An Ontology for eGovernment: Linking the Scientific Model with Concrete Projects

Gertraud Orthofer*, Maria A. Wimmer°

* University of Linz, Institute of Informatics in Business and Government, Austria ° University of Koblenz, Institute for IS Research, Research Group eGovernment, Germany

* orthofer@iwv.jku.at, ° wimmer@uni-koblenz.de

Abstract The field eGovernment has become an important topic of research and development. In order to support the activities going on in research and practice, an eGovernment portal providing on the one hand an eGovernment ontology and on the other hand an overview of practical projects in a certain field would be helpful. Such a portal could be a central entry point for the various stakeholders to a) learn about the field eGovernment and its characteristics from a scientific perspective, b) provide an instrument to further structure the field, c) thematically cluster projects, and at the same time d) provide a practical instrument for the users to overview the projects in the field. Within the project eip.at, such a portal has been created by using semantic technologies.

Introduction In the last years, eGovernment has developed to a renowned field of research. Likewise, a tremendous number of projects both in research and in practice have been initiated. Unfortunately, no structured approach was used to develop a common understanding of expressions used to form the field. Consequently, different disciplines have created their own definitions. In the application area, many projects address the same issues redundantly and it is difficult to get an overview of projects in the field. These problems led to the project eip.at (eGovernment intelligent portal), which was initiated and carried out at the Institute of Informatics in Business and Government (IWV) at University of Linz (http://www.eip.at – German only). The aims of the project were on the one hand to structure the field eGovernment and to link the terms and projects among each other by using semantic technologies. The result should be an eGovernment ontology and an eGovernment knowledge map. On the other hand, a prototype for a knowledge portal should be implemented to provide this information in a structured and semantically enriched way. Apart from the rather practical objectives listed before, a key research question was to learn about Copyright © 2002, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.

the applicability of semantic modeling technologies in the field of eGovernment. In the early phase of the project, four key user groups have been identified. Furthermore, a number of benefits were defined for each of these groups, some being valid for several user groups. Figure 1 provides an overview of the four user groups and their expected benefits to use the portal. Further details can be found in (Knoblechner et al, 2005) and (Wimmer, 2006).

Figure 1: Stakeholder groups and their identified benefits to use the eip.at portal In the subsequent part of this contribution, we first describe the semantic modeling and ontology concept. Then, the eGov ontology and the eGov knowledge map are briefly explained conceptually and practically. The paper concludes with a discussion of the lessons learnt in the portal development and an outlook of further work to do.

Semantic Modeling and Ontology Concept used

The starting point for developing the eGov ontology for eip.at was to structure the information and aspects shaping the eGovernment domain. Semantic modeling was used to develop the knowledge map. Due to space limitations, theories of semantic modeling are not discussed here. Instead, the reader is referred to focussed literature such as (Geroimenko and Chen, 2003), (Hjelm, 2001), and (Staab and Studer, 2004). The following aspects summarize some advantages of ontologies in respect to other structuring concepts: • unique, unambiguous definitions of expressions; • avoidance of semantic conflicts of e.g. naming, value

ranges, abstraction levels, type of visualization; • using a comprehensive set of elements; • concepts classes and instances to structure the domain; • clear description of relations (hierarchies / other); • description of knowledge objects via attributes,

functions (i.e. specific relations), axioms; • machine-computable; • set of rules and axioms for automatic deduction; • concept of inheritance. In the project eip.at, the modeling tool k-infinity was used. Background for modeling with k-infinity was a cooperation with an Austrian contractual partner of i-views, who was interested in evaluating k-infinity for the use in the modeling of a rather complex and larger knowledge map. The ontology approach used in eip.at bases on two main concepts: classes of objects (e.g. a “person”) and concrete instances of classes (e.g. “Lara Croft” is an instance of “person”). Furthermore, extending concepts are provided in k-infinity, some of which are: • Roles: Roles are used to extend instances, which are not

directly extendable with “individuums”. E.g. the class “author” is a possible extension (role) of a “person”.

• Attribution objects: Such objects are geographical information, time etc., which could also be mapped via attributes themselves. Yet then, an inter-linkage among objects would not be possible, because an attribute belongs to a specific object. For example, with the usage of attribution objects, all events taking place in a year or projects of a certain city or region can be searched for quite easily.

