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Graphs represent an increasingly popular data model for data-analytics, since they can naturally represent relationships and interactions between entities. Relational databases and their pure table-based data model are not well suitable to store and process sparse data. Consequently, graph databases have gained interest in the last few years and the Resource Description Framework (RDF) became the...
RDF models are widely used in the web of data due to their flexibility and similarity to graph patterns. Because of the growing use of RDFs, their volumes and contents are increasing. Therefore, processing of such massive amount of data on a single machine is not efficient enough, because of the response time and limited hardware resources. A common approach to overcome this limitation is cluster...
OpenSpending is the world's largest repository of open fiscal datasets. As of now it only supported loading datasets from CSV files, leaving out more heavily-structured formats like RDF. Rudolf, an RDF backend has been developed to expose Data Cube RDF triples and OLAP operations in JSON format through an OpenSpending-compatible HTTP API. This API can be directly utilized by the OpenSpending Viewer...
Distributed and replicated systems, such as Big Data applications, deal with conflicting and duplicated data. Therefore, it is needed a database with flexible data model to materialize the data and an end-user oriented interface in order to allow queries in heterogeneous data. Using OBDA approach in a Graph Database is an attempt to solve these problems. However, new problems arise regarding hierarchical...
The Global Change Information System was created by the US Global Change Research Program to provide specialists and the general public with accessible and usable global change related information. This system uses a relational and semantic web approach to describe the detailed provenance of global change information, such as “in report x, figure y is derived from dataset z”. The system supported...
In the context of large engineering projects the effective and efficient exchange and versioning of information from different engineering disciplines is essential. Semantic data integration approaches provide the necessary means to overcome the gap between heterogeneous local engineering tool concepts and common project-level concepts which enable the mapping of engineering data coming from different...
Graph analysis has revealed patterns and relationships hidden in data from a variety of domains such as transportation networks, social networks, clinical pathways, and collaboration networks. As these networks grow in size, variety and complexity, it is a challenge to find the right combination of tools and implementation of algorithms to discover new insights from the data. Addressing this challenge,...
In order to easily query and blend structured data on the web a query formulation language is presented. The core novelty of this is that it permits people with restricted IT skills to explore and query one (or multiple) data sources without prior knowledge about the schema, structure, terminology, or any technological details of these sources. Data source considered may be either an offline or inline...
A data space system manages a variety of heterogeneous data in integrated and incremental fashion. In order to populate the data uniformly requires a data publication tool which will able to extract the data from the data sources, and translate them into a regular format. In this paper, we have proposed a flexible architecture of Data space Publishing Tool (DSP Tool) for publishing the heterogeneous...
Large systems engineering projects involve the cooperation of various stakeholders from different engineering disciplines. Individual stakeholders apply various tools and related data storage approaches that (a) might hinder seamless interoperability and (b) include limited capability to support data versioning. Project-level concepts enable the mapping of engineering data coming from different disciplines...
This paper analyzes the potential of Semantic Web technologies to support innovation in industrial scenarios. The study focuses in particular on RDF stores, the software components dedicated to the storage, representation and retrieval of semantic information. Starting from a literature review, a qualitative analysis is carried out considering a set of these systems. RDF stores are evaluated to find...
The main objective of presented paper is to compare and analyze the performance of semantic and NoSQL storage on the selected datasets. Paper focuses on a theoretical analysis of the problem and details the performance testing of selected semantic repositories and NoSQL databases. The practical part is focused on the testing of selected systems and our main aim was to simulate multiple querying with...
Exchanging user information between multiple sources can potentially bring many benefits that enhance the user experience in software applications. Richer and more dynamic user models can be constructed allowing more tailoring of content and services to the specific needs of individual users. However, providing effective interoperability is a complex challenge as there can be significant heterogeneity...
Nowadays, ontology as a knowledge sharing approach plays an important role in semantic interoperability of enterprise applications (EAs). However, the manual process of ontology construction requires deep understanding of the domain. This approach is difficult, expensive and time-consuming. To overcome the knowledge acquisition bottleneck, ontology learning field aims to provide automatic and semi-automatic...
The current trend for building an ontology-based data management system (DMS) is to capitalize on efforts made to design a preexisting well-established DMS (a reference system). The method amounts to extracting from the reference DMS a piece of schema relevant to the new application needs—a module—, possibly personalizing it with extra constraints w.r.t. the application under...
One of the reasons for the slow adoption of SPARQL is the complexity in query formulation due to data diversity. The principal barrier a user faces when trying to formulate a query is that he generally has no information about the underlying structure and vocabulary of the data. In this paper, we address this problem at the maximum scale we can think of: providing assistance in formulating SPARQL...
We provide an overview of the current data management research issues in the context of the Semantic Web. The objective is to introduce the audience into the area of the Semantic Web, and to highlight the fact that the area provides many interesting research opportunities for the data management community. A new model, the Resource Description Framework (RDF), coupled with a new query language, called...
This paper describes the meta-data warehouse of Credit Suisse that is productive since 2009. Like most other large organizations, Credit Suisse has a complex application landscape and several data warehouses in order to meet the information needs of its users. The problem addressed by the meta-data warehouse is to increase the agility and flexibility of the organization with regards to changes such...
Sensor networks are often deployed with the purpose of providing data to large-scale information management and GIS systems, or to collect measurements for specific scientific experiments. The benefits of such use are clear and widely accepted. The reuse of observations in low-cost, lightweight, web applications and mashups is a further compelling use case for sensor networks, but requires provision...
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