adopting an agent modeling approach is too cumbersome for such a problem given the tight time constraints of the study.

The main objective is to exchange data, not to define inter-partner business processes. The basic issue is thus to define a domain ontology that is agreed upon by all partners, i.e. each partner can translate to and from the domain ontology to his own information system. One must notice that the existing legacy data models cannot easily be changed because of the existing data, and that the common ontology needs to consider this.

Our approach is to

The approach thus uses the few agent concepts such as goal, goal refinement, role and ontology that are needed to solve the problem at hand. The ability to use a subset of an agent methodology is important: it allows us to experiment new modeling techniques on new types of problems without compromising the tight time constraints of the study. Furthermore, it allows the model to evolve in the future as more sophisticated features are required by users by using a more complete set of agent concepts if needed.

References

  1. Pinkston, J. 93The Ins and Outs ofA0 Integration, How EAI differs from B2B Integration94 EAI Journal, August, 2001, 48-52,A0 http://w ww.eaijournal.com/PDF/Ins&OutsPinkston.pdf