Cendrarsiana

Schema mappings have been extensively studied in the context of data exchange and data integration, where they have turned out to be the right level of abstraction for formalizing data interoperability tasks. Up to now and for the most part, schema mappings have been studied as static objects, in the sense that each time the focus has been on a single schema mapping of interest or, in the case of composition, on a pair of schema mappings of interest. In this paper, we adopt a dynamic viewpoint and embark on a study of sequences of schema mappings and of the limiting behavior of such sequences. To this effect, we first introduce a natural notion of distance on sets of finite target instances that expresses how "Close" two sets of target instances are as regards the certain answers of conjunctive queries on these sets. Using this notion of distance, we investigate pointwise limits and uniform limits of sequences of schema mappings, as well as the companion notions of pointwise Cauchy and uniformly Cauchy sequences of schema mappings. We obtain a number of results about the limits of sequences of GAV schema mappings and the limits of sequences of LAV schema mappings that reveal striking differences between these two classes of schema mappings. We also consider the completion of the metric space of sets of target instances and obtain concrete representations of limits of sequences of schema mappings in terms of generalized schema mappings, that is, schema mappings with infinite target instances as solutions to (finite) source instances

Data exchange and schema mappings in open and closed worlds

In the study of data exchange one usually assumes an open-world semantics, making it possible to extend instances of target schemas. An alternative closed-world semantics only moves ‘as much data as needed’ from the source to the target to satisfy constraints of a schema mapping. It avoids some of the problems exhibited by the open-world semantics, but limits the expressivity of schema mappings. Here we propose a mixed approach: one can designate different attributes of target schemas as open or closed, to combine the additional expressivity of the open-world semantics with the better behavior of query answering in closed worlds. We define such schema mappings, and show that they cover a large space of data exchange solutions with two extremes being the known open and closed-world semantics. We investigate the problems of query answering and schema mapping composition, and prove two trichotomy theorems, classifying their complexity based on the number of open attributes. We find conditions under which schema mappings compose, extending known results to a wide range of closed-world mappings. We also provide results for restricted classes of queries and mappings guaranteeing lower complexity

UK utility data integration: overcoming schematic heterogeneity

In this paper we discuss syntactic, semantic and schematic issues which inhibit the integration of utility data in the UK. We then focus on the techniques employed within the VISTA project to overcome schematic heterogeneity. A Global Schema based architecture is employed. Although automated approaches to Global Schema definition were attempted the heterogeneities of the sector were too great. A manual approach to Global Schema definition was employed. The techniques used to define and subsequently map source utility data models to this schema are discussed in detail. In order to ensure a coherent integrated model, sub and cross domain validation issues are then highlighted. Finally the proposed framework and data flow for schematic integration is introduced

A vocabulary-independent generation framework for DBpedia and beyond

The dbpedia Extraction Framework, the generation framework behind one of the Linked Open Data cloud’s central hubs, has limitations which lead to quality issues with the dbpedia dataset. Therefore, we provide a new take on its Extraction Framework that allows for a sustainable and general-purpose Linked Data generation framework by adapting a semantic-driven approach. The proposed approach decouples, in a declarative manner, the extraction, transformation, and mapping rules execution. This way, among others, interchanging different schema annotations is supported, instead of being coupled to a certain ontology as it is now, because the dbpedia Extraction Framework allows only generating a certain dataset with a single semantic representation. In this paper, we shed more light to the added value that this aspect brings. We provide an extracted dbpedia dataset using a different vocabulary, and give users the opportunity to generate a new dbpedia dataset using a custom combination of vocabularies

A framework for utility data integration in the UK

In this paper we investigate various factors which prevent utility knowledge from being fully exploited and suggest that integration techniques can be applied to improve the quality of utility records. The paper suggests a framework which supports knowledge and data integration. The framework supports utility integration at two levels: the schema and data level. Schema level integration ensures that a single, integrated geospatial data set is available for utility enquiries. Data level integration improves utility data quality by reducing inconsistency, duplication and conflicts. Moreover, the framework is designed to preserve autonomy and distribution of utility data. The ultimate aim of the research is to produce an integrated representation of underground utility infrastructure in order to gain more accurate knowledge of the buried services. It is hoped that this approach will enable us to understand various problems associated with utility data, and to suggest some potential techniques for resolving them