scholarly journals Using superimposed multidimensional schemas and OLAP patterns for RDF data analysis

2018 ◽  
Vol 8 (1) ◽  
pp. 18-37 ◽  
Author(s):  
Median Hilal ◽  
Christoph G. Schuetz ◽  
Michael Schrefl
Keyword(s):  
Data Analysis ◽  
Semantic Web ◽  
Query Language ◽  
Query Languages ◽  
Sparql Query ◽  
Semantic Web Technologies ◽  
Rdf Data ◽  
Self Service ◽  
Description Framework ◽  
Definition Of

Abstract The foundations for traditional data analysis are Online Analytical Processing (OLAP) systems that operate on multidimensional (MD) data. The Resource Description Framework (RDF) serves as the foundation for the publication of a growing amount of semantic web data still largely untapped by companies for data analysis. Most RDF data sources, however, do not correspond to the MD modeling paradigm and, as a consequence, elude traditional OLAP. The complexity of RDF data in terms of structure, semantics, and query languages renders RDF data analysis challenging for a typical analyst not familiar with the underlying data model or the SPARQL query language. Hence, conducting RDF data analysis is not a straightforward task. We propose an approach for the definition of superimposed MD schemas over arbitrary RDF datasets and show how to represent the superimposed MD schemas using well-known semantic web technologies. On top of that, we introduce OLAP patterns for RDF data analysis, which are recurring, domain-independent elements of data analysis. Analysts may compose queries by instantiating a pattern using only the MD concepts and business terms. Upon pattern instantiation, the corresponding SPARQL query over the source data can be automatically generated, sparing analysts from technical details and fostering self-service capabilities.

scholarly journals Creating RESTful APIs over SPARQL endpoints using RAMOSE

Semantic Web ◽  
2021 ◽  
pp. 1-19
Author(s):  
Marilena Daquino ◽  
Ivan Heibi ◽  
Silvio Peroni ◽  
David Shotton
Keyword(s):  
Semantic Web ◽  
Service Providers ◽  
Query Language ◽  
Sparql Query ◽  
Direct Access ◽  
Technical Solution ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Sparql Endpoint ◽  
Rdf Data

Semantic Web technologies are widely used for storing RDF data and making them available on the Web through SPARQL endpoints, queryable using the SPARQL query language. While the use of SPARQL endpoints is strongly supported by Semantic Web experts, it hinders broader use of RDF data by common Web users, engineers and developers unfamiliar with Semantic Web technologies, who normally rely on Web RESTful APIs for querying Web-available data and creating applications over them. To solve this problem, we have developed RAMOSE, a generic tool developed in Python to create REST APIs over SPARQL endpoints. Through the creation of source-specific textual configuration files, RAMOSE enables the querying of SPARQL endpoints via simple Web RESTful API calls that return either JSON or CSV-formatted data, thus hiding all the intrinsic complexities of SPARQL and RDF from common Web users. We provide evidence that the use of RAMOSE to provide REST API access to RDF data within OpenCitations triplestores is beneficial in terms of the number of queries made by external users of such RDF data using the RAMOSE API, compared with the direct access via the SPARQL endpoint. Our findings show the importance for suppliers of RDF data of having an alternative API access service, which enables its use by those with no (or little) experience in Semantic Web technologies and the SPARQL query language. RAMOSE can be used both to query any SPARQL endpoint and to query any other Web API, and thus it represents an easy generic technical solution for service providers who wish to create an API service to access Linked Data stored as RDF in a triplestore.

scholarly journals Petri nets on the semantic web guidelines and infrastructure

2004 ◽  
Vol 1 (2) ◽  
pp. 127-151 ◽  
Author(s):  
Dragan Gasevic
Keyword(s):  
Semantic Web ◽  
Petri Net ◽  
Ontology Language ◽  
Uml Profiles ◽  
Community Effort ◽  
Model Sharing ◽  
Petri Net Markup Language ◽  
Description Framework ◽  
Definition Of ◽  
Resource Description

This paper gives the Petri net ontology as the most important element in providing Petri net support for the Semantic Web. Available Petri net formal descriptions are: metamodels, UML profiles, ontologies and syntax. Metamodels are useful, but their main purpose is for Petri net tools. Although the current Petri-net community effort Petri Net Markup Language (PNML) is XML-based, it lacks a precise definition of semantics. Existing Petri net ontologies are partial solutions specialized for a specific problem. In order to show current Petri net model sharing features we use P3 tool that uses PNML/XSLT-based approach for model sharing. This paper suggests developing the Petri net ontology to represent semantics appropriately. This Petri net ontology is described using UML, Resource Description Framework (Schema) RDF(S) and the Web Ontology Language-OWL.

