Figure 3 - uploaded by Bronius Paradauskas
Content may be subject to copyright.
Raw Physical Schema.

Raw Physical Schema.

Source publication
Article
Full-text available
This article discusses the process of enterprise knowledge extraction from relational database data dictionary and data and source code of legacy information systems. Problems of legacy systems and main solutions for them are briefly described here. The use of database reverse engineering and program understanding techniques to automatically infer...

Context in source publication

Context 1
... Extracted raw physical schema is presented in Figure 3. ...

Citations

... The framework of a process of enterprise knowledge extraction from relational database source code of legacy information systems is presented in [8,9]. ...
Article
Full-text available
B. Paradauskas, A. Laurikaitis. Extracting Conceptual Data Specifications from Legacy Information Systems // Electronics and Electrical Engineering. - Kaunas: Technologija, 2011. - No. 1(107). - P. 46-50. This article discusses the process of extraction of conceptual data specifications from relational database DDL code and data and source code of legacy information systems. Problems of legacy information systems and main solutions for them are briefly described here. Method of extracting conceptual data specifications from legacy information systems is provided. Comparison with other currently existing database reverse engineering methods is presented. III. 3, bibl. 10, tabl. 2 (in English; abstracts in English and Lithuanian).
... [19] ...
Article
Full-text available
The future vision of business information systems rely on semantic technologies as the Web Ontology Language OWL (currently, OWL2) that defines a meaning of business concepts and make them unambiguously understandable by human experts and software systems. Nevertheless, the spread of these technologies is observed mainly in the scientific papers and in some special domains, but not in everyday business operations. The reason for this is the fact that OWL is a language for information technology experts but not for business people – the actual managers of business policies and rules. From the other side, the Semantics of Business Vocabulary and Business Rules (SBVR), one of the recent OMG specifications, provides a means for describing semantic formulations of business concepts and business rules in a language that business people use. Currently some researchers ground their works on assumptions that formal logic-based SBVR formulations are transformable into OWL. However, an exhaustive study how these transformations could be built still is lacking. OWL2 presents new capabilities for linking two worlds. The goal of the paper is to introduce main concepts and problems in transforming SBVR into OWL2 by extending the relevant information from original SBVR specification and related works.
... Most reverse engineering tools and methods [17][18][19][20][21][22][23] follow a well-defined pattern of operation. They parse a given source code to the level of abstraction that is somewhere near Abstract Syntax Tree (AST). ...
Article
Full-text available
We present a language independent method for detecting model implementation patterns in a source code. In contrast to most other reverse engineering methods, we exploit existing program model for this purpose. Our method works by recognizing instances of simple model-to-code transformations. The patterns we use for recognition of model elements can be reused for composing templates for generating a program code. Our method is used for recognizing relationships between program model and handwritten program code.
... SBVR metamodel and XMI schema may be used for developing software tools for managing business vocabularies as well as for automating development of software for managing business on the base of business semantics, i.e. in the way different of previously existed approaches, e.g. [15], [19]. SBVR business vocabularies are transformable into UML&OCL [3], [14], and vice versa [2]; BPMN [1], RDB schemas [13], OWL [4], Web services [5], [7] etc. ...
Article
Full-text available
Today information systems more and more often rely on ontologies that are able to represent meaningful concepts and complex relationships among them relevant for business models and their supporting software systems. However, ontology development and access to ontological data is only possible on deep technological level that is not friendly for business experts. The goal of the paper is to present a possibility of querying OWL ontologies using semantic formulations of Semantics of Business Vocabulary and Business Rules (SBVR), expressed in SBVR Controlled English. We introduce the initial approach for specifying ontology queries as SBVR questions and transforming them to SPARQL.
... II. RELATED WORK SBVR metamodel and XMI schema may be used for developing software tools for managing business vocabularies as well as for automating development of software for managing business on the base of business semantics, i.e., in the way different of previously existed approaches, e.g., [18] [22]. SBVR business vocabularies are transformable into UML&OCL [3][17] and vice versa [2]; BPMN [1], RDB schemas [16], OWL [5], Web services [6], [9] etc. ...
Article
Full-text available
Analyzing semantic relations is a cumbersome task because these relations often are distributed over different information sources and hidden in existing relational database structures. Even with Semantic Web ontologies describing semantic relations we need to explore them on the deep technological level that is not friendly for business users. Semantics of Business Vocabulary and Business Rules (SBVR) gives a possibility of representing OWL 2 ontologies, SWRL rules and SPARQL queries using concepts and semantic formulations expressed in SBVR Structured English language understandable for business users. We suggest formulating derivation rules and queries for analyzing semantic relations as SBVR rules and questions, and transforming them into SWRL and SPARQL.