Integration Method of Business Vocabularies and

Business Rules Specifications (Models)

Edvinas Sinkevicius and Rimantas Butleris

Departament of Information Systems, Kaunas University of Technology, Studentu g. 50, Kaunas, Lithuania

1 STAGE OF THE RESEARCH

The stage of the research is in implementation of

merging algorithm of business vocabularies and

rules that will allow to merge several business

vocabularies and find conflicts that will be listed for

the user for further actions.

Online storage prototype for business process

vocabularies and business rules are implemented for

their management. Types of conflicts were identified

that could occur during vocabularies merging.

2 RESEARCH PROBLEM

Information system development starts from

defining business vocabulary and rules. There are

some cases when several business vocabularies and

rules from the same domain must be used. Therefore

there is a need to merge those business vocabularies

and rules to make one and use it for development of

a system.

The research problem is that there is a need to

use merged information from several business

vocabularies and rules. Merging them could cause to

occur conflicts between the elements from different

sources. To our knowledge, the problem yet is not

solved nor in the scientific literature nor in practical

applications.

3 OUTLINE OF OBJECTIVES

The goal of this research is to allow forming sets of

business rules, develop business vocabularies and

rules, configure and merge vocabularies and to

maintain interfaces with software models. In order to

do so, we have to develop an online access and

business process and business rules prototype based

on SBVR (Semantics of Business Vocabulary and

Rules) metamodel, ensuring the complete life cycle

of business vocabularies and rules.

The outline objectives are:

1. To identify business vocabularies and business

rules ensuring criteria that allows possibilities to

manipulate the elements of the vocabularies.

2. To estimate SBVR metamodel possibilities that

are needed for managing business vocabularies

and business rules.

3. To create vocabularies merging method and

carry out an experiment.

4. To prepare the management of architectural

framework for business vocabularies and

business rules storing.

5. To develop online access prototype that would

ensure the storage of business vocabularies and

business rules.

4 STATE OF THE ART

Analysis of related works showed that merging

whether it would be vocabularies, databases, web

services, etc., requires dealing with conflicts that

could occur due to different sources even if the

problem domain is the same. The method for

merging databases based on conflict solving is

presented by Parent et al. (Parent et al., 1998).

Semantic conflicts were solved during the exchange

of information through web services (Al-Baltah et

al., 2013). Furthermore, detailed semantic

classification was presented in the article. A

spreading activation model is proposed for the

purpose of automatically merging databases with

heterogeneous indexing systems by Lee (Lee, 1999).

Taxonomy of conflict problems in integrating

information resources using XML schema was

proposed (Lee et al., 2002). Term mapping process

is explained, but this method does not use conflict

solving because the information retrieval requires

term mappings. Ontologies merging problems by

means of definitions and terms were presented

(Kotis et al., 2006). Model-driven conflict

specification mechanism was presented, a conflict

metamodel has been proposed to specify conflict

patterns between different elements (Cicchetti et al.,

2008). The HCONE-merge approach was analysed

Sinkevicius E. and Butleris R..

Integration Method of Business Vocabularies and Business Rules Speciﬁcations (Models).

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

along with the other approaches to find the approach

that would allow merging with the minimum user

interaction. However, the results showed that human

interaction is necessary to produce valid mappings

between the ontologies. Merge algorithm was

presented which preserves context-free correctness

and detects context-free conflicts (Westfechtel,

1991). Formal approach to three-way merging of

models in the EMF framework which produces a

valid model, handles move operations, detects and

resolves context-free and context-sensitive conflicts

were presented by Westfechtel (Westfechtel, 2010)

Later, by the same author, formal and detail merging

techniques are presented (Westfechtel, 2014) listing

the conflicts and describing their solving solutions.

Method for three-way merging of XML was

presented, also, investigations were made for

number of cases on XML merging from which high-

level merge rules were derived (Lindholm, 2004).

An approach for computing differences between

UML models encoded as XMI files was presented

(Kelter et al., 2005), but the tests were performed

with not realistic examples, so they are not fully

comprehensive. Requirements for algorithms and

tools for differencing and merging of software

diagrams were defined (Förtsch et al., 2007). Also,

they have explored several crucial design decisions

which tool developers have to perform. Two

different kinds of conflicts in model versioning were

defined based on the notion of graph modifications:

operation-based and state-based conflicts (Taentzer

et al, 2010). An operation-based conflict detection

algorithm to detect conflicts in operations and

models was presented (Koegel et al., 2010) resulting

with operation-based conflict detection results in

less conflicts and requires fewer merges.

