International Conference 20th EURO Mini Conference Continuous Optimization and Knowledge-Based Technologies (EurOPT-2008) May 20 23, 2008, Neringa, LITHUANIA ISBN 978-9955-28-283-9 L. Sakalauskas, G.W. Weber and E. K. Zavadskas (Eds.): EUROPT-2008 Selected papers. Vilnius, 2008, pp. 462 467 Institute of Mathematics and Informatics, 2008 Vilnius Gediminas Technical University, 2008 APPLICATION OF METAMODELLING FOR INFORMATION SYSTEMS ENGINEERING Gražina Kalibataitė Kaunas University of Technology, Information Systems Department Studentu 50, Kaunas, Lithuania E-mail: kaligraz@elekta.lt Abstract: The article deals with the problems of company activity computerization and usage of the knowledge, problem of conformity between business and information systems as well as problems of the knowledge management in activity of organizations. It strives highlighting the problems related to insufficient usage of knowledge that is one of the most valuable recourses, stating of reasons that complicate information management processes. Also it discusses the problems of information integration, possibilities to use metadata in information systems. Conception of metadata as well as assumptions of its origin is discussed in the article, too. The article points up the role of metadata in an organization activity as well as technology to manage it, importance to computerize the knowledge management. Keywords: metadata, metamodeling, enterprise modeling, information system modeling. 1. Introduction Activity of enterprises more and more depends on the knowledge one of the most valuable resources they possess. Enterprise knowledge is a very important clue that is necessary while supporting business processes, reacting quickly and adequately towards changing environment conditions. Enterprises need unanimous, precise and permanent business information but knowledge submission and usage requires some basis of meta-knowledge, knowledge conception, and usage of representation and structural methods. Modern organizations vitally need implementing processes and technologies to distribute and use the knowledge. That is why the aim of the knowledge managing is to make teamwork easier using permanently increasing information flows as well as manage them. Business processes could become more effective if using different knowledge management methodology. Knowledge in the activity of organizations reverts into different shapes and it becomes more complicated to manage them. Quick and easy approach to the knowledge becomes more and more pressing for organizations. Organizations encounter problems of knowledge using and managing: to find the ways to reflect the possessed knowledge; to organize approach to the information and make it convenient for a user; increasing number of distributed non-integrated systems. Integration problems are problems of today. Activity of modern industrial enterprises in a market is determined by variety of products and technologies. Usually they have to apply products to rapidly changing customer demands. Modern company joins different, heterogeneous information systems that work autonomic, are distributed and should be integrated. Different company departments often use different programmed equipment that have their own data sets and the aim of the enterprise activity integration is to join all enterprise information technologies (IT) systems, business processes and job places on the basis of IT. Metadata is a highly important compound of enterprise activity information systems (IS). Today s pressing problem is that every modern enterprise is overfilled by data. It is very important for companies to have a possibility to identify resources, their origin, semantics and ways to the information approach. Metadata is the resource of such information. The problem is that different enterprise departments use different sets of data support instruments. Metadata fits each such set and that is why it is impossible to relate some information changes with one another. For solving this problem enterprises need metadata integrated projects but most part of enterprises do not have clear strategy to be used with metadata. Using metadatabases model is one of the ways to carry out enterprise IT integration on the basis of knowledge; effective way to reach general enterprise information resources, carry out business data analysis more 462
