XML document design via GN-DTD

Designing a well-structured XML document is important for the sake of readability and maintainability. More importantly, this will avoid data redundancies and update anomalies when maintaining a large quantity of XML based documents. In this paper, we propose a method to improve XML structural design by adopting graphical notations for Document Type Definitions (GN-DTD), which is used to describe the structure of an XML document at the schema level. Multiples levels of normal forms for GN-DTD are proposed on the basis of conceptual model approaches and theories of normalization. The normalization rules are applied to transform a poorly designed XML document into a well-designed based on normalized GN-DTD, which is illustrated through examples

A Method for Mapping XML DTD to Relational Schemas In The Presence Of Functional Dependencies

The eXtensible Markup Language (XML) has recently emerged as a standard for data representation and interchange on the web. As a lot of XML data in the web, now the pressure is to manage the data efficiently. Given the fact that relational databases are the most widely used technology for managing and storing XML, therefore XML needs to map to relations and this process is one that occurs frequently. There are many different ways to map and many approaches exist in the literature especially considering the flexible nesting structures that XML allows. This gives rise to the following important problem: Are some mappings ‘better’ than the others? To approach this problem, the classical relational database design through normalization technique that based on known functional dependency concept is referred. This concept is used to specify the constraints that may exist in the relations and guide the design while removing semantic data redundancies. This approach leads to a good normalized relational schema without data redundancy. To achieve a good normalized relational schema for XML, there is a need to extend the concept of functional dependency in relations to XML and use this concept as guidance for the design. Even though there exist functional dependency definitions for XML, but these definitions are not standard yet and still having several limitation. Due to the limitations of the existing definitions, constraints in the presence of shared and local elements that exist in XML document cannot be specified. In this study a new definition of functional dependency constraints for XML is proposed that are general enough to specify constraints and to discover semantic redundancies in XML documents. The focus of this study is on how to produce an optimal mapping approach in the presence of XML functional dependencies (XFD), keys and Data Type Definition (DTD) constraints, as a guidance to generate a good relational schema. To approach the mapping problem, three different components are explored: the mapping algorithm, functional dependency for XML, and implication process. The study of XML implication is important to imply what other dependencies that are guaranteed to hold in a relational representation of XML, given that a set of functional dependencies holds in the XML document. This leads to the needs of deriving a set of inference rules for the implication process. In the presence of DTD and userdefined XFD, other set of XFDs that are guaranteed to hold in XML can be generated using the set of inference rules. This mapping algorithm has been developed within the tool called XtoR. The quality of the mapping approach has been analyzed, and the result shows that the mapping approach (XtoR) significantly improve in terms of generating a good relational schema for XML with respect to reduce data and relation redundancy, remove dangling relations and remove association problems. The findings suggest that if one wants to use RDBMS to manage XML data, the mapping from XML document to relations must based be on functional dependency constraints

Normalization Theory for XML

Abstract. Specifications of XML documents typically consist of typing information (e.g., a DTD), and integrity constraints. Just like relational schema specifications, not all are good – some are prone to redundancies and update anomalies. In the relational world we have a well-developed theory of data design (also known as normalization). A few definitions of XML normal forms have been proposed, but the main question is why a particular design is good. In the XML world, we still lack universally accepted query languages such as relational algebra, or update languages that let us reason about storage redundancies, lossless decompositions, and update anomalies. A better approach, therefore, is to come up with notions of good design based on the intrinsic properties of the model itself. We present such an approach, based on Shannon’s information theory, and show how it applies to relational normal forms as well as to XML design, for both native and relational storage.

XML documents schema design

The eXtensible Markup Language (XML) is fast emerging as the dominant standard for storing, describing and interchanging data among various systems and databases on the intemet. It offers schema such as Document Type Definition (DTD) or XML Schema Definition (XSD) for defining the syntax and structure of XML documents. To enable efficient usage of XML documents in any application in large scale electronic environment, it is necessary to avoid data redundancies and update anomalies. Redundancy and anomalies in XML documents can lead not only to higher data storage cost but also to increased costs for data transfer and data manipulation.To overcome this problem, this thesis proposes to establish a formal framework of XML document schema design. To achieve this aim, we propose a method to improve and simplify XML schema design by incorporating a conceptual model of the DTD with a theory of database normalization. A conceptual diagram, Graph-Document Type Definition (G-DTD) is proposed to describe the structure of XML documents at the schema level. For G- DTD itself, we define a structure which incorporates attributes, simple elements, complex elements, and relationship types among them. Furthermore, semantic constraints are also precisely defined in order to capture semantic meanings among the defined XML objects.In addition, to provide a guideline to a well-designed schema for XML documents, we propose a set of normal forms for G-DTD on the basis of rules proposed by Arenas and Libkin and Lv. et al. The corresponding normalization rules to transform from a G- DTD into a normal form schema are also discussed. A case study is given to illustrate the applicability of the concept. As a result, we found that the new normal forms are more concise and practical, in particular as they allow the user to find an 'optimal' structure of XML elements/attributes at the schema level. To prove that our approach is applicable for the database designer, we develop a prototype of XML document schema design using a Z formal specification language. Finally, using the same case study, this formal specification is tested to check for correctness and consistency of the specification. Thus, this gives a confidence that our prototype can be implemented successfully to generate an automatic XML schema design