In many literature sources that explain merging

various technologies, solutions are missing for new

technologies or standards that should be used in

merging methods. Currently there are proposed

various new standards, as SBVR that allows

defining business vocabularies and rules that are

used in early stages of system development. SBVR

(Semantics of Business Vocabulary and Rules)

(OMG, 2008; OMG, 2013) allows to define business

process and business rules using Structured English.

As SBVR attracts more and more attention and it is

continually updated, this OMG (Object Management

Group) standard was selected for this research.

Online storage prototype for business

vocabularies and business rules was created on the

basis of VeTIS tool (Nemuraite et al., 2010; Sukys et

al., 2012) as an editor for business vocabulary and

rules.

5 METHODOLOGY

The current research is based on methodology of

finding all classified conflicts due to the different

sources of the same domain and using

transformation from SBVR vocabularies to OWL 2

(Web Ontology Language) ontologies in order to

detect inconsistencies. All the conflicts must be

listed to the user for further actions.

Semantic conflicts will be solved using

transformation from SBVR to OWL ontologies

(Karpovic et al., 2011; Karpovic et al., 2012). All

the other conflicts will be solved using primary

sources. To find inconsistencies in OWL 2

ontologies will be performed using Protégé Hermit

OWL Reasoner (ISG, 2012) or Protégé Pellet

Reasoner (Clarkparsia, 2013).

6 EXPECTED OUTCOME

The expected outcome of this research is to

implement a method that would allow performing

merging of several different vocabularies from the

same domain and finding all the conflicts that could

occur. For business vocabularies and rules

management online storage prototype must be

implemented.

7 APPROACH OF MERGING

SBVR VOCABULARIES OF

THE SAME DOMAIN

In this section we present the approach of merging

SBVR vocabularies of the same domain dealing with

several kinds of conflicts. Furthermore, online

storage prototype of SBVR vocabularies and rules is

presented.

7.1 SBVR Business Vocabularies and

Rules Management Method under

Implementation

While implementing business vocabulary and

business rules, several steps must be made. These

steps define all required actions in order to create

business vocabulary and rules for the examined

domain. Figure 1 presents those steps in an activity

diagram. In this diagram the activity “merge

vocabularies” is the activity which is examined in

detail (section 7.3) in order to create an algorithm

IntegrationMethodofBusinessVocabulariesandBusinessRulesSpecifications(Models)

Figure 1: Method of implementing business vocabularies and rules.

and the method for the possibility to merge several

vocabularies and rules and find conflicts that would

be presented to the user for further actions.

Needs for vocabularies merging could occur for

a variety reasons: due to several experts working on

the same project, due to the upgrade of the system,

due to automatic model transformations

(Mickeviciute et al., 2014) and etc.

7.2 Types of Conflicts While Merging

SBVR Vocabularies

While merging several business vocabularies and

business rules four types of conflicts could occur:

1. Structural conflicts

This type of conflicts could occur in two

different ways:

 When examined vocabularies are correct and

full, all the rules are defined:

e.g. vocabulary 1:

It is necessary that house has

at_most_1 color

e.g. vocabulary 2: It is necessary that house has

at_most_2 color

 When examined vocabularies are not full, then

we have to consider to the general rules:

e.g. when a person has just one date or birth.

2. Value conflicts

e.g. house has color

It is necessary that color is green or blue or...

It is necessary that house has at_most_1 color

The solution could be made that both rules are

left as they are and the additional rule is written:

e.g.

It is necessary that house is green or house is blue

This solution makes the given information fuzzy

and inaccurate.

3. Semantic conflicts

The word may have a meaning in the specific

context, e.g. roles, when a person is a driver if a

person drives a car:

e.g.

person

General concept: noun concept

driver

Concept type: role

General concept: person

One of the methods to define a conflict is to

perform transformation from vocabularies to

ontologies to check their consistency.

4. Naming conflicts

In the one vocabulary there will be a person, in

another vocabulary the same person may be

called client and etc. In this case their properties

overlap:

e.g.

person

client

In such cases synonymous forms should be used:

e.g. person

Synonym: client

7.3 Algorithm of Merging Vocabularies

This section of the paper explains the algorithm of

SBVR vocabularies merging. In order to do this,

there should be selected SBVR business

vocabularies from the same domain. All the other

steps are listed in the Figure 2.