• Content explanations: Content explanations reflect objects such as descriptions, definitions, project foci and relations. The first two serve to explain expressions used. Project foci has been added to enable the recognition of projects targeted towards the same key aspects. The object relations are used to demonstrate and model linkage between different knowledge objects.

In the course of the project eip.at, the modeling tool k-infinity was assessed in comparison with other tools for semantic modeling (SemTalk, OntoEdit, OpenCYC, OilEd and Protégé). The evaluation results are available in a diploma work (cf. Knoblechner and Seliger, 2005) and are briefly summarized in (Knoblechner et al, 2005) and in (Wimmer, 2006). Further comparison results of semantic modeling tools are in (Gómez-Pérez, 2002).

eip.at’s eGov Ontology and Knowledge Map The point of departure for the eGov ontology was the development of a scientifically structured field as detailed in figure 2. The structure was taken from the holistic view on eGovernment developed by (Wimmer and Traunmüller, 2002). As figure 2 shows, the root node of the egov knowledge map was called “eGovernment intelligent portal”. Underneath, three sub-classes were created: practical view, scientific perspective and modeling artifacts.

Figure 2: Upper part of the eGov knowledge map and eGov ontology (partial view, not all nodes are shown)

Figure 3: Practical view: main concepts (classes) The eGov ontology is reflected in the scientific perspective, which was divided into four key areas as shown in figure 2. The cross-perspective issues describe aspects that cannot clearly be assigned to one of the core

scientific perspectives shown in figure 2 (e.g. standards and interoperability may be part of technical, data/info/ knowledge, process, and organization issues alike). The eGovernment part covers e.g. the definitions (currently over 60 identified and inserted). The Topics related to eGovernment provide an auxiliary part to link e.g. future ontologies of eDemocracy, eHealth etc. The node called practical view (cf. figure 2) covers the aspects related to projects and specific instances in eGovernment. Examples are actors, information source, ICT infrastructure, projects, specific standards, events, public services and life events as shown in figure 3. Another auxiliary node as shown in figure 2 is modeling artifacts. It covers terms that can neither clearly be assigned to the practical nor to scientific perspective. The status of the current eGov knowledge map and eGov ontology are: • The eGov ontology is developed in German to cover a

large part of the core eAdministration domain. • The eGov knowledge map is not yet modeled largely,

since the data should partially be generated in an automatic way from an external eGovernment projects database. The interface specifications have been proven, yet access to the eGovernment projects database is not yet possible.

Portal Development, Lessons Learnt and Outlook

After the eGov knowledge map had reached a reasonable size, a web portal was implemented to provide the eGov knowledge map to the users via a simple web interface. For the export of the knowledge map from k-infinity to the oracle 9i database of the web portal, RDF (Resource Description Framework) and the Jena Framework were used. In the following, a few of many lessons learnt from the project eip.at are summarized, and future work on these topics is described. First of all, developing the eGov ontology and knowledge map was a highly know-how intense and time-consuming work. Many discussions and reflections were needed to develop the currently existing knowledge map. Apart from that, the existing ontology and knowledge map reflect the understanding of the team developing it. The model needs to be proven by experts in the field. Apart from that, the domain is still evolving and, hence, requires a rather dynamic and flexible (i.e. evolving) ontology. Next steps in this respect are on one hand to develop an English version of the eGov ontology in order to open the discussion within the eGov community. On the other hand, the knowledge map needs to be further developed to include the eGov projects and other sub-domains such as eDemocracy. As regards the modeling tool, several weaknesses and constraints have been found while modeling in k-infinity. Consequently, we are currently discussing the migration to

another modeling tool. Here, further investigations are required to select a proper tool that fits the requirements best. In this respect, suitable semantic modeling languages shall be examined as well. As regards the web portal, the search process is not yet satisfactorily implemented. It suffers from performance problems. Adequate search algorithms are needed to handle vast amounts of data in large knowledge maps. Apart from that, further work shall evaluate different combinations of database systems and frameworks. Finally, a portal is more attractive for everyone if more communication features are integrated (chat, fores, etc.) to interactively discuss and develop the knowledge map, different understandings and so on. Acknowledgement: The project eip.at was carried out with the help of M. Knoblechner, M. Krieger, M. Leitner, H. Luger, and T. Seliger. The authors express their special thanks for the valuable work of this excellent team.

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