Žinių naudojimo verslo informacinėse sistemose tyrimas ; Investigation of knowledge use in business information systems

Irma Sztáray

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Irma Valatkait INVESTIGATION OF KNOWLEDGE USE IN BUSINESS INFORMATION SYSTEMS Summary of Doctoral Dissertation Technological Sciences, Informatics Engineering – 07T 1031 Vilnius „Technika“ 2004 VILNIUS GEDIMINAS TECHNICAL UNIVERSITY Irma Valatkait INVESTIGATION OF KNOWLEDGE USE IN BUSINESS INFORMATION SYSTEMS Summary of Doctoral Dissertation Technological Sciences, Informatics Engineering – 07T Vilnius „Technika“ 2004 Doctoral dissertation was prepared at Vilnius Gediminas Technical University in 2000-2004.

Sujets

• Business rule
• Conceptual graph
• Informatics engineering

Informations

• Publié par: vilnius_gediminas_technical_university
• Publié le: 01 janvier 2004
• Nombre de lectures: 18

Extrait

 

 

    Irma Valatkait
          INVESTIGATION OF KNOWLEDGE USE IN BUSINESS INFORMATION SYSTEMS     Summary of Doctoral Dissertation Technological Sciences, Informatics Engineering – 07T                           Vilnius „Technika“ 2004

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VILNIUS GEDIMINAS TECHNICAL UNIVERSITY             Irma Valatkait
            INVESTIGATION OF KNOWLEDGE USE IN BUSINESS INFORMATION SYSTEMS         Summary of Doctoral Dissertation Technological Sciences, Informatics Engineering – 07T                                 Vilnius „Technika“ 2004

Doctoral dissertation was prepared at Vilnius Gediminas Technical University in 2000- 2004.     Scientific Supervisor: Prof Dr Olegas Vasilecas (Vilnius Gediminas Technical University, Technological Sciences, Informatics Engineering – 07T)     The dissertation is defended at the Council of Scientific Field of Informatics Engineering at Vilnius Gediminas Technical University:   Chairman:  Prof Dr Habil Gintautas Dzemyda (Institute of Mathematics and Informatics, Technological Sciences, Informatics Engineering – 07T)   Members: Prof Dr Habil Petras Gailutis Adom
nas (Vilnius Gediminas Technical University, Technological Sciences, Informatics Engineering – 07T) Prof Dr Habil Genadijus Kulvietis (Vilnius Gediminas Technical University, Technological Sciences, Informatics Engineering – 07T) Prof Dr Habil Ignas Skuas (Vytautas Magnus University, Technological Sciences, Informatics Engineering – 07T) Assoc Prof Dr Regina Kulvietien
(Vilnius Gediminas Technical University, Technological Sciences, Informatics Engineering – 07T)   Opponents:  Prof Dr Habil Rimantas Šeinauskas (Kaunas University of Technology, Technological Sciences, Informatics Engineering – 07T) Prof Dr Habil Narimantas Paliulis (Vilnius Gediminas Technical University, Social Sciences, Management and Administration – 03S)     The dissertation will be defended at the public meeting of the Council of Scientific Field of Informatics Engineering in the Senate Hall of Vilnius Gediminas Technical University at 1 p.m. on October 8, 2004. Address: Saul
tekio al. 11, LT-10223 Vilnius-40, Lithuania Tel. [phone], fax [phone] E-mail [e-mail].     The summary of the doctoral dissertation was distributed on September 7, 2004     A copy of the doctoral dissertation is available for review at the Library of Vilnius Gediminas Technical University (Saul
tekio al. 14, Vilnius).   © I. Valatkait
, 2004

 

VILNIAUS GEDIMINO TECHNIKOS UNIVERSITETAS           Irma Valatkait
            ŽININAUDOJIMO VERSLO INFORMACINSE SISTEMOSE TYRIMAS         Daktaro disertacijos santrauka Technologijos mokslai, informatikos inžinerija – 07T                                 Vilnius „Technika“ 2004

