A Z Approach in Validating ORA-SS Data Models

Lecture Notes in Computer Science, 2006

Semistructured data is now widely used in both web applications and database systems. Much of the research into this area defines algorithms that transform the data and schema, such as data integration, change management, view definition, and data normalization. While some researchers have defined a formalism for the work they have undertaken, there is no widely accepted formalism that can be used for the comparison of algorithms within these areas. The requirements of a formalism that would be helpful in these situations are that it must capture all the necessary semantics required to model the algorithms, it should not be too complex and it should be easy to use. This paper describes a first step in defining such a formalism. We have modelled the semantics expressed in the ORA-SS (Object Relationship Attribute data model for SemiStructured data) data modelling notation in two formal languages that have automatic verification tools. We compare the two models and present the findings.

Advances in Web-Age Information Management, 2006

Semistructured data has become prevalent in both web applications and database systems. This rapid growth in use makes the design of good semistructured data essential. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of ORA-SS in the Web Ontology Language (OWL) and automatically validating the semistructured data design using the OWL reasoning tool -RACER. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels.

Lecture Notes in Computer Science, 2006

There has been a rapid growth in the use of semistructured data in both web applications and database systems. Consequently, the design of a good semistructured data model is essential. In the relational database community, algorithms have been defined to transform a relational schema from one normal form to a more suitable normal form. These algorithms have been shown to preserve certain semantics during the transformation. The work presented in this paper is the first step towards representing such algorithms for semistructured data, namely formally defining the semantics necessary for achieving this goal. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of the ORA-SS notation into the Web Ontology Language (OWL) and automatically verifying the semistructured data design using the OWL reasoning tools. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels.

Proceedings of the Second International Conference on Web Information Systems Engineering

Semistructured data has become prevalent with the growth of the Internet. The development of new web applications that require efficient design and maintenance of large amounts of data makes it increasingly important to design "good" semistructured databases to prevent data redundancy and updating anomalies. However, it is not easy, even impossible, for current semistructured data models to capture the semantics traditionally needed for designing databases. In this paper, we show how an Object-Relationship-Attribute model for SemStructured data (ORA-SS) can facilitate the design of "good" semistructured databases. This is accomplished via the normalization of ORA-SS. An XML DTD or Schema generated from a normal form ORA-SS schema diagram has no undesirable redundancy, and thus no updating anomalies for the complying semistructured databases. The general design methodology and detailed steps for converting an ORA-SS schema diagram into a normal form ORA-SS schema diagram are presented. These steps can also be used as guidelines for designing semistructured databases using the ORA-SS model.

J. Univers. Comput. Sci., 2009

The rapid growth of the World Wide Web has resulted in a dramatic in- crease in semistructured data usage, creating a growing need for effective and efficient utilization of semistructured data. In order to verify the correctness of semistructured data design, precise descriptions of the schemas and transformations on the schemas must be established. One effective way to achieve this goal is through formal model- ing and automated verification. This paper presents the first step towards this goal. In our approach, we have formally specified the semantics of the ORA-SS (Object- Relationship-Attribute data model for Semistructured data) data modeling language in PVS (Prototype Verification System) and provided automated verification support for both ORA-SS schemas and XML (Extensible Markup Language) data instances using the PVS theorem prover. This approach provides a solid basis for verifying algo- rithms that transform schemas for semistructured data.

Citeseer

Semi-structured data is becoming increasingly important with the introduction of XML and related languages and technologies. The recent shift from DTDs (document type de nitions) to XML-Schema for XML data highlights the importance of a schema de nition for semi-structured data ...

Formal Methods in System Design, 2010

The wide adoption of semistructured data has created a growing need for effective ways to ensure the correctness of its organization. One effective way to achieve this goal is through formal specification and automated verification. This paper presents a theorem proving approach towards verifying that a particular design or organization of semistructured data is correct. We formally specify the semantics of the Object Relationship Attribute data model for Semistructured Data (ORA-SS) modeling notation and its correctness criteria for semistructured data normalization using the Prototype Verification System (PVS). The result is that effective verification on semistructured data models and their normalization can be carried out using the PVS theorem prover.

Lecture Notes in Computer Science, 2002

Semistructured data is becoming increasingly important for web applications with the development of XML and related technologies. Designing a "good" semistructured database is crucial to prevent data redundancy, inconsistency and undesirable updating anomalies. However, unlike relational databases, there is no normalization theory to facilitate the design of good semistructured databases. In this paper, we introduce the notion of a semistructured schema and identify the various anomalies that may occur in such a schema. A Normal Form for Semistructured Schemata, NF-SS, is proposed. A semistructured schema in NF-SS guarantees minimal redundancy and hence no undesirable updating anomalies for the associated semistructured databases. Furthermore, a semistructured schema in NF-SS gives a more reasonable representation of real world semantics. We develop an iterative algorithm based on a set of heuristic rules to restructure a semistructured schema into a normal form. These design methods also provide insights into the normalization task for semistructured databases.

2000

Abstract Recently, there have been several proposals of formalisms for modeling semistructured data, which is data that is neither raw, nor strictly typed as in conventional database systems. Semistructured data models are graph-based models, where graphs are used to represent both databases and schemas.

Semi-structured Data are becoming extremely popular in versatile applications including interactive web application, protein structure analysis, 3D object representation, personal lifetime information management. In order to meet the challenges of today's complex applications, a generic model is in demand. This paper therefore focuses to examine the Semi-structured Data Model and implementation issues for Semi-structured Data. The paper assumes that: fluidity in data structure makes it difficult to store and manage the semi structured data using conventional data models like Relational Database model; the main advantage of fully structured data is the strong typing which enables high performance and efficiency; unstructured and semi structured data allow a higher degree of flexibility; Graph based models (e.g OEM) can be used to index semi-structured data; data modeling technique in OEM allows the data to be stored in graph based model; the data in graph based model is easier to search/ index; and finally, XML allows data to be arranged in hierarchical order which enables the data to be indexed and searched as well.