Archiving scientific data

We present an archiving technique for hierarchical data with key structure. Our approach is based on the notion of timestamps whereby an element appearing in multiple versions of the database is stored only once along with a compact description of versions in which it appears. The basic idea of timestamping was discovered by Driscoll et. al. in the context of persistent data structures where one wishes to track the sequences of changes made to a data structure. We extend this idea to develop an archiving tool for XML data that is capable of providing meaningful change descriptions and can also efficiently support a variety of basic functions concerning the evolution of data such as retrieval of any specific version from the archive and querying the temporal history of any element. This is in contrast to diff-based approaches where such operations may require undoing a large number of changes or significant reasoning with the deltas. Surprisingly, our archiving technique does not incur any significant space overhead when contrasted with other approaches. Our experimental results support this and also show that the compacted archive file interacts well with other compression techniques. Finally, another useful property of our approach is that the resulting archive is also in XML and hence can directly leverage existing XML tools

UML to XML-Schema Transformation: a Case Study in Managing Alternative Model Transformations in MDA

In a Model Driven Architecture (MDA) software development process, models are\ud repeatedly transformed to other models in order to finally achieve a set of models with enough details to implement a system. Generally, there are multiple ways to transform one model into another model. Alternative target models differ in their quality properties and the selection of a particular model is determined on the basis of specific requirements. Software engineers must be able to identify, compare and select the appropriate transformations within the given set of requirements. The current transformation languages used for describing and executing model transformations only provide means to specify the transformations but do not help to identify and select from the alternative transformations. In this paper we propose a process and a set of techniques for constructing a transformation space for a given transformation problem. The process uses a source model, its meta-model and the meta-model of the target as input and generates a transformation space. Every element in that space represents a transformation that produces a result that is an instance of the target meta-model. The requirements that must be fulfilled by the result are captured and represented in a quality model. We explain our approach using an illustrative example for transforming a platform independent model expressed in UML into platform specific models that represent XML schemas. A particular quality model of extensibility is presented in the paper

Biochemical network matching and composition

This paper looks at biochemical network matching and compositio

Representations of sources and data: working with exceptions to hierarchy in historical documents

No abstract available

Bigraphical Logics for XML

Bigraphs have been recently proposed as a meta-model for global computing resources; they are built orthogonally on two structures: a hierarchical ‘place’ graph for locations and a ‘link’ (hyper-)graph for connections. XML is now the standard meta-language for the data exchange and storage on the web. In this paper we address the similarities between bigraphs and XML and we propose bigraphs as a rich model for XML (and XML contexts). Building on this idea we proceed by investigating how the recently proposed logic of BiLog can be instantiated to describe, query and reason about web data (and web contexts)

Adding Logical Operators to Tree Pattern Queries on Graph-Structured Data

As data are increasingly modeled as graphs for expressing complex relationships, the tree pattern query on graph-structured data becomes an important type of queries in real-world applications. Most practical query languages, such as XQuery and SPARQL, support logical expressions using logical-AND/OR/NOT operators to define structural constraints of tree patterns. In this paper, (1) we propose generalized tree pattern queries (GTPQs) over graph-structured data, which fully support propositional logic of structural constraints. (2) We make a thorough study of fundamental problems including satisfiability, containment and minimization, and analyze the computational complexity and the decision procedures of these problems. (3) We propose a compact graph representation of intermediate results and a pruning approach to reduce the size of intermediate results and the number of join operations -- two factors that often impair the efficiency of traditional algorithms for evaluating tree pattern queries. (4) We present an efficient algorithm for evaluating GTPQs using 3-hop as the underlying reachability index. (5) Experiments on both real-life and synthetic data sets demonstrate the effectiveness and efficiency of our algorithm, from several times to orders of magnitude faster than state-of-the-art algorithms in terms of evaluation time, even for traditional tree pattern queries with only conjunctive operations.Comment: 16 page