Mosto: Generating SPARQL Executable Mappings between Ontologies

Data translation is an integration task that aims at populating a target model with data of a source model, which is usually performed by means of mappings. To reduce costs, there are some techniques to automatically generate executable mappings in a given query language, which are executed using a query engine to perform the data translation task. Unfortunately, current approaches to automatically generate executable mappings are based on nested relational models, which cannot be straightforwardly applied to semantic-web ontologies due to some differences between both models. In this paper, we present Mosto, a tool to perform the data translation using automatically generated SPARQL executable mappings. In this demo, ER attendees will have an opportunity to test this automatic generation when performing the data translation task between two different versions of the DBpedia ontology.Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08- TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010-21744Ministerio de Ciencia e Innovación TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-

HaIRST: Harvesting Institutional Resources in Scotland Testbed. Final Project Report

The HaIRST project conducted research into the design, implementation and deployment of a pilot service for UK-wide access of autonomously created institutional resources in Scotland, the aim being to investigate and advise on some of the technical, cultural, and organisational requirements associated with the deposit, disclosure, and discovery of institutional resources in the JISC Information Environment. The project involved a consortium of Scottish higher and further education institutions, with significant assistance from the Scottish Library and Information Council. The project investigated the use of technologies based on the Open Archives Initiative (OAI), including the implementation of OAI-compatible repositories for metadata which describe and link to institutional digital resources, the use of the OAI protocol for metadata harvesting (OAI-PMH) to automatically copy the metadata from multiple repositories to a central repository, and the creation of a service to search and identify resources described in the central repository. An important aim of the project was to identify issues of metadata interoperability arising from the requirements of individual institutional repositories and their impact on services based on the aggregation of metadata through harvesting. The project also sought to investigate issues in using these technologies for a wide range of resources including learning, teaching and administrative materials as well as the research and scholarly communication materials considered by many of the other projects in the JISC Focus on Access to Institutional Resources (FAIR) Programme, of which HaIRST was a part. The project tested and implemented a number of open source software packages supporting OAI, and was successful in creating a pilot service which provides effective information retrieval of a range of resources created by the project consortium institutions. The pilot service has been extended to cover research and scholarly communication materials produced by other Scottish universities, and administrative materials produced by a non-educational institution in Scotland. It is an effective testbed for further research and development in these areas. The project has worked extensively with a new OAI standard for 'static repositories' which offers a low-barrier, low-cost mechanism for participation in OAI-based consortia by smaller institutions with a low volume of resources. The project identified and successfully tested tools for transforming pre-existing metadata into a format compliant with OAI standards. The project identified and assessed OAI-related documentation in English from around the world, and has produced metadata for retrieving and accessing it. The project created a Web-based advisory service for institutions and consortia. The OAI Scotland Information Service (OAISIS) provides links to related standards, guidance and documentation, and discusses the findings of HaIRST relating to interoperability and the pilot harvesting service. The project found that open source packages relating to OAI can be installed and made to interoperate to create a viable method of sharing institutional resources within a consortium. HaIRST identified issues affecting the interoperability of shared metadata and suggested ways of resolving them to improve the effectiveness and efficiency of shared information retrieval environments based on OAI. The project demonstrated that application of OAI technologies to administrative materials is an effective way for institutions to meet obligations under Freedom of Information legislation

Composition and Inversion of Schema Mappings

In the recent years, a lot of attention has been paid to the development of solid foundations for the composition and inversion of schema mappings. In this paper, we review the proposals for the semantics of these crucial operators. For each of these proposals, we concentrate on the three following problems: the definition of the semantics of the operator, the language needed to express the operator, and the algorithmic issues associated to the problem of computing the operator. It should be pointed out that we primarily consider the formalization of schema mappings introduced in the work on data exchange. In particular, when studying the problem of computing the composition and inverse of a schema mapping, we will be mostly interested in computing these operators for mappings specified by source-to-target tuple-generating dependencies

An Evolution-based Approach for Assessing Ontology Mappings - A Case Study in the Life Sciences

Ontology matching has been widely studied. However, the resulting on-tology mappings can be rather unstable when the participating ontologies or util-ized secondary sources (e.g., instance sources, thesauri) evolve. We propose an evolution-based approach for assessing ontology mappings by annotating their cor-respondences by information about similarity values for past ontology versions. These annotations allow us to assess the stability of correspondences over time and they can thus be used to determine better and more robust ontology mappings. The approach is generic in that it can be applied independently from the utilized match technique. We define different stability measures and show results of a first evaluation for the life science domain

Towards Transformation Rule Composition

Many model transformation problems require different intermediate transformation steps. For example, platform-specific models (PSM) are often generated from platform-independent models (PIM) by chains of model transformations. This requires the presence of several intermediate meta-models between those of the PIM and the PSM. Thus, most of the effort is needed to define a transformation mechanism for each intermediate step. The solution proposed in this paper is to investigate whether it is possible to generate a single transformation from a chain of transformations, solely involving the initial PIM and final PSM meta-models. The presented work focuses on the composition of transformations at the rule level. We apply the automatic procedure for composing rules in the context of the evolution of the Enterprise Java Beans (EJB) language, transforming UML models into EJB 2.0 models and then to EJB 3.0 models