Disertacija rengta 2000−2004 m. Vilniaus Gedimino technikos universitete.     Mokslinis vadovas: prof. dr. Olegas Vasilecas (Vilniaus Gedimino technikos universitetas, technologijos mokslai, informatikos inžinerija – 07T).     Disertacija ginama Vilniaus Gedimino technikos universiteto Informatikos inžinerijos mokslo krypties taryboje:   Pirmininkas:  prof. habil. dr. Gintautas Dzemyda (Matematikos ir informatikos institutas, technologijos mokslai, informatikos inžinerija – 07T).     Nariai: prof. habil. dr. Petras Gailutis Adom
nas (Vilniaus Gedimino technikos universitetas, technologijos mokslai, informatikos inžinerija – 07T), prof. habil. dr. Genadijus Kulvietis (Vilniaus Gedimino technikos universitetas, technologijos mokslai, informatikos inžinerija – 07T), prof. habil. dr. Ignas Skuas (Vytauto Didžiojo universitetas, technologijos mokslai, informatikos inžinerija – 07T), doc. dr. Regina Kulvietien
(Vilniaus Gedimino technikos universitetas, technologijos mokslai, informatikos inžinerija – 07T).   Oponentai: prof. habil. dr. Rimantas Šeinauskas (Kauno technologijos universitetas, technologijos mokslai, informatikos inžinerija – 07T), prof. habil. dr. Narimantas Paliulis (Vilniaus Gedimino technikos universitetas, socialiniai mokslai, vadyba ir administravimas – 03S).     Disertacija bus ginama viešame Informatikos inžinerijos mokslo krypties tarybos pos
dyje 2004 m. spalio m
n. 8 d. 13 val. Vilniaus Gedimino technikos universiteto senato pos
dži   sal
je.   Adresas: Saul
tekio al. 11, LT-10223 Vilnius-40, Lietuva Tel.: [phone], faksas [phone] El. p. [e-mail]     Disertacijos santrauka išsiuntin
ta 2004 m. rugs
jo m
n. 7 d.      Disertacij perži galimar
ti Vilniaus Gedimino technikos universiteto bibliotekoje (Saul
tekio al. 14, Vilnius).  

VGTU leidyklos „Technika“ 1031 mokslo literatros knyga © I. Valatkait
, 2004

GENERAL DESCRIPTION   Problem topicality The last decade may be characterized as the time of explicitly addressing knowledge issues at all levels: business organizations core assets are centered on their core competencies expressed and stored explicitly as business knowledge, business information systems (IS) employing knowledge based technologies in serving the daily business organizations needs, the society itself aiming and actually taking steps towards knowledge society. Todays society is referred to as the “knowledge society” indicating that in modern world the professionalism (under professionalism meaning the understanding of knowledge processes, knowledge structure, and knowledge use) is regarded as the main practical issue. Knowledge orientation and wide-spread knowledge use propels creation and usage of intelligent information systems with the ability to process not only data, but also information and knowledge contained and used in business processes. With the above stated aim in mind IS development research has started using the notions of knowledge representation, knowledge modeling, knowledge processing, ontologies, data or knowledge mining, and knowledge discovery, intelligent systems, agents and intelligent agents, etc. The majority of these notions are not novel, however, recently they have started to be successfully analyzed and employed in IS applied in real business environment. In such circumstances in the research of the business IS development the business rules approach has achieved a lot of attention and already has a steady niche with a strong motivation behind. As the success factors may be mentioned the following. First, knowledge stated explicitly is considered as the asset that must be accumulated, stored, used and possibly even sold; knowledge is also considered as the intellectual capital of their owners. Second, in the set of successful business resources knowledge is one of the most valuable ones, stating the rules of driving the business. Third, rapidly evolving intelligent business IS development technologies supported by corresponding computer hardware technologies enable business organizations to manage their business knowledge as effectively as any other type of assets thus supporting knowledge use for creating business value. These factors not only necessitate the importance of knowledge use in business organizations, but also oblige researchers to innovate on intelligence in business IS engineering technologies, methods and techniques, such, that would enable the ultimate goal of business organizations – to be fast and adaptive. The imperative property of such technologies, methods, and techniques is the direct application for use in real business organizations.   In such a context the most important task is to map real world knowledge to computable form that enables business organizations to accumulate their business knowledge and use it effectively in order to make visible the individual policies that the organization puts in place as a guide to accomplish its goals and enable to fine-tune itself to the ever-changing business environment thus becoming faster and more responsive than its competitors.   The main objectives The main objective is to develop knowledge based business IS development methods and techniques satisfying business IS requirements; the main of the requirements being  5

