Thu Trinh

Solving the implication problem for XML functional dependencies with properties

Due to the complex nature of XML, finding classes of integrity constraints for XML data that are both expressive and practical is an important but challenging task. In this paper, we study a class of XML functional dependencies (called pXFDs) defined on the basis of tree homomorphism. We establish a semantic equivalence between the implications problems for pXFDs and for propositional Horn clauses, which guarantees linear time decidability of pXFD implication. Hence, pXFDs cannot only be used to capture relevant data semantics, but also be reasoned about efficiently.

On the Notion of an XML Key

Ongoing efforts in academia and industry to advance the management of XML data have created an increasing interest in research on integrity constraints for XML. In particular keys have recently gained much attention. Keys help to discover and capture relevant semantics of XML data, and are crucial for developing better methods and tools for storing, querying and manipulating XML data. Various notions of keys have been proposed and investigated over the past few years. Due to the different ways of picking and comparing data items involved, these proposals give rise to constraint classes that differ in their expressive power and tractability of the associated decision problems. This paper provides an overview of XML key proposals that enjoy popularity in the research literature.

Constraint acquisition for Entity-Relationship models

We establish search algorithms from the area of propositional logic as invaluable tools for the semantic knowledge acquisition in the conceptual database design phase. The acquisition of such domain knowledge is crucial for the quality of the target database. Integrity constraints are conditions that capture the semantics of the application domain under consideration. They restrict the databases to those that are considered meaningful to the application at hand. In practice, the decision of specifying a constraint is very important and extremely challenging. We show how techniques from propositional logic can be utilised to offer decision support for specifying Boolean and multivalued dependencies between properties of entities and relationships in conceptual databases. In particular, we use a search version of SAT-solvers to semi-automatically generate sample databases for this class of dependencies in Entity-Relationship models. The sample databases enable design participants to judge, justify, convey and test their understanding of the semantics of the future database. Indeed, the decision by the participants to specify a dependency explicitly is reduced to their decision whether there is some sample database that they can accept as a future database instance.

Using transversals for discovering XML functional dependencies

Dependency discovery is an important technique for relational database design due to numerous applications like normalisation and query optimisation. Similar applications are likely to exist in the context of XML. To date, there are few investigations into dependency discovery in the context of XML. We propose a transversal approach for discovering a class of subgraph-based XML functional dependencies with pre-image semantics (XFDs). We cover all aspects of the discovery process, from determining agree sets to the extraction of an XFD cover. An inherent challenge is the large and complex search space of valid XFDs due to the tree-structure of XML data.

Efficient reasoning about XFDs with pre-image semantics

The study of integrity constraints has been identified as one of the major challenges in XML database research. The main difficulty is finding a balance between the expressiveness and the existence of automated reasoning tools. We investigate a previous proposal for functional dependencies in XML (XFDs) that is based on homomorphisms between data trees and schema trees. We demonstrate that reasoning about our XFDs is well-founded. We provide a finite axiomatisation and show that their implication is equivalent to the logical implication of propositional Horn clauses and thus decidable in time linear in the size of the constraints. Hence, our XFDs do not only capture valuable semantic information but also permit efficient automated reasoning support.

On the Existence of Armstrong Data Trees for XML Functional Dependencies

Armstrong databases are a popular tool in example-based database design. An Armstrong database for a given constraint set Σ from a fixed constraint class

Axiomatising functional dependencies for XML with frequencies

\mathcal Z

Know your limits: enhanced XML modeling with cardinality constraints

satisfies precisely those constraints from

Boolean Constraints for XML Modeling

\mathcal Z

Sample-based Decision Support for Specifying XML

that are logically implied by Σ. In this paper we study Armstrong data trees for functional dependencies for XML-encoded data in the context of a simple XML tree model reflecting the permitted parent-child relationships together with their frequencies.