As the Figure 2 shows, merging vocabularies are

IC3K2014-DoctoralConsortium

Figure 2: Algorithm of SBVR vocabularies merging.

transformed (Karpovic et al., 2011; Karpovic et al.,

2012) to OWL ontologies (W3C, 2012) to check for

their consistency. Located inconsistencies are solved

in the main merged vocabulary. If after the

transformation structural, value or naming conflicts

are still found, the whole sequence could be repeated

from the beginning using the main merged

vocabulary. In this algorithm are used three methods

of vocabularies merging: transforming to ontologies,

automated with presentation of results to the user for

validation and created by expert manually.

7.4 Online Storage Prototype for

Business Vocabularies and Rules

The online storage prototype for business

vocabularies and rules were implemented to create

and maintain business vocabularies. Use case

diagram of the implemented prototype is presented

in Figure 3. The vocabularies merging activity is

hidden under “Manage vocabularies, sets of rules

and projects” use case.

Interface of implemented tool is presented in Figure

4. Project and file browser is on the left side and

concept tree is given on the right side of the tool.

Other main functions are explained in the grey blocs.

Example of two vocabularies merging is given in

Figure 5. Different colours show different conflicts:

the same in different name (orange), added concept

(green), deleted concept (red). Vocabulary A and

Vocabulary B are from the same domain.

IntegrationMethodofBusinessVocabulariesandBusinessRulesSpecifications(Models)

Figure 3: Use case diagram of online storage prototype for business vocabularies and rules.

Figure 4: User interface of implemented tool for business vocabularies and business rules management.

8 CONCLUSIONS AND FUTURE

WORKS

According to the analysis of related works about

SBVR metamodel and other possible model storage

ways the decision was made that the best storage

way of SBVR model is with structured natural

language. Merging problems of vocabularies were

defined and SBVR vocabularies merging rules were

created. Four main vocabularies merging conflicts

were defined: structural, value, semantic and

naming. Three methods of vocabularies merging

were identified: transforming to ontologies,

automated with presentation of results to the user for

validation and created by expert manually. All of

these methods are included in new proposed method.

Management of architectural frame for business

vocabularies and business rules storing was prepared

and online access ensuring business vocabularies

and business rules storage prototype was developed.

Project and file

browser

Search result

screen

Main menu

Business vocabulary and

rules editing screen

Concept tree of

business vocabulary

IC3K2014-DoctoralConsortium

Figure 5: Two vocabularies after merging: colours show difference.

The future work of this research is devoted for

implementing merging method of business

vocabularies. Further, the will be carried out an

experiment to test the new method.

REFERENCES

Al-Baltah, I. A., Ghani, A. A. A., Rahman, W. N., W. AB,

Atan, R, 2013: A Classification of Semantic Conflicts

in Heterogenous Web Services at Message-level.

Turkish Journal of Electrical Engineering and

Computer Science.

Cicchetti,A., Di Ruscio,D., Pierantonio, A., 2008:

Managingmodel conflicts in distributed development.

In: Czarnecki, K., Ober, I., Bruel, J.-M., Uhl, A.,

Völter, M. (eds.) Proceedings of the 11th International

Conference on Model Driven Engineering Languages

and Systems (MoDELS 2008). Lecture Notes in

Computer Science, Toulouse, France, vol. 5301, pp.

311–325. Springer, Berlin.

clarkparsia, 2013: Pellet Reasoner Plug-in for Protégé 4,

clark&parsia. http://clarkparsia.com/pellet/protege/.

Förtsch, S.,Westfechtel, B., 2007: Differencing and

merging of software diagrams—state of the art and

challenges. In: Filipe, J., Helfert, M., Shishkov, B.

(eds.) Proceedings of the Second International

Conference on Software and Data Technologies

(ICSOFT 2007), Barcelona, Spain, pp. 90–99.

INSTICC Press, Valencia.

ISG, 2012: HermiT OWL Reasoner, Information System

Group, Overview. http://hermit-reasoner.com/.

Karpovic, J., Nemuraite, L., 2011: Transforming SBVR

Business semantics into Web Ontology Language

OWL2: Main Concepts. In proceeding of 17th

International Conference on Information and Software

Technologies IT.

Karpovic, J., Nemuraite, L., Stankeviciene, M., 2012:

Requirements for Semantic Business Vocabularies and

Rules for Transforming Them into Consistent OWL2

Ontologies. Communications in Computer and

Information Science, Vol 319, pp. 420-435.

