- The main scope is to present UML Information Flow model generation from Enterprise model (EM) transformation algorithm. The transformation algorithm description is presented in details and depicted steps. Whole generation process steps are illustrated by particular example following the transformation algorithm step by step.
Keywords – Enterprise Model, Knowledge-based, IS Engineering, UML, Information Flow, Information Item.
There have been quite many attempts for the analysis of
UML models generation from different knowledge based
models combining other modelling languages, workflow
patterns and frameworks or even generation from natural
language specifications [
UML models are receiving an increasing attention from
researchers in the recent years. It is a very challenging target
for analysis of UML models since the knowledge about an
enterprise system is allocated within several model views.
UML models are maintained to decrease the confusion of the
problem with the increase enterprise changes. By operating
UML models knowledge can be effectively expressed and can
be used simply in all phases of IS development life cycle [
UML as one of the main components of IS development life cycle phase models, can be generated in semi-automatic way from knowledge repository – Enterprise model. This kind of realization will improve the efficiency of these participants of information system development process: system analyst and/or system designer and/or system developer.
II. ENTERPRISE MODEL ELEMENTS ROLE VARIATIONS
Enterprise meta-model is formally determined enterprise
model composition, which contained of a formalized enterprise
model alongside with the general principles of control theory.
Enterprise model is the main source of the requisite knowledge
of the specific problem domain for IS engineering and IS
reengineering processes [
meta-model manages Enterprise model
composition. Enterprise model stores knowledge that is
necessary for IS development process only and will be used
during all phases of IS development life cycle [
There is given formalized Enterprise meta-model
description, which is needed to define UML Information Flow
model generation process algorithm. Enterprise model can be
described as Malcev algebra based algebra system (Fig. 1) [
M1=<K, R> (1) where M1 – Enterprise model as algebra system; K – elements set of M1 system; K={K1, K2,…, K21}, where K1,....K21 EM meta-classes; R – set of relationships between elements, where R={r1, r2, r3}.
For each set of K element Kn composition is defined as: Kn=<{an1, an2,…,ank}, {mn1, mn2,…,mnl}>, where {an1, an2,…,ank} – attributes of Kn element, {mn1, mn2,…,mnl}– methods of Kn element.
Enterprise model M1 composition is as follows:
M1=<{K1, K2,...,K21}, {r1, r2, r3}> (2) where: K1 – meta-class Process, K2 – meta-class Function, K3 – meta-class Actor, K4 – meta-class Event, K5 – meta-class Goal, K6 – meta-class Material Flows, K7 – meta-class Input Material Flow, K8 – meta-class Output Material Flow, K9 – meta-class Information Flow, K10 – meta-class Interpretation, K11 – meta-class Data Processing and Solution Making, K12 – meta-class Realization, K13 – meta-class Information Activity, K14 – meta-class Business Rules, K15 – meta-class Interpretation Business Rules, K16 – meta-class Data Processing and Solution Making Business Rules, K17 – metaclass Realization Business Rules, K18 – meta-class Process Output, K19 – meta-class Information processing Input Attributes, K20 – meta-class Information processing Output Attributes, K21 – meta-class Process Input, r1 – Aggregation, r2 – Generalization, r3 – Association.
Information systems design methods indicates the
disposition of systems engineering actions, i.e. how, in what
order and what UML model to use in the IS development
process and how to implement the process (Table 1). Majority
of them are based on different types of models describing
varying aspects of the system qualities. Meaning of each model
can be defined individually, but more important is the fact that
each model is the projection of the system. An inexperienced
specialist can use UML models inappropriately and the
description of the system will possibly be insufficient or even
mistaken [
Determining specific UML model and selecting the initial
model element is reasonably meaningful, because further
generating process relies on it. Many UML model elements
iterates in different UML model, but these elements describe
different aspects of the system. In example Enterprise model
element Business rule has different signification in different
UML models [
When Enterprise model as enterprise knowledge storage allows – the stored knowledge is sufficient, validated and verified – to generate UML models applying transformation algorithms. This kind storage can be used not only for knowledge of the enterprise gathering, but also as a tool that minimizes IS reengineering volume of work if any changes occur in an enterprise. UML models generation from Enterprise model is implementation of knowledge based IS development life cycle design phase.
