The amount of information on the internet is increasing every day and it is very difficult to find exact information from big list of search results. Users typically generate query specifying keywords and the search engine displays documents, what contains keywords what were set by user. Search within unstructured data starts from data processing: first of all documents are braked into sentences, then words and word groups are analyzed semantically and syntactically, to obtain facts. Facts describe objects of real world. Facts obtained from unstructured data will be stored into database, and unstructured data will be transformed into structured data. Afterwards it will be easy to analyze, conjunct, filter or do other manipulations with structured data.

The place of data modelling in information systems‘ life cycle and the importance of data model quality in effective IS exploitation are shown in this masters' work. Refering to results of the nonfiction literature analysis the reasons why the process of data modelling must be automated are introduced; current automatization solutions are described. And as it is the main purpose of this work an original data modelling method is described and programmable prototype which automates one step of that method – schema integration is introduced.

Šiame darbe nagrinėjama objektinių ir reliacinių schemų integruojamumo ir suderinamumo problema. Programinei įrangai kurti šiuo metu populiariausios objektinės programavimo kalbos, tačiau duomenys, kuriais manipuliuojama, dažniausiai saugojami reliacinėse duomenų bazėse, todėl aktualu programuojant naudojamas struktūras susieti su reliacinės duomenų bazės struktūromis. Organizacijų informacijų sistemose duomenys dažnai yra saugojami keliose duomenų saugyklose, yra poreikis integruoti įvairiose saugyklose esančius duomenis. Tam tikslui naudojamos federacinės duomenų bazės, besiremiančios kanoniniu duomenų modeliu. Šiame darbe aprašomas objektinių ir reliacinių schemų integracijos modelis. Pasiūlytas skurdus kanoninis duomenų modelis, kurį sudaro atributai ir apribojimai: funkcinės, jungimo/projekcijos ir poaibio priklausomybės. Aprašytos transformacijos iš reliacinių ir objektinių schemų į kanoninę schemą, algoritmas kanoninėms schemoms integruoti, kanoninės schemos transformacija į struktūrinius tipus, naudojant modifikuotą sintezės algoritmą, ir OWL. Aprašyti algoritmai leidžia pasiekti vienareikšmiškumą ir iš dalies automatizuotumą. Modifikuotas sintezės algoritmas duoda geresnius rezultatus nei standartinis, nes įvertina jungimo/projekcijos priklausomybes. Pasiūlyti algoritmai gali būti naudojami integracijai, norint atkurti konceptualiąją schemą ar objektines struktūras iš reliacinės schemos. / In this work the problem of integration and compatibility of relational and object schemas is investigated. Nowadays object-oriented programming languages are the most popular, but data that has to be manipulated is usually stored in relational databases. It is relevant to map structures that are used in programming languages to relational structures. Data is usually stored in several repositories in enterprise information systems, so there is the need to integrate them. Federated databases are used for this purpose, and they have canonical data model. Semantically poor canonical data model, which consists of attributes and constraints (functional, join and subset dependencies), is proposed. Algorithms are given for transforming relational and object schemas to canonical schema, integrating canonical schemas, transforming canonical schema to structural types (using modified synthesis algorithm) and OWL. Proposed algorithms give unambiguous result and can be partially automated. Modified synthesis algorithm gives better results than standard algorithm as it takes join dependencies into account. The algorithms can be used to restore conceptual schema and object structures from relational schema as well as to integrate schemas.

Analysis of already created heat metering and billing systems are made. Lacks and advantages of existing systems are overlooked and considered for add-on model development. Heat metering and billing functions are described and solution is presented. MS Navision and MS SQL Server technologies usability aspects where analyzed. The functionality of MS Navision where compared with described heat metering and billing functions and the fit-gap where made. Product was built as a specific add-on module for MS Navision Attain. The most important goals of product where heat energy billing integration with financial management and flexible data model for program adaptation to methodology changes of heat energy billing. Data model flexibility analysis where done and compatibility to requirements was established. MS Navision and MS SQL server functions performance testes where run and recommendations for choosing platform are made.