APPLICATION OF METAMODELLING FOR INFORMATION SYSTEMS ENGINEERING precisely and quickly, determine and evaluate the enterprise data changes, manage information resources. The aim of metadatabases model is to achieve information integration between distributed and heterogeneous systems, let those systems work together. The object of the article: reveal peculiarities of organizing activities of modern enterprises: orientation towards knowledge, active their usage as well as pressing problems related to the knowledge usage; show metadatabases model is one of possible ways to increase effectiveness of an enterprise system. 2. Enterprise function computerizing and knowledge Talking about enterprise modeling, it is important to know it s importance and difference between data and information. Unless it is not known it will not be easy to understand information modeling system and it s efficiency. However today s computer systems are working on the information and not on knowledge. Constantly changing outside and growing request makes difficult to control nowadays company. Enterprises must have solid and constant business information (BI software, 2007). Organization knowledge is a cure, which helps to hold up business and allows to react adequate and quickly to volatile environmental conditions (Zalieckaitė, Mikalauskienė, 2007). Knowledge must be separated from data and information (Fig. 1). Data contains figures, facts, views and sounds. It is information stock for subject use and which helps it to get significant information (Bellinger, Castro, Mills, 2004; Kėdaitienė, 1999). Fig. 1. Connection with data, information and knowledge Talking about organization knowledge, it is considered to talk about the useful company information taking no count of its form and where it is hold. In estimation of many authors knowledge is to be very important unit analysing information integration (Brazaitis, Brazaitienė, 1999; Inform, 2002; Kėdaitienė, 1999): Enterprise ability to use its immaterial property is coming major in compare with the ability of investation and material property management ; Knowledge is used to process data and to make the information; People have to do estimation, take decision and do the action; Knowledge ensure enterprise hardly transfered competitive advantage source; Development of new products, services and operations based on knowledge turns to the main internal function of the enterprise. 3. Business and information system conformity problem Disposable knowledge increasibly depends from different people, enterprise activity and its effective usage, which is the most valuable resource. Unfortunately, the means used to present the knowledge are not perfect. The essential importance for nowadays enterprises is to introduce processes and technologies, which could use the knowledge and distribute them. There are three essential knowledge ruling components (Prabhakaran, Chou, 2006; Попов, Фоминых, 2005): People, who give their experience to form new ideas; Processes, which are used for the whole information use and propagation; Technologies, which effect to people and process work.. The other business processes could be more effective if to use various knowledge ruling methods. However knowledge ruling idea is not exactly structured yet (Попов, Фоминых, 2005). Mostly all companies operate huge quantity of result information and practical experience concentrated in data base, document storage, e-mails, sales reports and of course in workers mind. The problem is to organise access to this data and to give convenient form to user. The other problem is, that enterprises are using different 463
G. Kalibataitė production systems, specialised in special areas for different purposes. This is why large quantity of distributed not integrated systems is growing (Harjinder, 2000). 4. Knowledge outlook control and main principles There are lots of knowledge forms in the enterprise activity, so it is hard to control them. Today knowledge control is connected with information and communication technology, which warrants knowledge processing, running and receiving. Enterprise knowledge control objects (Joseph, 1999): to increase the knowledge quantity of its workers and to increase the possibility to share it. These principles are the same for all nowaday enterprises. Knowledge control model must be set to control enterprise knowledge. Knowledge control is the use of technologies in the way to reach propper and accessible information, in despite of its creation and storage place. The technologies must be addapted to the conditions (Brown, Duguid, 2004). Enough plenty quantity of enterprise knowledge is noticed in business process and information structure, which is the main knowledge control element. So it is why the business process models usage makes Activity Based Costing creation faster and gives conditions to pass the Activity Based Management. Knowledge based system is supposed to be computer programm with declarative knowledge base, which contains encoded human knowledge for solving the problems Knowledge base contains all the rules (rule-base) and most of the facts (Maskeliūnas, 2006). Usage motivation helps preserve knowledgebuilds up the corporate memory of the firm. The main knowledge ruling object is extraction, storage, concentration and effective usage. 