Kelter, U., Wehren, J., Niere, J., 2005: A generic

difference algorithm for UML models. In:

Liggesmeyer, P., Pohl, K., Goedicke, M. (eds.)

Software Engineering 2005. Lecture Notes of

Informatics, Essen, Germany, vol. P-64, pp. 105–116.

Gesellschaft für Informatik.

Koegel, M., Hermannsdoerfer, M., von Wesendonk, O.,

Helming, J., 2010: Operation-based conflict detection.

In: Di Ruscio, D., Kolovos, D.S. (eds.) Proceedings of

the 1st InternationalWorkshop on Model Comparison

in Practice (IWMCP 2010), Malaga, Spain. ACM

Press, New York, pp. 21–30.

Kotis, K., Vouros G. A., Stergiou, K., 2006: Towards

Automatic Merging of Domain OntologiesL The

HCONE-merge approach. Journal of Web Semantics,

Vol 4, No 1.

Lee, J., 1999: A Apreading Activation Model for

Vocabulary Merging. Graduate School of Library and

Information Science University of Illinois at Urbana-

Champaign.

Lee, K. H, Kim, M. H., Lee, K. C, Kim, B. S, Lee, M. Y,

2002: Conflict Classification and Resolution in

Heterogeneous Information Integration based on XML

Schema. In proceeding of IEEE Region 10 Conference

on Computers, Communications, Control and Power

Engineering, Vol 1, pp. 93-96.

Lindholm, T., 2004: A Three-way Merge for XML

Documents. In proceeding of the 2004 ACM

symposium on Document engineering, ISBN: 1-

58113-938-1, New York, USA.

IntegrationMethodofBusinessVocabulariesandBusinessRulesSpecifications(Models)

Mickeviciute, E., Nemuraite, L., Butleris, R., 2014b:

Applying SBVR Business Rules Vocabulary and

Business Rules for Creating BPMN Process Models.

In proceedings of International Conference on

Workshop on Applications of Knowledge-Based

Technologies in Business – AKTB 21-23 May, 2014,

Larnaca, Cyprus.

Nemuraitė L., Skersys T., Šukys A., Šinkevičius E.,

Ablonskis L., 2010: VETIS tool for editing and

transforming SBVR business vocabularies and

business rules into UML&OCL models. // Information

Technologies' 2010 : proceedings of the 16th

international conference on Information and Software

Technologies, IT 2010, Kaunas, Lithuania, April 21-

23, Kaunas : Technologija. ISSN 2029-0020. 2010,

pp. 377-384.

OMG, 2008: Semantics of Business Vocabulary and

Business Rules (SBVR) specification. Version 1.0.

OMG Document Number: formal/2008-01-02.

OMG, 2013: Semantics of Business Vocabulary and

Business Rules (SBVR) specification. Version.1.1,

OMG Document Number: formal/2013-09-04.

Parent, C., Spaccapietra, S., 1998: Issues and Approaches

of Database Integration. Communications of the

ACM, Vol 41, issue 5, pp. 166-178.

Šukys A., Nemuraitė L., Paradauskas B., Šinkevičius E.,

2012: Transformation framework for SBVR based

semantic queries in business information systems //

Bustech 2012 : the second International Conference on

Business Intelligence and Technology, July 22-27,

2012, Nice, France. [S.l.]: IARIA, 2012. ISBN

9781612082233, pp. 1-6.

Taentzer,G., Ermel, C., Langer, P.,Wimmer, M, 2010.:

Conflict detection for model versioning based on

graph modifications. In: Ehrig, H., Rensink, A.,

Rozenberg, G., Schürr, A. (eds.) ICGT 2010—Graph

Transformations, 5th International Conference.

Lecture Notes in Computer Science, vol. 6372, pp.

171–186. Enschede, The Netherlands.

W3C, 2012: OWL 2 Web Ontology Language (OWL),

W3C Recommendation. Second ed. http://www.

w3.org/TR/2012/REC-owl2-overview-20121211/.

Westfechtel, B., 1991: Structure-Oriented Merging of

Revisions of Software Documents. In proceedings of

the 3rd international workshop on Software

configuration management, pp. 68-79.

Westfechtel, B., 2010: A Formal Approach to Three-Way

Merging of EMF Models. In proceeding of the 1st

International Workshop on Model Comparison in

Practice, pp. 31-41.

Westfechtel, B., 2014: Merging of EMF models. In

proceedings of Software & Systems Modeling, Col 13,

issue 2, pp. 757-788.

IC3K2014-DoctoralConsortium