Approaching OBDA Evolution through Mapping Repair

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An Online Bibliography on Scheme Evolution

We briefly motivate and present a new online bibliography on schema evolution, an area which has recently gained much interest in both research and practice

Using Ontologies for Semantic Data Integration

While big data analytics is considered as one of the most important paths to competitive advantage of today’s enterprises, data scientists spend a comparatively large amount of time in the data preparation and data integration phase of a big data project. This shows that data integration is still a major challenge in IT applications. Over the past two decades, the idea of using semantics for data integration has become increasingly crucial, and has received much attention in the AI, database, web, and data mining communities. Here, we focus on a specific paradigm for semantic data integration, called Ontology-Based Data Access (OBDA). The goal of this paper is to provide an overview of OBDA, pointing out both the techniques that are at the basis of the paradigm, and the main challenges that remain to be addressed

Consistent Ontologies Evolution Using Graph Grammars

Ontologies are often used for the meta-modelling of dynamic domains, therefore it is essential to represent and manage their changes and to adapt them to new requirements. Due to changes, an ontology may become invalid and non-interpretable. This paper proposes the use of the graph grammars to formalize and manage ontologies evolution. The objective is to present an a priori approach of inconsistencies resolutions to adapt the ontologies and preserve their consistency. A framework composed of different graph rewriting rules is proposed and presented using the AGG (Algebraic Graph Grammar) tool. As an application, the article considers the EventCCAlps ontology developed within the CCAlps European project

Robust and simple database evolution

Software developers adapt to the fast-moving nature of software systems with agile development techniques. However, database developers lack the tools and concepts to keep the pace. Whenever the current database schema is evolved, the already existing data needs to be evolved as well. This is usually realized with manually written SQL scripts, which is error-prone and explains significant costs in software projects. A promising solution are declarative database evolution languages, which couple both schema and data evolution into intuitive operations. Existing database evolution languages focus on usability but do not strive for completeness. However, this is an inevitable prerequisite to avoid complex and error-prone workarounds. We present CODEL which is based on an existing language but is relationally complete. We precisely define its semantic using relational algebra, propose a syntax, and formally validate its relational completeness. Having a complete and comprehensive database evolution language facilitates valuable support throughout the whole evolution of a database. As an instance, we present VACO, a tool supporting developers with variant co-evolution. Given a variant schema derived from a core schema, VACO uses the richer semantics of CODEL to semi-automatically co-evolve this variant with the core