5. Enterprise integration problems Essential aspect of information system modeling belongs to integrity. Enterprise activity integrity plays huge role in IT systems base connection with IT systems, business process and working places. Main creation problems of integrated information systems are: It is hard to change data and knowledge in integrated systems due to tight infrastructures (business rules), integrated use; Business rules influence some business area and force for change all connected information and programm systems; Particular programm system can use different business rule systems and methods of their formalisation; When the business changes occur, program systems must be modified newly going through the whole system engineering cycle which takes long time; Business system could be changed periodically, so interative modification is necessary at once in several systems. Integrated account data control is expressed by: onetime data record and multiplex its usage, integrated index cast after data processing and initial data use for effective result information count. The meta-model system is envisioned to not only support CASE tools management and paradigm translation, but also utilize the resultant metadata capabilities to directly facilitate the management of application information systems across the enterprise (Fig. 2). Fig. 2. Enterprise Information Integration Using Meta-Models (Hsu, Tao, Bouziane, Babin, 1993) 464
APPLICATION OF METAMODELLING FOR INFORMATION SYSTEMS ENGINEERING Metadata storage could be good architectural solution for the whole enterprise information integration. To avoid difficulties in usage, such requirements must be followed: fast reach and flexibility, capability, extention, orientation to user, adjustment reaction and business modeling. 6. Using metamodeling for enterprise computerising 6.1. Metadata approach model Metadata is very important in every information system. Every modern enterprise is stuffed with data. It could be found everywhere with reccurence in different places. Enterprise must have the possibility to identify source, reason, semantics and access ways to data. Metadata is the source of this information. In despite of this, organizations do not have dedicated programs to define their meta data strategies (Muralidhar, 2005; Prabhakaran, M.; Chou, 2006). Metadatabase is the store of info on enterprise structure, application programms function, their operating, information model, base, interaction and information dynamics in the enterprise. Metadata base model foresees enterprise information system integration on knowledge base and is striving for iformation integration between distributed and not uniformed systems to ensure their joint work (Hsu, Rattner, 1993). Metadata model. In computer science and related disciplines, metamodeling is the construction of a collection of concepts within a certain domain (Wikipedia). There are several ways to choose metamodeling data: creating special data model for work with it; use of egzisting models standards. Two standard models are used: Open Information Model (OIM) and Common Warehouse Meta-Mode) (CWM). CWM describe metadata changes between store activity based on knowledge means and ruling based on knowledge. OIM tai metadata specification, described in universal modeling language UML (Muralidhar, 2005). Data storage source could be releative or orientated to objects storage. There do exist long range of possibilities. One of solutions is central storage, where all metadata is kept (Fig. 3). Main items of metadata are stored in centralised storage: engineering metadata, data base system ruling, activity and metadata are connected to various processes. 6.2. Metadatabase management system Fig. 3. Architecture using centralized storage (Muralidhar, 2005) Main metadata ruling system structure (Fig.4): Metadatabase Management System (MDBMS); Information Base Modeling System (IBMS); Rule-Oriented Programming Environment (ROPE) (Hsu, Babin, 1992). Fig. 4. The Metadatabese System (Hsu, Babin, 1992) 465
G. Kalibataitė Metadatabase Management System is the conjunction of user and processor, which control information in metadata base. MDBMS contains three main elements: system connector, global request manager and metadata manager.information Base Modeling System is computerised software tool, which lets the system user design enterprise information system and collective information resource dictionary. Dictionary is metadata resource in automate setting, which directly provides metadata base with information. Rule-Oriented Programming Environment is such software, which ensures interaction between separate enterprise IS subsystem. This make a layer between metadata ruling system and local engineering system. Based on rules software setting is set to gather more system requirements. Main enterprise metadata base setting is based on parallel architecture (Hsu, Babin, 1992). Many efforts are put in