Transformation algorithm of UML models generation from Enterprise model is top level algorithm for enterprise metamodel based UML model generating process (Fig. 2). Main steps for generating process are identifying and selecting UML model for generating process, identifying starting (initial) element for the selected UML model and selecting all elements related to this UML model, generating enterprise model elements to UML model elements and generating the whole UML model.
There is given formalized UML Information Flow model
description. UML Information Flow also can be described as
Malcev algebra based algebra system (Fig. 3) [
M4=<K,R> (3) where M4 – UML Information Flow model as algebra system; K – elements set of M4 system; K={K34, K35,…, K37}, where K34,....K37 UML Information Flow meta-classes; R – set of relationships between elements, where R={r1, r2, r3}.
UML Information Flow M4 composition is as follows: M4={K34, K35,…, K37},{r2},{r3}> (4) where: K34 – meta-class Actor, K35 – meta-class Class, K36 – meta-class Information Flow, K37 – meta-class Information Item, r2 – Generalization, r3 – Association. entities at some high levels of abstraction and it is directly related with UML Class and Use Case models (Fig. 4). This model describes information flows and provides information to Class and Use Case models. Information flows can be useful to describe circulation of information through a system. These flows represents aspects of models not yet completely specified or with less details.
Formal description φ1: K3→K34 φ1: K1→K35
According to the figure 3 it is clear that Enterprise model elements: Actor, Process, Function, Information Flow, Information processing Input Attributes, Information processing Output Attributes can be generated as UML Information Flow model elements: Actor, Class, Information Flow, Information Item.
A. UML Information Flow Model Transformation Algorithm
UML Information Flow Model belongs to dynamic UML models part and shows exchange of information among system
Transformation algorithm of UML information Flow model generation from Enterprise model process is presented in the figure (Fig. 5) and is illustrated by following steps:
Step 1: According to the top level transformation algorithm of UML models generation from EM process, UML Information Flow model is identified for the generation process. So the initial element for UML Information Flow model is Actor element.
Step 2: UML Information Flow model Actor element is generated from Enterprise model.
Step 3: Process element from Enterprise model which is related with the initial actor element is selected.
Step 4: UML Information Flow model Class element is generated from Enterprise model.
Step 5: Information Flow element as link of other elements from Enterprise model which is related with the process element is selected.
Step 6: UML Information Flow model Information Flow element as link of other elements is generated from Enterprise model.
Step 7: Information processing Input Attributes element as definition of link element from Enterprise model which is related with the process element is selected.
Step 8: If UML Information Flow model Information item element is definition of link to next element then it is generated from Enterprise model.
Step 9: Else Information processing Output Attributes element as definition of link to previous element from Enterprise model is selected.
Step 10: UML Information Flow model Information item element as definition of link to previous element is generated from Enterprise model.
Step 11: UML Information flow elements Information item and Information Flow are linked.
Step 12: UML Information flow elements Information Flow and Class are linked.
Step 13: There is checking if there are more Information flows in Enterprise model related to UML Information Flow model. In case, there are, algorithm goes back to step 5.
Step 14: UML Information flow elements Class and Actor are linked.
Step 15: There is checking if there are more Processes in Enterprise model related to UML Information Flow model. In case, there are, algorithm goes back to step 3.
Step 16: UML Information flow element Actor is updated.
Step 17: There is checking if there are more Actors in Enterprise model related to UML Information Flow model. In case, there are, algorithm goes back to step 1.
Step 18: Else all UML Information Flow model elements and links are generated from Enterprise Model.
