The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Dowming Yeh - One of the best experts on this subject based on the ideXlab platform.

  • Extracting entity-relationship diagram from a table-based legacy database
    Journal of Systems and Software, 2008
    Co-Authors: Dowming Yeh, William C. Chu
    Abstract:

    Current database reverse engineering researches presume that the information regarding semantics of attributes, primary keys, and foreign keys in database tables is complete. However, this may not be the case. In a recent DBRE effort to derive a data model from a table-based database system, we find the data content of many attributes are not related to their names at all. In this paper, we present a process that extracts an extended entity-relationship diagram from a table-based database with little descriptions for the fields in its tables and no description for keys. The primary inputs of our approach are system display forms, table schema and data instance. We utilize screen displays to construct form instances. Secondly, code analysis and data analysis involving comparisons of fields and decomposition of fields are applied to extract attribute semantics from forms and table schemas, followed by the determination of primary keys, foreign keys and constraints of the database system. In the final step of conceptualization, with the processes of table mergence and relationship identification, an extended ER diagram is successfully extracted in a case study.

  • extracting entity relationship diagram from a table based legacy database
    Conference on Software Maintenance and Reengineering, 2005
    Co-Authors: Dowming Yeh
    Abstract:

    Current database reverse engineering researches presume that the information regarding semantics of attributes, primary keys, and foreign keys in database tables is complete. However, this may not be the case. In this paper, we present a process that extracts an extended entity relationship diagram from a table-based database with little descriptions for the fields in its tables and no description for keys. The primary inputs of our approach are system display forms and table schema. An extended ER diagram is successfully extracted in a case study.

William C. Chu - One of the best experts on this subject based on the ideXlab platform.

  • Extracting entity-relationship diagram from a table-based legacy database
    Journal of Systems and Software, 2008
    Co-Authors: Dowming Yeh, William C. Chu
    Abstract:

    Current database reverse engineering researches presume that the information regarding semantics of attributes, primary keys, and foreign keys in database tables is complete. However, this may not be the case. In a recent DBRE effort to derive a data model from a table-based database system, we find the data content of many attributes are not related to their names at all. In this paper, we present a process that extracts an extended entity-relationship diagram from a table-based database with little descriptions for the fields in its tables and no description for keys. The primary inputs of our approach are system display forms, table schema and data instance. We utilize screen displays to construct form instances. Secondly, code analysis and data analysis involving comparisons of fields and decomposition of fields are applied to extract attribute semantics from forms and table schemas, followed by the determination of primary keys, foreign keys and constraints of the database system. In the final step of conceptualization, with the processes of table mergence and relationship identification, an extended ER diagram is successfully extracted in a case study.

Yangsae Moon - One of the best experts on this subject based on the ideXlab platform.

  • samstarplus an automatic tool for generating multi dimensional schemas from an entity relationship diagram
    Revista De Informática Teórica E Aplicada, 2010
    Co-Authors: Jinho Kim, Il-yeol Song, Yangsae Moon, Suan Lee, Donghoo Kim, Ritu Khare
    Abstract:

    This paper presents a tool that automatically generates multidimensional schemas for data warehouses from OLTP entity-relationship diagrams (ERDs). Based on user’s input parameters, it generates star schemas, snowflake schemas, or a fact constellation schema by taking advantage of only structural information of input ERDs. Hence, SAMSTARplus can help users reduce efforts for designing data warehouses and aids decision making.

  • ER - SAMSTAR: An Automatic Tool for Generating Star Schemas from an entity-relationship diagram
    Lecture Notes in Computer Science, 2008
    Co-Authors: Il-yeol Song, Ritu Khare, Suan Lee, Sang-pil Kim, Jinho Kim, Yangsae Moon
    Abstract:

    While online transaction processing (OLTP) databases are modeled with entity-relationship diagrams (ERDs), data warehouses constructed from these OLTP DBs are usually represented as star schema. Designing data warehouse schemas, however, is very time consuming. We present a prototype system, SAMSTAR, which automatically generates star schemas from an ERD. The system takes an ERD drawn by ERwin Data Modeler as an input and generates star schemas. SAMSTAR uses the Connection Topology Value [1] which is the syntactic structural information embedded in an ERD. SAMSTAR displays the resulting star schemas on a computer screen graphically. With this automatic generation of star schema, this system helps designers reduce their efforts and time in building data warehouse schemas.

Il-yeol Song - One of the best experts on this subject based on the ideXlab platform.

  • samstarplus an automatic tool for generating multi dimensional schemas from an entity relationship diagram
    Revista De Informática Teórica E Aplicada, 2010
    Co-Authors: Jinho Kim, Il-yeol Song, Yangsae Moon, Suan Lee, Donghoo Kim, Ritu Khare
    Abstract:

    This paper presents a tool that automatically generates multidimensional schemas for data warehouses from OLTP entity-relationship diagrams (ERDs). Based on user’s input parameters, it generates star schemas, snowflake schemas, or a fact constellation schema by taking advantage of only structural information of input ERDs. Hence, SAMSTARplus can help users reduce efforts for designing data warehouses and aids decision making.

