Accessing and Documenting Relational Databases through OWL ontologies

Relational databases have been designed to store high volumes of data and to provide an efficient query interface. Ontologies are geared towards capturing domain knowledge, annotations, and to offer high-level, machine-processable views of data and metadata. The complementary strengths and weaknesses of these data models motivate the research effort we present in this paper. The goal of this work is to bridge the relational and ontological worlds, in order to leverage the efficiency and scalability of relational technologies and the high level view of data and metadata proper of ontologies. The system we designed and developed achieves: (i) automatic ontology extraction from relational data sources and (ii) automatic query translation from SPARQL to SQL. Among the others, we focus on two main applications of this novel technology: (i) ontological publishing of relational data, and (ii) automatic relational schema annotation and documentation. The system has been designed and tested against real life scenarios from Big Science projects, which are used as running examples throughout the paper

SCHEMA, EVOLUTION IN WIKIPEDIA Toward a Web Information System Benchmark

Evolving the database that is at the core of an Information System represents a difficult maintenance problem that has only been studied in the framework of traditional information systems. However, the problem is likely to be even more severe in web information systems, where open-source software is often developed through the contributions and collaboration of many groups and individuals. Therefore, in this paper, we present an in-depth analysis of the evolution history of the Wikipedia database and its schema; Wikipedia is the best-known example of a large family of web information systems built using the open-source software MediaWiki. Our study is based on: (i) a set of Schema Modification Operators that provide a simple conceptual representation for complex schema changes, and (ii) simple software tools to automate the analysis. This framework allowed us to dissect and analyze the 4.5 years of Wikipedia history, which was short in time, but intense in terms of growth and evolution. Beyond confirming the initial hunch about the severity of the problem, our analysis suggests the need for developing better methods and tools to support graceful schema evolution. Therefore, we briefly discuss documentation and automation support systems for database evolution, and suggest that the Wikipedia case study can provide the kernel of a benchmark for testing and improving such systems

Open-Source Databases: Within, Outside, or Beyond Lehman’s Laws of Software Evolution?

Abstract. Lehman’s laws of software evolution is a well-established set of observations (matured during the last forty years) on how the typical software systems evolve. However, the applicability of these laws on databases has not been studied so far. To this end, we have performed a thorough, large-scale study on the evolution of databases that are part of larger open source projects, publicly available through open source repositories, and report on the validity of the laws on the grounds of properties like size, growth, and amount of change per version

A data-oriented survey of context models

Context-aware systems are pervading everyday life, there- fore context modeling is becoming a relevant issue and an expanding research field. This survey has the goal to pro- vide a comprehensive evaluation framework, allowing appli- cation designers to compare context models with respect to a given target application; in particular we stress the anal- ysis of those features which are relevant for the problem of data tailoring. The contribution of this paper is twofold: a general analysis framework for context models and an up- to-date comparison of the most interesting, data-oriented approaches available in the literature

Context information for Knowledge reshaping

More and more often, we face the necessity of extracting appropriately reshaped knowledge from an integrated representation of the information space. Be such a global representation a central database, a global view of several ones or an ontological representation of an information domain, we face the need to define personalised views for the knowledge stakeholders: single users, companies or applications. We propose exploiting the information usage context within a methodology for context-aware data design, where the notion of context is formally defined together with its role within the process of view building by information tailoring. This paper presents our context model, called the context dimension tree, which plays a fundamental role in tailoring the information space according to user information needs

Emergent Semantics and Cooperation in Multi-Knowledge Environments: the ESTEEM Architecture

In the present global society, information has to be exchangeable in open and dynamic environments, where interacting peers do not necessarily share a common,understanding of the world at hand, and do not have a complete picture of the context where the interaction occurs. In this paper, we present the Esteem approach and the related peer architecture for emergent semantics in dynamic and multi-knowledge environments. In Esteem, semantic communities are built around declared interests in the form of manifesto ontologies, and their autonomous nature is preserved by allowing a shared semantics to naturally emerge, from peer interactions

Emergent semantics and cooperation in multi−knowledge environments: The ESTEEM architecture

In the present global society, information has to be exchangeable in open and dynamic environments, where interacting peers do not necessarily share a common understanding of the world at hand, and do not have a complete picture of the context where the interaction occurs. In this paper, we present the Esteem approach and the related peer architecture for emergent semantics in dynamic and multi-knowledge environments. In Esteem, semantic communities are built around declared interests in the form of manifesto ontologies, and their autonomous nature is preserved by allowing a shared semantics to naturally emerge from peer interactions