The massive semantic data sources linked in the Web of Data give new meaning to old features like navigation; introduce new challenges like semantic specification of Web fragments; and make it possible to specify actions relying on semantic data. In this paper we introduce a declarative language to face these challenges. Based on navigational features, it is designed to specify fragments of the Web of Data and actions to be performed based on these data. We implement it in a centralized fashion, and show its power and performance. Finally, we explore the same ideas in a distributed setting, showing their feasibility, potentialities and challenges.
Extend SPARQL with navigational features. The SERVICE feature of SPARQL 1.1 and proposals like the one of @cite_12 extend the scope of SPARQL queries with navigational features @cite_12 @cite_23 . The system SQUIN, based on link-traversal , a query execution paradigm that discover on the fly data sources relevant for the query, permits to automatically navigate to other sources while executing a query.
@cite_23 @cite_12
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Navigational features have been largely recognized as fundamental for graph database query languages. This fact has motivated several authors to propose RDF query languages with navigational capabilities. In this paper, we propose the query language nSPARQL that uses nested regular expressions to navigate RDF data. We study some of the fundamental properties of nSPARQL and nested regular expressions concerning expressiveness and complexity of evaluation. Regarding expressiveness, we show that nSPARQL is expressive enough to answer queries considering the semantics of the RDFS vocabulary by directly traversing the input graph. We also show that nesting is necessary in nSPARQL to obtain this last result, and we study the expressiveness of the combination of nested regular expressions and SPARQL operators. Regarding complexity of evaluation, we prove that given an RDF graph G and a nested regular expression E, this problem can be solved in time O(|G|@?|E|). Link traversal based query execution is a new query execution paradigm for the Web of Data. This approach allows the execution engine to discover potentially relevant data during the query execution and, thus, enables users to tap the full potential of the Web. In earlier work we propose to implement the idea of link traversal based query execution using a synchronous pipeline of iterators. While this idea allows for an easy and efficient implementation, it introduces restrictions that cause less comprehensive result sets. In this paper we address this limitation. We analyze the restrictions and discuss how the evaluation order of a query may affect result set size and query execution costs. To identify a suitable order, we propose a heuristic for our scenario where no a-priory information about relevant data sources is present. We evaluate this heuristic by executing real-world queries over the Web of Data. The last decade witnessed a growing interest in research on content-based image retrieval (CBIR) and related areas. Several systems for managing and retrieving images have been proposed, each one tailored to a specific application. Functionalities commonly available in CBIR systems include: storage and management of complex data, development of feature extractors to support similarity queries, development of index structures to speed up image retrieval, and design and implementation of an intuitive graphical user interface tailored to each application. To facilitate the development of new CBIR systems, we propose an image-handling extension to the relational database management system (RDBMS) PostgreSQL. This extension, called PostgreSQL-IE, is independent of the application and provides the advantage of being open source and portable. The proposed system extends the functionalities of the structured query language SQL with new functions that are able to create new feature extraction procedures, new feature vectors as combinations of previously defined features, and new access methods, as well as to compose similarity queries. PostgreSQL-IE makes available a new image data type, which permits the association of various images with a given unique image attribute. This resource makes it possible to combine visual features of different images in the same feature vector. To validate the concepts and resources available in the proposed extended RDBMS, we propose a CBIR system applied to the analysis of mammograms using PostgreSQL-IE. SPARQL -the standard query language for querying RDF- provides only limited navigational functionalities, although these features are of fundamental importance for graph data formats such as RDF. This has led the W3C to include the property path feature in the upcoming version of the standard, SPARQL 1.1.We tested several implementations of SPARQL 1.1 handling property path queries, and we observed that their evaluation methods for this class of queries have a poor performance even in some very simple scenarios. To formally explain this fact, we conduct a theoretical study of the computational complexity of property paths evaluation. Our results imply that the poor performance of the tested implementations is not a problem of these particular systems, but of the specification itself. In fact, we show that any implementation that adheres to the SPARQL 1.1 specification (as of November 2011) is doomed to show the same behavior, the key issue being the need for counting solutions imposed by the current specification. We provide several intractability results, that together with our empirical results, provide strong evidence against the current semantics of SPARQL 1.1 property paths. Finally, we put our results in perspective, and propose a natural alternative semantics with tractable evaluation, that we think may lead to a wide adoption of the language by practitioners, developers and theoreticians.