Modeling and Describing an Ontological Knowledge Framework for Integrated Public Service Delivery

Introduction

Contemporary governments are experiencing a shift from supplying common, non-electronic services towards more demand-driven and personalized electronic service delivery (see e.g. Chen, 2003). The evolution of information technology and new requests of service from the modern society compelled the evolutions of new solutions for the interaction between citizens and their governments (Sabucedo, Rifón, Pérez, & Gago, 2009). As a result, governments are focusing more on their client’s needs and less on their own functionalities, organizational structures, and boundaries. Initially, public organizations focused on recurring client needs instead of on irregular needs. As such, assessing needs and reacting to needs do not provide the flexibility to react to new needs or even changes in laws and regulations. Public services are fragmented due to constitutional, legal, and jurisdictional limitations. As a consequence, governments are often acting in silo structures, but nowadays are forced to cooperate with other government agencies and even partners in the private sector. Integrated Service Delivery (ISD) can provide an opportunity for public organizations to collectively offer a coordinated bundle of services that match variable client needs (Kraaijenbrink, 2002). This should diminish fragmentation of service delivery. Furthermore, ISD improves information sharing and collaborative work between government systems and their clients (Zhu, Li, Shi, Xu, & Shen, 2009).

The focus of the research reported in this chapter is to determine relationships, relational constraints, and interdependencies between the main concepts for ISD. Insights in relationships among functionalities, constraints that apply for such relationships, and services provided by organizations are required. For example, if a citizen requests a driver’s license at the municipality he also needs to be registered in the citizens’ registry and he must be eligible to drive a motorized vehicle. These insights are needed because ISD requires that public organizations collaborate with each other. This understanding contributes to distinguish the key concepts and relations that form the basis for coordinating the activities necessary for ISD. This is realized by the development of an ontological knowledge framework for integrated public service delivery, which aligns and abstracts knowledge of the public domain from several viewpoints. By studying the public domain from organization-, actor-, service-, resource-, and event-centric viewpoints in, we attempt to develop a rich ontology for ISD that is well-balanced between several perspectives.

Ontologies are becoming increasingly essential for organizations, because they are looking towards them as vital machine-processable semantic resources for many application areas (Jarrar & Meersman, 2008). An ontology is an agreed understanding of a certain domain, formally represented as logical theory in the form of a computer-based resource. Complex software applications such as e-services for the public domain can meaningfully communicate to exchange data and thus make such data transactions interoperate independently of their internal technologies by sharing an ontology. Relating the notion of ontology to the research described in this chapter, it can be noticed that organizations sharing an ontology which includes semantics related to the public domain create a starting point for realizing ISD. Because an ontology that is shared by public organizations is an agreed understanding of the public domain and as such enables to identify essential concepts and relations between concepts in such processes it enables interoperability. Ultimately, the ontology should help to exchange information and monitor the execution of services. A graphical model of the ontological knowledge framework is presented in this chapter, which includes a language to determine requirements for ISD based on the ontology. This is followed by a textual description of the model before this chapter is concluded.