business representatives ability to adapt the business IS to the rapidly changing business environment by themselves without any software development efforts by the means of the automatic model implementation mechanism. To achieve the stated objective the following tasks must be performed: 1. to analyze knowledge based business IS development technologies; 2. to analyze the knowledge based business IS development methods and techniques that enable business representatives to be active participants of the business IS development process and later to be able to modify and maintain the business rules set by themselves throughout the different stages of the IS life cycle; 3. to analyze different languages intended for business knowledge (including business knowledge structured as business rules) representation and formulate the requirements for business rules modeling language; 4. to choose the suitable business rules modeling language and motivate the choice according to the analysis results. The chosen language should support the possibility of automatic business rules model implementation; 5. to propose the method for automatic implementation of the business knowledge represented as business rules, model; 6. to implement the proposed mechanism of the automatic implementation of the business rules model in the selected modeling language and carry out the experiment with the representative example.   The methods of research The analysis of modeling languages, methods, techniques, tools, etc. used for knowledge based IS development was performed using literature review and comparative analysis. The business IS development methods were analyzed and developed using methods of logical induction, notions generalization, and conceptual modeling. Implementation of the proposed methods was created suing conceptual modeling and construction methods.   Novelty of results Although the notion of knowledge in the research on IS development is present for over a decade, the knowledge based IS development technologies and related notions, methods, and tools are not yet systematically classified and widely used. Business rules approach to IS development as the practically applicable knowledge based IS development technology is the hot research topic – the business rules based IS architectures are proposed, the notion and semantics of business rule are discussed, the modeling languages and their extensions for business rules modeling and standard interchange formats are developed. To discuss the above mentioned topics international scientific conferences are being held, initiatives combining research and business representatives are being created (e.g.,Rule Markup Initiative, Object Management Group Business Rules Working Group, etc.).GUIDE   Business Rules Project(later known asBusiness Rules Group) with the aim to systematize business rules, related notions, and methods was launched in 1993. However, their final report was published only in 2000. The results included business rule notion, business rule conceptual model, business rules types and modeling possibilities. The work started by Business Rules Groupare currently being continued and extended by a number of authors, institutions, even commercial organizations. In 2002Object Management Group has released the Request for Information on business rules.  6

