RDFKB: A Semantic Web Knowledge Base

The Semantic Web is gaining increasing interest to fulfill the need of sharing and reusing information. In this context, RDF has been conceived to provide an easy way to represent any kind of data and metadata, according to a graph-based, lightweight model and a straight XML serialization. Although RDF has the advantage of being general and simple, it cannot be used as a storage model as it is, since it can be easily shown that even simple management operations involve serious performance limitations. Starting from an analysis of the current state of the art for RDF data management, we present in this paper a novel approach for storing, managing and processing RDF data in an effective and efficient way. The approach is based on an organization that is particularly suited for RDF constructs, but it can be easily extended to other models that relies on RDF, like RDFS and/or OWL. We refer to real world scenarios in which large RDF data repositories need to be navigated and processed, even if the schema is not known in advance. We consider complex data management operations, which go beyond simple selections or projections and involve the navigation of huge portions of data sources. A tool has been developed to test the feasibility of the approach over large RDF repositories (datasets of millions of triples). We compare the performance of the proposed framework with prior solutions and present experimental results supporting its effectiveness and efficiency.

2001

The Semantic Web is a logical evolution of the existing Web. It is based on a common conceptual data model of great generality that allows both humans and machines to work with interrelated, but disjoint, information as if it was a single global database. The design and implementation of a general, scalable, federated and flexible data storage and indexing model, which corresponds to the data model of the Semantic Web, is fundamental for the success and deployment of such a system. The generality of the RDF data model presents unique challenges to efficient storage, indexing and querying engines. This paper presents our experience and work related to RDFStore which implements a new flexible indexing and query model. The model is tailored to RDF data and is designed around the Semantic Web from the ground up. The paper describes the underlying indexing algorithm, together with comparisons to other existing RDF storage and query strategies.

WSEAS Transactions on …, 2006

Although the faster development of the semantic web technologies provides new scenarios to interchange and interoperate among different automated or semi automated systems, in big datasets, there are several problems that influence in a low performance. On the other hand, due to the special store mode of RDF data the inference and reasoning capabilities are more costly. In a web server environment, this fact not provides a real room to enable the semantic web vision. We are developing a new approach to semantic data inference based on the use of object oriented storage technologies.

2019

The Resource Description Framework (RDF) data presentation model and the SPARQL query language have been the core of the semantic web technologies since the early 2000’s. In this article, we evaluate three RDF storage technologies. Our motivation is to find a storage solution that can be used to process “big data” RDF sets. Our method is based on measuring query response times with large samples (hundreds of thousands of RDF documents, millions of RDF statements). We find that all the proposed technologies provide much better performance than querying RDF data stored in files. However, with 300 000 documents, even with the fastest technology, an aggregation query still lasts more than 100 seconds in our environment. As a further performance improvement, we test the same data and queries with MongoDB, demonstrate its performance (10 seconds instead of 100) and scalability (up to 1000 000 documents). However, despite its benefits we must note that because of its data presentation and ...

World Wide Web

The Semantic Web is gaining increasing interest to fulfill the need of sharing, retrieving, and reusing information. In this context, the Resource Description Framework (RDF) has been conceived to provide an easy way to represent any kind of data and metadata, according to a lightweight model and syntaxes for serialization (RDF/XML, N3, etc.). Despite RDF has the advantage of being general and simple, it cannot be used as a storage model as it is, since it can be easily shown that even simple management operations involve serious performance limitations. In this paper we present a framework which provides a flexible and persistent layer relying on a novel storage model that guarantees good scalability and performance of query evaluation. The approach is based on the notion of construct, that represents a concept of the domain of interest. This makes the approach easily extensible and independent from the specific knowledge representation language. Based on this representation, reasoning capabilities are supported by a rule-based engine. Finally we present experimental results over real world scenarios to demonstrate the feasibility of the approach.

IEEE Data(base) Engineering Bulletin - DEBU, 2003

To realize the vision of the Semantic Web, efficient sto rage and retrieval of large RDF data sets is required. A common technique for persisting RDF data (graphs) is to use a single relational database table, a triple store. But, we believe a single triple store cannot scale for large-scale applications. This paper describes storing and querying persistent RDF graphs in Jena, a Semantic Web programmers' toolkit. Jena augments the triple store with property tables that cluster multiple property values in a single table row. We also describe two tools to assist in designing application-specific RDF sto rage schema. The first is a synthetic data generator that generates RDF graphs consistent with an underlying ontology. The second mines an RDF graph or an RDF query log for frequently occurring patterns. These patterns can be applied to schema design or caching strategies to improve performance. We also briefly describe Jena inferencing and a new approach to context in RDF which w...

Proc. 20th Int. FLAIRS Conf., AAAI Press, 2007

Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form. As the volume of Semantic Web data grows, software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to perform their tasks. We will discuss the general issues underlying the indexing and retrieval of RDF-based information and describe Swoogle, a crawler based search engine whose index contains information on over two million RDF documents, and Tripleshop, which uses Swoogle to automatically build datasets appropriate for responding to user supplied queries. We will illustrate their use in ELVIS (Ecosystem Location Visualization and Information System), a distributed platform for constructing end-to-end use cases that demonstrate the semantic web's utility for integrating scientific data.

2016

SQL and, more recently, SPARQL are standard languages of the software industry for retrieving data. Other studies showed that retrieving data by using a SPARQL query is much slower than the semantically equivalent SQL query. Nevertheless, some recent proposals optimized database servers for SPARQL queries. This paper presents the results of a comparative analysis between the capability of SQL and SPARQL with respect to the retrieval of data from a relational database and RDF-triples. A free and open source-based scenario was constructed by using PostgreSQL and Virtuoso for storing data, and RETRI, a data retrieving software built in JavaScript which displays data views in a specific XML format. Open data from the British National Library Bibliographic Data Set were used in the experiment; results were analyzed from a performance perspective. Keywords: Data views, retrieving process performance, semantic web. RESUMEN SQL y mas recientemente SPARQL, son lenguajes estandares para la re...

The web is changing the way in which data warehouses are designed, used, and queried. With the advent of initiatives such as Open Data and Open Government, organizations want to share their multidimensional data cubes and make them available to be queried online. The RDF data cube vocabulary (QB), the W3C standard to publish statistical data in RDF, presents several limitations to fully support the multidimensional model. The QB4OLAP vocabulary extends QB to overcome these limitations, allowing to implement the typical OLAP operations, such as rollup, slice, dice, and drill-across using standard SPARQL queries. In this paper we introduce a formal data model where the main object is the data cube, and define OLAP operations using this model, independent of the underlying representation of the cube. We show then that a cube expressed using our model can be represented using the QB4OLAP vocabulary, and finally we provide a SPARQL implementation of OLAP operations over data cubes in QB4OLAP.

ACM SIGMOD Record, 2013