Processing Regular Path Queries on Arbitrarily Distributed Data

Regular Path Queries (RPQs) are a type of graph query where answers are pairs of nodes connected by a sequence of edges matching a regular expression. We study the techniques to process such queries on a distributed graph of data. While many techniques assume the location of each data element (node or edge) is known, when the components of the distributed system are autonomous, the data will be arbitrarily distributed. As the different query processing strategies are equivalently costly in the worst case, we isolate query-dependent cost factors and present a method to choose between strategies, using new query cost estimation techniques. We evaluate our techniques using meaningful queries on biomedical data

An introduction to Graph Data Management

A graph database is a database where the data structures for the schema and/or instances are modeled as a (labeled)(directed) graph or generalizations of it, and where querying is expressed by graph-oriented operations and type constructors. In this article we present the basic notions of graph databases, give an historical overview of its main development, and study the main current systems that implement them

Evolving Objects in Temporal Information Systems

This paper presents a semantic foundation of temporal conceptual models used to design temporal information systems. We consider a modelling language able to express both timestamping and evolution constraints. We conduct a deeper investigation of evolution constraints, eventually devising a model-theoretic semantics for a full-fledged model with both timestamping and evolution constraints. The proposed formalization is meant both to clarify the meaning of the various temporal constructors that appeared in the literature and to give a rigorous definition, in the context of temporal information systems, to notions like satisfiability, subsumption and logical implication. Furthermore, we show how to express temporal constraints using a subset of first-order temporal logic, i.e. DLRUS, the description logic DLR extended with the temporal operators Since and Until. We show how DLRUS is able to capture the various modelling constraints in a succinct way and to perform automated reasoning on temporal conceptual models

Reasoning about Summarizability in Heterogeneous Multidimensional Schemas

. In OLAP applications, data are modeled as points in a multidimensional space. Dimensions themselves have structure, described by a schema and an instance; the schema is basically a directed acyclic graph of granularity levels, and the instance consists of a set of elements for each level and mappings between these elements, usually called rollup functions. Current dimension models restrict dimensions in various ways; for example, rollup functions are restricted to be total. We relax these restrictions, yielding what we call heterogeneous schemas, which describe more naturally and cleanly many practical situations. In the context of heterogeneous schemas, the notion of summarizability becomes more complex. An aggregate view defined at some granularity level is summarizable from a set of precomputed views defined at other levels if the rollup functions can be used to compute the first view from the set of views. In order to study summarizability in heterogeneous schemas, ..