In our research we have given the survey on knowledge based IS development technologies and knowledge modeling languages. Based on this survey we have proposed the requirements for the knowledge modeling language and selected conceptual graphs as the modeling language satisfying the formulated requirements. Although conceptual graphs as the modeling language is not a new one, the application of the language for business knowledge, stated as business rules, modeling is a novel approach. In order to improve the business rules modeling process and the usability of the model we have proposed the extension of conceptual graphs – the business rules modeling template. The usage of the template has enabled us to define and develop the automatic implementation component of business rules model in conceptual graphs. To achieve this aim, the method of automatic active databases triggers generation is proposed. Based on these results we have developed the framework for business IS development based on business rules approach.   Practical significance of results In the research of the business IS development the business rules approach has achieved a lot of attention and already has a steady niche with a strong motivation behind. The usefulness of the approach and its advantages over the traditional IS development approaches call for the technology standards. Despite the work done towards standardization there is still a way to go – commercial products use their unique modeling languages for business rules, most of their rules processing and enforcement engines are stand-alone, even the embeddable ones use their unique rules representation format. In our research focusing on the business rules we have stepped towards employing the widely spread technology of active databases and have argued that it is feasible and possible to model business rules using conceptual graphs. Such a model having representations in visual and textual form (linear form and CGIF) and the possibility to translate the model to the near natural English language can be used both at conceptual and implementation levels. We have designed and implemented the automatic trigger generation component. Using the representative example from the real business organization (the representative example was comprised of structural domain knowledge and corresponding business rules) we have carried out the experiment during which the business rules model was transformed from visual notation to CGIF, then from CGIF to XML, and then from XML to MS SQL Server trigger. The experiment results have proven that using the proposed modeling language – conceptual graphs – with the proposed extension can be used for business rules modelling and the resulting business rules model can be successfully employed for automatic business rules model implementation using active databases. The advantages of the approach are several: 1. Business rules modeling language – conceptual graphs – is flexible and usable at different levels of practical IS development activities; 2. Business rules repository in XML format offers extension points and rules exchange / sharing possibilities; 3. The wide spread technology of active databases is used for rules enforcement instead of dedicated technologies and tools thus easing incorporation of the approach into the real business applications.   Scientific approval and contribution of the results The main results of the doctoral dissertation are published in 9 scientific papers [1-9].  7

The contributed talks were given at 8 conferences: 1. Lietuvos mokslas ir pramon
: Informacin
s technologijos, 2002, Kaunas, Lithuania 2. Lietuvos matematikdraugijos XLIII konferencija, 2002, Vilnius, Lithuania 3. Eleventh International Conference on Information Systems Development ISD2002, Riga, Latvia 4. Seventh East-European Conference on Advance in Databases and Information Systems ADBIS2003, Dresden, Germany 5. Twelfth International Conference on Information Systems Development ISD2003, Melbourne, Australia 6. Lietuvos mokslas ir pramon
: Informacin
s technologijos, 2003, Kaunas, Lithuania 7. International Conference on Modeling and Simulation of Business Systems MOSIBUS2003, Vilnius, Lithuania 8. Thirteenth International Conference on Information Systems Development ISD2004, presentations in Doctoral Consorcium and Conference Panel “Issues of Business Rules Approach in IS Development”, Vilnius, Lithuania   CONTENTS    The dissertation consists of the introduction, three chapters, conclusions, used terms and abbreviations, references, and two appendices (CD). The language of the doctoral dissertation is Lithuanian.   Chapter 1. Introduction A short review on the topicality of the research topics is given. We introduce the main objectives of the doctoral dissertation and the achieved results. The scientific novelty of the results and their practical significance are discussed.   Chapter 2. The analysis of the knowledge based technologies and their application in business organizations and business information systems 2.1. Knowledge representation and modeling Knowledge modeling is the process or technology intended to model knowledge. The result of knowledge modeling is knowledge or expertise model, which conveys relative business domain knowledge, business goals, problems at hand, etc. description. The inherent part of knowledge modeling is knowledge representation. Knowledge representation uses theories and methods of several disciplines – logics, ontology, and computation. In short, knowledge modeling can be defined as creation of computable models using logics and ontology for a specific domain.   2.2. Knowledge representation principles Knowledge representation should adhere to the following five principles: (1) knowledge representation is substitution; (2) knowledge representation is a set of ontological commitments; (3) knowledge representation is a fragmental theory of intellectual reasoning; (4) knowledge representation is an environment for computation; (5) knowledge representation is an expression of human reasoning. Out of these principles stem the requirements for knowledge representation languages.    