systems integration to connect systems in data level i.e. to estimate, which data part is used and in which system. Using traditional information system integration method (Fig. 5) exact transferable data structure is to be used. Used metadata base in system integration (Fig.6) traditional model through exact encoding connection chanels between systems is changed to data exchange model (based on knowledge and rules) (Hsu, Babin, 1992). Fig. 5. Traditional Approach to System Integration Fig. 6. Metadatabase Approach to System Integration 7. Conclusions Article analyses industry information integration problems as well as a role of the metadatabases in the company information systems. Conception of metadatabases and its environment, presumptions of metadatabases, their role in the activity of an organization, importance of the informational management is discussed. Today we face the problem, that lots of nowadays enterprises are fulfilled with data. You can find them everywhere and most of them are the same occur in several places. Many enterprises have no straight metadata usage strategy. Enterprises must save the possibility to identify sources, their origin, semantics and the data approach sources. Metadata is the main source of getting this information and more it is very important component of every information system. Although metadata is not universal data ruling tool, which could demonstratively improve data analysis quality in the enterprise and at the same time influence growing work effectiviness. Metadata is used to decrease complication, expand queries and to do multiflex data analysis. References BI software company. 2007. Pagrindinės kompanijų problemos. Available from Internet: <http://www.cee.businessobjects.com/global/resources/partners/business%20objects_bukletas_lt.doc.>. Brazaitis, Z.; Brazaitienė, T. 1998. Verslo vadybos informacinės sistemos. Vilnius. Bellinger, G.; Castro, D.; Mills, A. 2004. Data, information, knowledge and wisdom. Available from Internet: <http://www.systems-thinking.org/dikw/dikw.htm>. Brown, J.; Duguid, P. 2004. Socialinis informacijos gyvenimas. Vilnius. Joseph, M. F. 1999. Enterprise knowledge management modeling and distributed knowledge management systems. Available from Internet: <http://www.dkms.com/papers/ekmdkms.pdf>. Harjinder, S. G. 2000. The case for enterprise business model management. DM Review Magazine. Available from Internet: <http://www.dmreview.com/issues/20001201/2789-1.html>. 466
APPLICATION OF METAMODELLING FOR INFORMATION SYSTEMS ENGINEERING Hsu, C.; Babin, G.; Bouziane, H.; Cheung, W.; Rattner, L.; Rubenstein, A. 1992. The metadatabase approach to integrating and managing manufacturing information systems, Journal of Intelligent Manufacturing 333 349. Available from Internet:<http://viu.eng.rpi.edu/publications/mdbapp.pdf>. Hsu, C.; Rattner, L. 1993. Metadatabase solutions for enterprise information integration problems, ACM Database, 23 35. Available from Internet: <http://portal.acm.org/citation.cfm?id=154424&coll=portal&dl=acm>. Hsu, C.; Tao, Y. C.; Bouziane, M.; Babin, G. 1993. Paradigm translations in integrating manufacturing information using a meta-model: The TSER Approach. Information Systems Engineering, France 1(3): 325 352. Available from Internet: <http://viu.eng.rpi.edu/publications/paratra.pdf>. Informacinių sistemų kūrimo metodika. 2002. Available from Internet: <http://www.ivpk.lt/teises_aktai/ files/15.pdf>. Kėdaitienė, A. 1999. Marketingo tyrimų informacija: mokomoji knyga. Metodinis leidybinis centras. Maskeliūnas, S. 2006. Žinių technologijų pagrindinių terminų žodynėlis, Nr. 35. Matematikos ir informatikos institutas. Available from Internet: < http://www.likit.lt/?i=klausimai/atsakymai>. Muralidhar, P. 2005. Meta data management in the enterprise. DM Review Magazine. Available from Internet: <http://www.dmreview.com/article_sub.cfm?articleid=1032598>. Prabhakaran, M.; Chou, C. 2006. Semantic integration in enterprise information management, SETLabs 4(2 Oct Dec): 45 52. Available from Internet: <http://www.infosys.com/research/publications/setlabs-briefingsenterprise-it.pdf>. Understanding Metadata. 2004. Published by: NISO Press National Information Standards Organization. Available from Internet: <http://www.niso.org/standards/resources/understandingmetadata.pdf>. Waddington, D. 2004. An architected approach to integrated information. Available from Internet: <http://hosteddocs.ittoolbox.com/dw041505.pdf>. Wikipedia meta-modeling. Available from Internet: <http://en.wikipedia.org/wiki/meta-modeling>. Zalieckaitė, L.; Mikalauskienė, A. O. 2007. Organizacijos žinių struktūrų ir jų vadybos prieigų analizė, Informacijos mokslai 41: 42 57. ISSN 1392 0561. Попов, Э. В.; Фоминых, И. Б.; Харин, Н. П.; Виньков, М. М. 2005. Управление знаниями: Аналитический обзор. Available from Internet: <http://www.rfbr.ru/pics/20742ref/uprznan.pdf>. 467