  • ER - SAMSTAR: An Automatic Tool for Generating Star Schemas from an entity-relationship diagram
    Lecture Notes in Computer Science, 2008
    Co-Authors: Il-yeol Song, Ritu Khare, Suan Lee, Sang-pil Kim, Jinho Kim, Yangsae Moon
    Abstract:

    While online transaction processing (OLTP) databases are modeled with entity-relationship diagrams (ERDs), data warehouses constructed from these OLTP DBs are usually represented as star schema. Designing data warehouse schemas, however, is very time consuming. We present a prototype system, SAMSTAR, which automatically generates star schemas from an ERD. The system takes an ERD drawn by ERwin Data Modeler as an input and generates star schemas. SAMSTAR uses the Connection Topology Value [1] which is the syntactic structural information embedded in an ERD. SAMSTAR displays the resulting star schemas on a computer screen graphically. With this automatic generation of star schema, this system helps designers reduce their efforts and time in building data warehouse schemas.

  • samstar a semi automated lexical method for generating star schemas from an entity relationship diagram
    Data Warehousing and OLAP, 2007
    Co-Authors: Il-yeol Song, Ritu Khare, Bing Dai
    Abstract:

    The star schema is widely accepted as the de facto data model for data warehouse design. A popular approach for developing a star schema is to develop it from an entity-relationship diagram with some heuristics. Most of the existing approaches analyze the semantics of an ERD to generate a star schema. In this paper, we present the SAMSTAR method, which semi-automatically generates star schemas from an ERD by analyzing its semantics as well as structure. The novel features of SAMSTAR are (1) the use of the notion of Connection Topology Value (CTV) in identifying the candidates of facts and dimensions and (2) the use of Annotated Dimensional Design Patterns (A_DDP) as well as WordNet to extend the list of dimensions. We illustrate our method by applying it to the examples from existing literature. We prove that the outputs of our method are a superset of those of the existing methods. The SAMSTAR method simplifies the work of experienced designers and gives a smooth head-start to novices.

Ritu Khare - One of the best experts on this subject based on the ideXlab platform.

  • samstarplus an automatic tool for generating multi dimensional schemas from an entity relationship diagram
    Revista De Informática Teórica E Aplicada, 2010
    Co-Authors: Jinho Kim, Il-yeol Song, Yangsae Moon, Suan Lee, Donghoo Kim, Ritu Khare
    Abstract:

    This paper presents a tool that automatically generates multidimensional schemas for data warehouses from OLTP entity-relationship diagrams (ERDs). Based on user’s input parameters, it generates star schemas, snowflake schemas, or a fact constellation schema by taking advantage of only structural information of input ERDs. Hence, SAMSTARplus can help users reduce efforts for designing data warehouses and aids decision making.

  • ER - SAMSTAR: An Automatic Tool for Generating Star Schemas from an entity-relationship diagram
    Lecture Notes in Computer Science, 2008
    Co-Authors: Il-yeol Song, Ritu Khare, Suan Lee, Sang-pil Kim, Jinho Kim, Yangsae Moon
    Abstract:

    While online transaction processing (OLTP) databases are modeled with entity-relationship diagrams (ERDs), data warehouses constructed from these OLTP DBs are usually represented as star schema. Designing data warehouse schemas, however, is very time consuming. We present a prototype system, SAMSTAR, which automatically generates star schemas from an ERD. The system takes an ERD drawn by ERwin Data Modeler as an input and generates star schemas. SAMSTAR uses the Connection Topology Value [1] which is the syntactic structural information embedded in an ERD. SAMSTAR displays the resulting star schemas on a computer screen graphically. With this automatic generation of star schema, this system helps designers reduce their efforts and time in building data warehouse schemas.

  • samstar a semi automated lexical method for generating star schemas from an entity relationship diagram
    Data Warehousing and OLAP, 2007
    Co-Authors: Il-yeol Song, Ritu Khare, Bing Dai
    Abstract:

    The star schema is widely accepted as the de facto data model for data warehouse design. A popular approach for developing a star schema is to develop it from an entity-relationship diagram with some heuristics. Most of the existing approaches analyze the semantics of an ERD to generate a star schema. In this paper, we present the SAMSTAR method, which semi-automatically generates star schemas from an ERD by analyzing its semantics as well as structure. The novel features of SAMSTAR are (1) the use of the notion of Connection Topology Value (CTV) in identifying the candidates of facts and dimensions and (2) the use of Annotated Dimensional Design Patterns (A_DDP) as well as WordNet to extend the list of dimensions. We illustrate our method by applying it to the examples from existing literature. We prove that the outputs of our method are a superset of those of the existing methods. The SAMSTAR method simplifies the work of experienced designers and gives a smooth head-start to novices.