B. Generated UML Information Flow Model Example
Generation of UML Information Model is illustrated with
the example of Scheduled workflow for Ultrasound
examination for the pet in Veterinary clinic [
Detailed stages of Veterinary clinic example processes stored in Enterprise model are described: Stage 1 – Pet owner registers his pet in veterinary clinic registration system. Information system manages pet owner registration and services ordering and is responsible for updating information. Stage 2 – Pet registration information from veterinary clinics registration system is connected to ultrasound examination registration system. System manages examination order scheduling. Stage 3 – Data gaining system acquires and creates medical data while a pet is present (in example: ultrasound, tomography etc.) Stage 4 – Data storage system manages examination data storage and sharing inside Veterinary clinic. Stage 5 – Surgeon gets data from data storage system, evaluates it through reviewing and evaluating system and prepares diagnosis response. Stage 6 – Veterinary gets diagnosis response prepared by surgeon through reviewing and evaluating system. Stage 7 – Pet owner gets diagnosis information during the appointment with veterinary.
Transformation algorithm of UML Information Flow model generation of stage 1 of Scheduled workflow for Ultrasound examination for the pet in Veterinary clinic example from Enterprise model process is illustrated by following steps:
Step 1: Selected initial element for UML Information Flow model is Actor element.
Step 2: UML Information Flow model Actor element is generated from Enterprise model, in certain example first actor is Pet owner.
First two steps of transformation algorithm is presented in table 4.
Step 3: Process element from Enterprise model which is related with the initial actor element is selected.
Step 4: UML Information Flow model Class element is generated from Enterprise model, in certain example first class is Pet registration. Step 5: Information Flow element as link of other elements from Enterprise model which is related with the process element is selected.
Step 6: UML Information Flow model Information Flow element as link of other elements is generated from Enterprise model, in certain example first Information flow is between Pet owner and Pet registration. Step 7: Information processing Input Attributes element as definition of link element from Enterprise model which is related with the process element is selected.
Step 8: If UML Information Flow model Information item element is definition of link to next element then it is generated from Enterprise model in certain example first Information item is Pet information.
Step 9: Else Information processing Output Attributes element as definition of link to previous element from Enterprise model is selected. Step 10: UML Information Flow model Information item element as definition of link to previous element is generated from Enterprise model.
Step 11: UML Information flow elements Information item and Information Flow are linked. Step 12: UML Information flow elements Information Flow and Class are linked.
Step 12 of transformation algorithm is presented in table 9. Step 13: There is checking if there are more Information flows in Enterprise model related to UML Information Flow model. In case, there are, algorithm goes back to step 5. All steps form the 5 are repeated.
Next two (in other case three) steps of transformation algorithm is presented in table 7.
Step 13 of transformation algorithm is presented in table 10, showing the result after repetition steps from step 5.
Step 14: UML Information flow elements Class and Actor are linked, in certain example Pet owner is linked to pet registration.
Step 14 of transformation algorithm is presented in table 11, showing the result after repetition steps from step 5.
After 14 steps of the transformation algorithm generating of Scheduled workflow for Ultrasound examination for the pet in Veterinary clinic data from Enterprise model the 1 stage – pet owner registers his pet in veterinary clinic registration system. Information system manages pet owner registration and services ordering, is responsible for updating information – is shown in the figure.
Full UML Information flow model after all steps of the transformation algorithm generating Scheduled workflow for Ultrasound examination for the pet in Veterinary clinic example is shown in the figure.
After the implementation all the steps of transformation algorithm it can be undoubtedly declared that chosen example perfectly illustrates accuracy of the UML Information flow elements generated from Enterprise model.
In the first part of the article the Enterprise model elements role variations possibilities in UML dynamic models generating process and top level of transformation algorithm are presented.
The next part handles with detailed explanation of UML Information model transformation algorithm, which is depicted by steps.
In the next part there is presented particular example, which data is stored in knowledge based Enterprise model and there are described all the stages of the example.
Final part describes transformation algorithm steps for the UML Information Flow model generation from The Enterprise model and illustrates it with graphical schemes.
The illustrated example shows that data stored in Enterprise model is sufficient for generating process and it is possible to claim, that every element of UML dynamic models can be generated from the Enterprise model using transformation algorithms and this can accomplish knowledge based IS development cycle design phase.