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2.3. Analysis of knowledge based technologies Knowledge usage in intelligent systems is rather diverse – different knowledge based technologies emerged which have influenced the practical employment of knowledge in IS. The survey on intelligent agents, ontology, knowledge sharing, knowledge processing, intelligent databases, active databases, knowledge discovery and data mining is given.   2.4. Analysis of knowledge representation languages The survey on knowledge representation languages (frames, description logics, and rules) is given pointing out that all languages despite their origin (frame-based or rule- based) have formal logic background. Having in mind different knowledge representation languages, knowledge representation principles, business IS development process, and the business knowledge model usage in business IS development process we propose the requirements for the business knowledge modeling language: (1) the language must be formal to guarantee preciseness and unambiguity and enable implementation from conceptual model; (2) the language must be informal in order to be used as a means of communication between system analysts and business representatives for the business representatives being the owners of their knowledge can convey the right representation and thus should be active participants in all stages of the business IS life cycle. The relation betweeen the proposed requirements and the driving factors for the requirements is shown in Figure 1 below.   Knowledge model usage cases: Knowledge model usage cases: modeling language for systemcomprehensive modeling language analysts and developers for both business representatives used in the following phases of IS Knowledge model: and system analysts lifecycle: from modeling to implementation used in the following phases of IS - implementation lifecycle: - analysis / design support and maintenance -

FORMAL INFORMAL  - logic based - near-natural language script  - interchange format (textual) - graphical format  - unambiguous - easy to use  - precise - intuitive

Knowledge representation principles: Knowledge representation principles: knowledge representation is a Knowledge model: knowledge representation is fragmental theory of intellectual from implementation to modeling sbusutitonti reasoningknowledge representation is a set knowledge representation is an of ontological commitments environment for computationknowledge representation is an expression of human reasoning   Figure 1. The driving factors and the proposed requirements for business knowledge modeling language   Chapter 3. Business rules investigation 3.1. Business rule definition Business knowledge is a rather intangible concept and it is difficult to find a single definition for it and a single structuring scheme.  9

Business rule definition is twofold. From business perspective business rule is a statement that defines or constrains some aspect of the business; it is intended to assert business structure, or to control or influence the behavior of the business. Atomic business rules cannot be broken down or decomposed further into more detailed business rules because, if reduced any further, there would be loss of important information about the business. From IS perspective business rule is a statement, which constrains certain business aspect, defines business structure, and controls business processes. In IS it is implemented as facts registration (as data) and constraints applied during registration process. The motivation behind the business rules approach is rather straightforward: 1. The concept of business rule is not a new one; business representatives use it to describe business processes of their organizations. Thus business representatives are capable to use the concept by themselves while identifying business rules. 2. Business rules are the method to structure business knowledge. Since it is easily comprehensible and convenient for both business representatives and system analysts, it constitutes an excellent basis for communication. 3. Business rules structure closely resembles the structure of production rules thus it is possible to represent business rules using some formal logic-based modeling language. 4. Business rules in a formal representation language allow using this representation for automatic implementation. 5. Business rules are expected to change more frequently than the rest of business objects, and tend to evolve over time as a result of new business requirements. Therefore it is reasonable to identify business rules as a separate component and deal with it respectively at logical and physical levels.   3.2. Business rules taxonomies The famous business rules researcher Ellen Gottesdiener states: "There is no agreed- upon taxonomy for business rules, nor does there need to be." While it is questionable whether there should be one agreed taxonomy, it is indeed true that it does not exist yet. We give the extensive list of proposed taxonomies (15 different taxonomies). The list is quite extensive; it covers the opinions of business rules researchers as well as commercial companies working in this field. However, in our reasearch focusing on the implementation perspective we propose to divide the business rules categories into two broad types: 1. Terms, facts, and state integrity constraints can be considered as structural assertions, which introduce the definitions of business entities and describe the connections between them. Since they can be captured by a conceptual model of the problem domain, e.g. by an Entity-Relationship (ER) or a UML class model, they can be regarded not as business rules but rather as concepts forming the business vocabulary (or ontology). 2. Other categories can be considered as dynamic assertions which fall into the following main types: a) dynamic constraints restrict the admissible transitions from one state of the system to another; b) derivation rule is a statement of knowledge that is derived from other knowledge by an inference or a mathematical calculation;

 

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