Data Confidentiality on the Semantic Web

2008 ◽  
pp. 3309-3320
Author(s):  
Csilla Farkas
Keyword(s):  
Semantic Web ◽  
Formal Semantics ◽  
Future Research ◽  
Semantic Web Technologies ◽  
Inference Problem ◽  
Web Technologies ◽  
Ontology Language ◽  
Future Research Directions ◽  
Description Framework ◽  
Resource Description

This chapter investigates the threat of unwanted Semantic Web inferences. We survey the current efforts to detect and remove unwanted inferences, identify research gaps, and recommend future research directions. We begin with a brief overview of Semantic Web technologies and reasoning methods, followed by a description of the inference problem in traditional databases. In the context of the Semantic Web, we study two types of inferences: (1) entailments defined by the formal semantics of the Resource Description Framework (RDF) and the RDF Schema (RDFS) and (2) inferences supported by semantic languages like the Web Ontology Language (OWL). We compare the Semantic Web inferences to the inferences studied in traditional databases. We show that the inference problem exists on the Semantic Web and that existing security methods do not fully prevent indirect data disclosure via inference channels.

The Utilization of Semantic Web for Integrating Enterprise Systems

2008 ◽  
pp. 97-114
Author(s):  
Dimitrios Tektonidis ◽  
Albert Bokma
Keyword(s):  
Semantic Web ◽  
Heterogeneous Systems ◽  
Enterprise Application Integration ◽  
Application Integration ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Enterprise Application ◽  
Shared Information ◽  
Service Oriented ◽  
Definition Of

Integrating enterprise system has become an issue of sharing information rather than transforming information due to the increasing complexity and the heterogeneity of the applications. The transition from application centric to integration centric enterprise application integration (EAI) requires methods and technologies that will enable and facilitate the definition of shared information. The use of ontologies Semantic Web and technologies can improve the existing EAI methods by providing a framework capable to define shared information. Ontologies based Enterprise application integration (ONAR) framework utilizes Semantic Web technologies to define shared information among heterogeneous systems. The present paper presents the utilization of ontologies for the formation of ONAR framework and its application for service oriented application integration (SOAI)

Query Optimization of Distributed RDF Data Based on MapReduce

2013 ◽  
Vol 441 ◽  
pp. 970-973
Author(s):  
Yan Qin Zhang ◽  
Jing Bin Wang
Keyword(s):  
Query Optimization ◽  
Query Language ◽  
Sparql Query ◽  
Query Execution ◽  
Data Set ◽  
Greedy Strategy ◽  
Lehigh University ◽  
Join Algorithm ◽  
Simple Protocol ◽  
Rdf Data

As the development of the semantic web, RDF data set has grown rapidly, thus causing the query problem of massive RDF. Using distributed technique to complete the SPARQL (Simple Protocol and RDF Query Language) Query is a new way of solving the large amounts of RDF query problem. At present, most of the RDF query strategies based on Hadoop have to use multiple MapReduce jobs to complete the task, resulting in waste of time. In order to overcome this drawback, MRQJ (using MapReduce to query and join) algorithm is proposed in the paper, which firstly uses a greedy strategy to generate join plan, then only one MapReduce job should be created to get the query results in SPARQL query execution. Finally, a contrast experiment on the LUBM (Lehigh University Benchmark) test data set is conducted, the results of which show that MRQJ method has a great advantage in the case that the query is more complicated.

scholarly journals OpenCitations, an infrastructure organization for open scholarship

2020 ◽  
Vol 1 (1) ◽  
pp. 428-444 ◽  
Author(s):  
Silvio Peroni ◽  
David Shotton
Keyword(s):  
Semantic Web ◽  
Large Scale ◽  
Open Data ◽  
Data Sets ◽  
Citation Data ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Creative Commons ◽  
Citation Indexes ◽  
Description Framework

