Development processes for ontologies

One way of encoding prior knowledge for activity recognition is by using ontologies [104], and although there are no development processes for models for activity recognition, there are some for developing and maintaining ontologies [60]. An ontology development process resembles a software engineering process in that it is divided in similar phases – specification, conceptualisation, formalisation, implementation, and maintenance [48]. Below we discuss several different development processes for ontologies.

5.2.3.1 Uschold and King’s ontology development method [149]

According to [60, p. 115] the first method for building ontologies was proposed by Uschold and King in [149] and later extended in [148]. The development process they proposed was based on experience gathered from developing the Enterprise Ontology [150]. Uschold et al.

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Figure 5.7: The ontologies development process proposed by Uschold and King [149] (Figure adapted from [60, p. 115].).

propose a process that consists of four phases. Fig. 5.7 shows the structure of the development process. The first phase consists of identifying the ontology’s purpose and scope. It aims at defining why is the ontology being built, what applications it has, and what the relevant terms of the domain will be. The second phase is building the ontology. As can be seen in Fig. 5.7, it is divided into three activities: the first is the ontology capture which deals with identifying the key concepts and relationships in the problem domain. The second activity is the coding, where the basic terms that will be used for specifying the ontology are committed; and where the actual ontology is implemented. The third activity is the integration of existing ontologies and deals with the way in which already existing ontologies are used in the developed ontology. The third phase in the proposed process is the ontology evaluation where a technical judge- ment is performed on the implemented ontology, its documentation and the associated software environment. The last phase is the ontology documentation where the guidelines for the docu- mentation are established.

As Gomez-Perez et al. [60, p. 119] explain, the main drawback in this method is that it lacks a concept phase before implementing the ontology. This leads to problems in understanding the ontology when based on its implementation. This in turn causes the inability of experts to build such ontologies in their domain of expertise. This is also one of the main drawbacks of the intuitive model development presented in Chapter 3.

5.2.3.2 On-To-Knowledge [136]

The On-To-Knowledge project’s [136] purpose was to apply ontologies to electronically available information in order to improve the quality of knowledge management in large and distributed organisations. Among other things the project includes a methodology for building ontologies. The proposed development process can be seen in Fig. 5.8. It consists of five

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Figure 5.8: The ontologies development process proposed by Staab et al. [136] (Figure adapted from [60, p. 147].).

phases, the first of which is the feasibility study where the problem is identified, as well as the most promising focus and the target solution. The second phase is the ontology kickoff where the ontology requirements are identified and specified together with the domain and the goal of the ontology, the design guidelines, the available knowledge sources, and the potential ontology users and use cases. Additionally, a baseline taxonomy is developed. The third phase is the ontology refinement where the goal is to create an application-oriented ontology based on the guidelines produced by the kickoff phase. This phase is divided into two activities: the first is the knowledge elicitation process with domain experts where the baseline taxonomy from phase two is further developed and refined. The second activity is the ontology formalisation where the ontology is implemented using the chosen ontology language. The language is selected based on the requirements of the application.

The fourth phase is the ontology evaluation and it deals with proving that the developed ontology and the corresponding software environment are serving their purpose. During this phase, two activities are executed: the first is checking the requirements and competency ques- tions derived in the second phase; and the second deals with testing the ontology in the target application environment. The last phase is the maintenance. In the On-To-Knowledge project it was proposed that the ontology maintenance is integrated in the system software [60, p. 146–148].

In difference with the methodology proposed by Uschold et al. [149], this one has a more extensive conceptualisation phase. However, it still suffers from the fact that earlier phases are not included into the iteration process, thus making it impossible to correct conceptual problems discovered at the later phases. On the other hand, similarly to the intuitive development process in Chapter 3, it defines the conceptual elements to be modelled and the requirements based on which the implementation language is selected. Additionally, the evaluation process here is nearer to that of activity recognition than the validation and verification processes typical for simulation and software engineering.

5.2.3.3 Methontology [48]

Methontology is a structured methodology for building ontologies from scratch proposed by Fernandez et al. [48]. It is based on the experiences made in developing an ontology in the domain of chemicals [48].

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Figure 5.9: The ontologies development process proposed by Fernandez et al. [48] (Figure adapted from [48] and [60, p. 127].).

Fig. 5.9 shows the lifecycle for developing ontologies. The first step that has to be per- formed before building an ontology is the planification where the ontology designer plans the main tasks that have to be executed, how they should be arranged, what time and resources are needed for each task. After the planning, the ontology development begins. There are six states (or phases) through which the developer should pass in order to create successful ontology. The first phase is the ontology specification which deals with the questions what is the purpose of

the ontology, what are the ontology applications, and what are the users of this ontology. The

second phase is the ontology conceptualisation where the problem to be solved and its solution are described. The conceptualisation is based on the problem specification and the knowledge acquired about the problem domain. The third phase is the formalisation of the ontology. In it the conceptual ontology is transformed into a formal model, in this case using description logic or frame oriented representation systems. The fourth phase is the ontology integration. The purpose of this step is to reuse already existing ontologies by integrating them into the ontol- ogy being built. The next phase is the ontology implementation. In it the formalised ontology is implemented in the selected formal language. The final phase is the ontology maintenance which deals with modifying or including new definitions to the ontology.

In parallel to the phases above, three more activities are executed. These are the knowledge

acquisition where the knowledge to be integrated into the ontology is elicited and where the

sources of this knowledge as well as the techniques used for acquiring it are listed. The second action is the process of documenting where each step of the development process is carefully documented for future ontology use or reuse. The last action is the ontology evaluation where the technical soundness and the applicability to the problem domain are proved. These three actions are executed throughout the whole development process and are not considered as sep- arate phases in the ontology development lifecycle.

In difference with the previous two methodologies, Methontology provides the option to iterate the process and to return to the early phases at any step of the development. This al- lows fixing conceptual problems that were not discovered during the early development stages. This also provides a better mechanism of adapting and evolving the ontology. Of course, the

methodology cannot be directly applied to the field of activity recognition as it has different objectives but the process can be adapted for the purposes of model based activity recognition. Furthermore, it does not concerns itself with developing the probabilistic model structure.