Further developments

Furthermore, we tested several modeling tools that support the methods that were developed. We are still attempting to improve both the methods and modeling speed. While modeling legislation we continue to develop the POWER ontology of legislation. We also developed an architecture that enables us to embed the knowledge components within (the future) process models of knowledge intensive processes and tasks.

Our experiences thus far are that both legislation drafters, experts from the knowledge groups and people from our automation department are very enthusiastic about our approach. This creates the basis for further development.

7.8. Further developments

The first period spent doing research in the POWER domain delivered useful tools (such as an anomaly detector) and several models that have proved to be supportive in the implementation process of new legislation.

We already experienced that working with different experts from different knowledge groups using the POWER methods increased the homogeneity of the conceptual models of the legislation in question.

However many problems remain to be solved. Legislation consists of definitions, normative descriptions of situations and, on some occasions, directives for processes (e.g. the inspector should send a confirmation letter within two weeks). The latter is a particularly complicating factor when bridging the gap between legislation and design. Administrations have a great amount of freedom in their organizational and process design. The law-based models of POWER, therefore, should fit in common process organization and systems design methods. This process aspect is accounted for in our current research activities. We try to implement an architecture that consists of several layers:

• Legislative model and process model layer;

• Functional layer (re-factored conceptual model integrated with task model);

• Technical layer (knowledge components and application frameworks, and a connecting architecture);

• Realization layer (generated knowledge component code or developed framework code);

• Implementation layer (deployed knowledge components).

The latter four levels are already applied on small scale in the DTCA’s automation department. We plan to broaden the architecture to full-scale application. The DTCA developed the process layer in co-operation with the Telematics Institute (a research school of the Twente University) in the so-called Testbed research program. Our challenge is to integrate POWER and Testbed and connect the output of both to the functional layer that is input for our software factory (B/AC).

7.9. Conclusions

In the POWER program a knowledge capitalization/knowledge codification approach is combined with an organization dynamics approach in which the DTCA’s knowledge processes are aligned (see Figure 7.9.1). As a result the DTCA will be able to improve the quality of law enforcement and decrease the time needed for implementing changes in legislation and regulations.

Thus far we established a method that:

• Provides us with verifiable models;

• Helped us to detect over 150 anomalies in legislation;

• Bridges the gap between legislation and business systems design;

• Provides the means to capture legal knowledge in and tractable and maintainable way.

We think that the POWER method can be applied in many other governmental situations and perhaps even in non-governmental organizations where regulations play an important role (e.g. process industries, insurance companies, etc.).

We noticed that legislative drafters (and representatives of the knowledge groups as well) often express themselves procedurally and consequently they often create unintended restrictions on the design of procedures, organization and systems often following legislation drafting. Information technologists and knowledge engineers therefore prefer declarative specifications (which allow a greater amount of implementation freedom).

Although we already succeeded in breaking up discussions with respect to procedural specifications much research is needed especially after representation formalisms that are suitable for both legal experts and information technologists.

Knowledge Management: The Role of Mental Models in Business Systems

Figure 7.9.1.: The government and its environment. The POWER research program aims at supporting both legislation drafting and implementation of legislation thus improving the affectivity of law enforcement organizations.

In many knowledge management approaches we see that either a lot of attention is paid to stock approaches (e.g. the creation of digital libraries and inter- and intranet technologies or knowledge based systems) or to flow approaches (e.g. HRM measures aimed at increasing organizational learning and knowledge sharing). We have found that with the right combination of these approaches one can achieve tremendous results.

Using POWER enables more efficient and effective knowledge creation and dissemination processes from which both the DTCA and the taxpayer will eventually benefit. Knowledge management has become more than just an interesting field of research, it pays off.

References

Van Engers, T.M., Glassée, E., 2001, Facilitating the Legislation Process using a shared Conceptual Model. In: IEEE Intelligent Systems January 2001, p. 50- 57.

Van Engers, T.M., Kordelaar, P., 1998, POWER: Programme for an Ontology based Working Environment for modeling and use of Regulations and legislation, Proceedings of the ISMICK’99.ISBN 2-913-923-02-X.

Van Engers, T.M., Kordelaar, P.J.M., Den Hartog, J., Glassée,E., 2000, POWER: Programme for an Ontology based Working Environment for modeling and use of Regulations and legislation. In Proceeding of the 11th workshop on Databases and Expert Systems Applications (IEEE) eds. Tjoa, Wagner and Al-Zobaidie, Greenwich London, ISBN 0-7695-0680-1, pp.

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Knowledge Management: The Role of Mental Models in Business Systems