OpenCitations is an infrastructure organization for open scholarship dedicated to the publication of open citation data as Linked Open Data using Semantic Web technologies, thereby providing a disruptive alternative to traditional proprietary citation indexes. Open citation data are valuable for bibliometric analysis, increasing the reproducibility of large-scale analyses by enabling publication of the source data. Following brief introductions to the development and benefits of open scholarship and to Semantic Web technologies, this paper describes OpenCitations and its data sets, tools, services, and activities. These include the OpenCitations Data Model; the SPAR (Semantic Publishing and Referencing) Ontologies; OpenCitations’ open software of generic applicability for searching, browsing, and providing REST APIs over resource description framework (RDF) triplestores; Open Citation Identifiers (OCIs) and the OpenCitations OCI Resolution Service; the OpenCitations Corpus (OCC), a database of open downloadable bibliographic and citation data made available in RDF under a Creative Commons public domain dedication; and the OpenCitations Indexes of open citation data, of which the first and largest is COCI, the OpenCitations Index of Crossref Open DOI-to-DOI Citations, which currently contains over 624 million bibliographic citations and is receiving considerable usage by the scholarly community.

UPDATE-ENABLED TRIPLIFICATION OF RELATIONAL DATA INTO VIRTUAL RDF STORES

2010 ◽  
Vol 04 (04) ◽  
pp. 423-451 ◽  
Author(s):  
SUNITHA RAMANUJAM ◽  
VAIBHAV KHADILKAR ◽  
LATIFUR KHAN ◽  
MURAT KANTARCIOGLU ◽  
BHAVANI THURAISINGHAM ◽  
...  
Keyword(s):  
Semantic Web ◽  
Relational Database ◽  
Relational Databases ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Relational Data ◽  
Semantic Web Technologies ◽  
Heterogeneous Data Sources ◽  
Description Framework ◽  
Almost All

The current buzzword in the Internet community is the Semantic Web initiative proposed by the W3C to yield a Web that is more flexible and self-adapting. However, for the Semantic Web initiative to become a reality, heterogeneous data sources need to be integrated in order to enable access to them in a homogeneous manner. Since a vast majority of data currently resides in relational databases, integrating relational data sources with semantic web technologies is at the top of the list of activities required to realize the semantic web vision. Several efforts exist that publish relational data as Resource Description Framework (RDF) triples; however almost all current work in this arena is uni-directional, presenting data from an underlying relational database into a corresponding virtual RDF store in a read-only manner. An enhancement over previous relational-to-RDF bridging work in the form of bi-directionality support is presented in this paper. The bi-directional bridge proposed here allows RDF data updates specified as triples to be propagated back into the underlying relational database as tuples. Towards this end, we present various algorithms to translate the triples to be updated/inserted/deleted into equivalent relational attributes/tuples whenever possible. Particular emphasis is laid, in this paper, on the translation and update propagation process for triples containing blank nodes and reification nodes, and a platform enhanced with our algorithms, called D2RQ++, through which bi-directional translation can be achieved, is presented.

scholarly journals A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 1822 ◽  
Author(s):  
Ana Claudia Sima ◽  
Christophe Dessimoz ◽  
Kurt Stockinger ◽  
Monique Zahn-Zabal ◽  
Tarcisio Mendes de Farias
Keyword(s):  
Query Language ◽  
Data Sources ◽  
Multiple Sources ◽  
Semantic Web Technologies ◽  
Genome Database ◽  
Web Technologies ◽  
Multiple Data ◽  
Hands On ◽  
Description Framework ◽  
Different Sources

The increasing use of Semantic Web technologies in the life sciences, in particular the use of the Resource Description Framework (RDF) and the RDF query language SPARQL, opens the path for novel integrative analyses, combining information from multiple sources. However, analyzing evolutionary data in RDF is not trivial, due to the steep learning curve required to understand both the data models adopted by different RDF data sources, as well as the SPARQL query language. In this article, we provide a hands-on introduction to querying evolutionary data across multiple sources that publish orthology information in RDF, namely: The Orthologous MAtrix (OMA), the European Bioinformatics Institute (EBI) RDF platform, the Database of Orthologous Groups (OrthoDB) and the Microbial Genome Database (MBGD). We present four protocols in increasing order of complexity. In these protocols, we demonstrate through SPARQL queries how to retrieve pairwise orthologs, homologous groups, and hierarchical orthologous groups. Finally, we show how orthology information in different sources can be compared, through the use of federated SPARQL queries.

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