Integration of Heterogeneous Databases: Discovery of Meta-Information and Maintenance of Schema-Restructuring Views

In today\u27s networked world, information is widely distributed across many independent databases in heterogeneous formats. Integrating such information is a difficult task and has been adressed by several projects. However, previous integration solutions, such as the EVE-Project, have several shortcomings. Database contents and structure change frequently, and users often have incomplete information about the data content and structure of the databases they use. When information from several such insufficiently described sources is to be extracted and integrated, two problems have to be solved: How can we discover the structure and contents of and interrelationships among unknown databases, and how can we provide durable integration views over several such databases? In this dissertation, we have developed solutions for those key problems in information integration. The first part of the dissertation addresses the fact that knowledge about the interrelationships between databases is essential for any attempt at solving the information integration problem. We are presenting an algorithm called FIND2 based on the clique-finding problem in graphs and k-uniform hypergraphs to discover redundancy relationships between two relations. Furthermore, the algorithm is enhanced by heuristics that significantly reduce the search space when necessary. Extensive experimental studies on the algorithm both with and without heuristics illustrate its effectiveness on a variety of real-world data sets. The second part of the dissertation addresses the durable view problem and presents the first algorithm for incremental view maintenance in schema-restructuring views. Such views are essential for the integration of heterogeneous databases. They are typically defined in schema-restructuring query languages like SchemaSQL, which can transform schema into data and vice versa, making traditional view maintenance based on differential queries impossible. Based on an existing algebra for SchemaSQL, we present an update propagation algorithm that propagates updates along the query algebra tree and prove its correctness. We also propose optimizations on our algorithm and present experimental results showing its benefits over view recomputation

Four Lessons in Versatility or How Query Languages Adapt to the Web

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”

A framework for information integration using ontological foundations

With the increasing amount of data, ability to integrate information has always been a competitive advantage in information management. Semantic heterogeneity reconciliation is an important challenge of many information interoperability applications such as data exchange and data integration. In spite of a large amount of research in this area, the lack of theoretical foundations behind semantic heterogeneity reconciliation techniques has resulted in many ad-hoc approaches. In this thesis, I address this issue by providing ontological foundations for semantic heterogeneity reconciliation in information integration. In particular, I investigate fundamental semantic relations between properties from an ontological point of view and show how one of the basic and natural relations between properties – inferring implicit properties from existing properties – can be used to enhance information integration. These ontological foundations have been exploited in four aspects of information integration. First, I propose novel algorithms for semantic enrichment of schema mappings. Second, using correspondences between similar properties at different levels of abstraction, I propose a configurable data integration system, in which query rewriting techniques allows the tradeoff between accuracy and completeness in query answering. Third, to keep the semantics in data exchange, I propose an entity preserving data exchange approach that reflects source entities in the target independent of classification of entities. Finally, to improve the efficiency of the data exchange approach proposed in this thesis, I propose an extended model of the column-store model called sliced column store. Working prototypes of the techniques proposed in this thesis are implemented to show the feasibility of realizing these techniques. Experiments that have been performed using various datasets show the techniques proposed in this thesis outperform many existing techniques in terms of ability to handle semantic heterogeneities and performance of information exchange

Weak functional dependencies on trees with restructuring

We present an axiomatisation for weak functional dependencies, i.e. disjunctions of functional dependencies, in the presence of several constructors for complex values. The investigated constructors capture records, sets, multisets, lists, disjoint union and optionality, i.e. the complex values are indeed trees. The constructors cover the gist of all complex value data models including object oriented databases and XML. Functional and weak functional dependencies are expressed on a lattice of subattributes, which even carries the structure of a Brouwer algebra as long as the union-constructor is absent. Its presence, however, complicates all results and proofs significantly. The reason for this is that the union-constructor causes non-trivial restructuring rules to hold. In particular, if either the set- or the the union-constructor is absent, a subset of the rules is complete for the implication of ordinary functional dependencies, while in the general case no finite axiomatisation for functional dependencies exists

Exploring novel designs of NLP solvers: Architecture and Implementation of WORHP

Mathematical Optimization in general and Nonlinear Programming in particular, are applied by many scientific disciplines, such as the automotive sector, the aerospace industry, or the space agencies. With some established NLP solvers having been available for decades, and with the mathematical community being rather conservative in this respect, many of their programming standards are severely outdated. It is safe to assume that such usability shortcomings impede the wider use of NLP methods; a representative example is the use of static workspaces by legacy FORTRAN codes. This dissertation gives an account of the construction of the European NLP solver WORHP by using and combining software standards and techniques that have not previously been applied to mathematical software to this extent. Examples include automatic code generation, a consistent reverse communication architecture and the elimination of static workspaces. The result is a novel, industrial-grade NLP solver that overcomes many technical weaknesses of established NLP solvers and other mathematical software