MICROORGANISMOS ELECTROGÉNICOS EN LAS CCMS

It is important to clarify at this point the terms that are used in the EAGQ method as well as their relations with the ArchiMate® concepts. The new terms introduced are the terms: ‘Indicator’, ‘Measure’ and ‘Data’. These terms have been used for grouping the steps in the EAGQ method (Figure 47) and they also refer to the two separate domains of Figure 46. Thus, the indicators and measures facilitate the analysis in the goal level, while the data and measurements represent the analysis in the EA level.

The definitions of the terms ‘indicator’ and ‘measure’ are based on the SMO definitions provided in Table 23, while the term ‘data’ refers to input values used in the measurements. In Table 23, the term ‘measure’ is further refined in ‘base measure’ and ‘derived measure’. In the EAGQ method, this differentiation between types of measures is not going to be used. Additionally, the SMO distinguishes ‘measurement approaches’ as measurement methods and functions, which correspond accordingly to the base and derived measures. Both differentiations are considered confusing. The aim of the EAGQ method is to introduce the necessary concepts for performing the measurement in the EA level and the analysis in the goal level, while avoiding additional complexity. Therefore, the terminology used in the method is presented in Table 30. The definitions for the terms ‘measure’ and ‘measurement approach’ are derived from the definitions in Table 23. Additionally, as far as the ‘analysis model’ is concerned, the definition provided in Table 30 is a result of the definition in Table 23, but it also aligns with the definition of the ‘analysis model’ discussed by Jansen et al. [36] as part of the Quantitative Analysis Process (Table 8). The diagram in Figure 48 provides the relations between the terms.

Term Definition

Measure A measure of an attribute which is a result of a measurement approach. A measure can be also calculated by using other measures.

Indicator A measure that is derived from other measures using an analysis model. Measurement

approach

The measurement method used for calculating the value of a measure. It comprises a set of operations as well as an algorithm or a calculation formula. Defining the measurement approach also includes the measurement scale. Analysis

model

An analysis model is a generalization of a measurement approach. The analysis model includes a measurement approach for calculating the value of an indicator and decision criteria for performing the analysis of the calculated value.

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Measurement approach Analysis model Indicator Measure measured by measured by subtype of used by computed by computed by

Figure 48 - Relations between terms in the EAGQ method

A proposal of the correlation between concepts of the goal model and the EA model and the terms ‘Indicator’, ‘Measure’ and ‘Data’ is presented in Figure 49. The indicators, as it has been explained, correspond to ‘goals’. The measures, though, correspond to ‘requirements’ and derive information from EA concepts.

The term ‘requirement’ in ArchiMate 2.1 Specification [17] is defined as “a statement of need that must be realized by a system”. The fact that requirements provide more precise information regarding the change in stake and the needs that the target EA should fulfill, makes it an ideal concept for representing the measurement needs imposed by the goals. Thus, requirements serve as intermediaries for translating the goals into system needs, while the measures serve as the intermediaries for translating the indicators into measurement needs. The measures corresponding to requirements, though, need to be derived from the EA model. The measures in the requirement-level are usually more complex measures, which are calculated from other simpler measures, which are called component measures for clarifying the relationship between them. Hence, the requirement-level provides the point where the aggregation of the measurements occurs.

The measurement approaches of the measures are the focus of the ‘Data Measurements’ box in Figure 47. The measurements are performed in the EA model and the term ‘data’ corresponds to any kind of concept in the EA model which realizes a specific requirement. To put it differently, as the EA concepts realize the requirements, the data are the input values used for computing the measures related to the requirements. The source of the data lies on the concepts participating in the measurements.

In the next sections, every step of the EAGQ method and its corresponding activities are presented and analyzed. Overall, the method aims to assist and guide the quantitative analysis of change in order to justify its contribution to fulfilling the goals. The quantitative analysis in the goal domain is achieved by taking into consideration the current situation, as represented by the Baseline EA model, and comparing it with estimations of the expected results that the transformation will cause. The comparisons are performed based on data populations of the EA models and quantifications on these data.

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5. An EA-based Goal Quantification Method