Scalability and Performance Evaluation of Semantic Web Databases

Butt, Anila Sahar; Khan, Sharifullah

doi:10.1007/s13369-013-0753-4

Cited by 9 publications

(13 citation statements)

References 8 publications

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“…Fuseki SPARQL Server performs very well in most of the triplestore related operations (Butt and Khan, 2014 ), although it suffers from write performance problems (Kilintzis and Beredimas, 2014 ). The reasoning step can be tuned and adapted to use different OWL profiles to reduce execution time.…”

Section: Methodsmentioning

confidence: 99%

Extending XNAT Platform with an Incremental Semantic Framework

Timón

Rincón

Martínez‐Tomás

2017

Front. Neuroinform.

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Informatics increases the yield from neuroscience due to improved data. Data sharing and accessibility enable joint efforts between different research groups, as well as replication studies, pivotal for progress in the field. Research data archiving solutions are evolving rapidly to address these necessities, however, distributed data integration is still difficult because of the need of explicit agreements for disparate data models. To address these problems, ontologies are widely used in biomedical research to obtain common vocabularies and logical descriptions, but its application may suffer from scalability issues, domain bias, and loss of low-level data access. With the aim of improving the application of semantic models in biobanking systems, an incremental semantic framework that takes advantage of the latest advances in biomedical ontologies and the XNAT platform is designed and implemented. We follow a layered architecture that allows the alignment of multi-domain biomedical ontologies to manage data at different levels of abstraction. To illustrate this approach, the development is integrated in the JPND (EU Joint Program for Neurodegenerative Disease) APGeM project, focused on finding early biomarkers for Alzheimer's and other dementia related diseases.

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Section: Methodsmentioning

confidence: 99%

Extending XNAT Platform with an Incremental Semantic Framework

Timón

Rincón

Martínez‐Tomás

2017

Front. Neuroinform.

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“…SPARQL (Karim et al. ; Butt and Khan ) is a graph‐matching query language. Each SPARQL query consists of a set of triple patterns that is inherently a graph pattern.…”

Section: Concepts and Definitionmentioning

confidence: 99%

“…The data, stored in RDF format, can be retrieved and manipulated by the Semantic Web query lan-guage (SPARQL). SPARQL (Karim et al 2015;Butt and Khan 2014) is a graph-matching query language. Each SPARQL query consists of a set of triple patterns that is inherently a graph pattern.…”

Section: Semantic Web Query Languagementioning

confidence: 99%

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Social Semantic Web Framework for Industrial Synergies Initiation

Ghali

Frayret

2018

J of Industrial Ecology

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Summary Industrial synergies join two or more organizations that initially functioned as independent economic actors—that may originate from different sectors—together in order to share resources and exchange by‐products for mutual environmental, financial, and social benefits for its participants. Industrial symbioses (ISs) are networks of industrial synergies that can be initiated and created over time in various manners. In practice, the initiation of an industrial synergy, and particularly the identification of by‐product compatibilities, relies on direct or facilitated knowledge and information sharing, which is essential for discovering industrial synergy opportunities. Beyond its potential contribution to facilitate knowledge and information sharing among organizations, the Social Semantic Web (SSW) also has the potential to facilitate the initiation of industrial synergy by systematically and automatically identifying and recommending by‐products exchange compatibilities to potential partners. This framework exploits the ability of the sematic web to enable the search for analogies between potential partners within a region or district and existing industrial synergies around the world. This paper proposes the Social Semantic Web for Industrial Synergies Initiation (SSWISI) framework for the initiation of industrial synergies, which is based on the Social Semantic Web. The framework proposed in this paper adopts the concept of Linked Open Data (LOD), which enables the sharing and exchanging of information with external systems. This feature distinguishes the proposed framework from the existing approaches in its initiation of industrial synergies.

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“…SWR techniques generally consider one of three storage structures: (1) Native Storage: SWR approaches [22,20] deploy persistent storage with their own designed storage architecture and are generally considered to be more efficient than the ones relying on relational databases [9]. (2) NoSQL Databases: Some of the SWR techniques use NoSQL databases to increase processing power and storage.…”

Section: Storagementioning

confidence: 99%

A Taxonomy of Semantic Web Data Retrieval Techniques

Butt

Haller

Xie

2015

Proceedings of the 8th International Conference on Knowledge Capture

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The Semantic Web provides access to an increasing amount of structured information in a wide variety of domains. Information overload due to the large amount of structured data is as much a problem as on the traditional Web. To solve this problem, ample research has been proposed on Semantic Web data retrieval techniques and after more than a decade of research in this domain it is now reasonable to consider the questions: is the field of Semantic Web data retrieval making progress? What are the directions that have been taken? and what are some of the promising significant directions to pursue future research? To answer these questions, we review the state-of-the-art Semantic Web data retrieval techniques and define a taxonomy of these techniques to classify the ongoing research and find potential future research directions.

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Scalability and Performance Evaluation of Semantic Web Databases

Cited by 9 publications

References 8 publications

Extending XNAT Platform with an Incremental Semantic Framework

Extending XNAT Platform with an Incremental Semantic Framework

Social Semantic Web Framework for Industrial Synergies Initiation

A Taxonomy of Semantic Web Data Retrieval Techniques

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