45,077 research outputs found
Scalable RDF Data Compression using X10
The Semantic Web comprises enormous volumes of semi-structured data elements.
For interoperability, these elements are represented by long strings. Such
representations are not efficient for the purposes of Semantic Web applications
that perform computations over large volumes of information. A typical method
for alleviating the impact of this problem is through the use of compression
methods that produce more compact representations of the data. The use of
dictionary encoding for this purpose is particularly prevalent in Semantic Web
database systems. However, centralized implementations present performance
bottlenecks, giving rise to the need for scalable, efficient distributed
encoding schemes. In this paper, we describe an encoding implementation based
on the asynchronous partitioned global address space (APGAS) parallel
programming model. We evaluate performance on a cluster of up to 384 cores and
datasets of up to 11 billion triples (1.9 TB). Compared to the state-of-art
MapReduce algorithm, we demonstrate a speedup of 2.6-7.4x and excellent
scalability. These results illustrate the strong potential of the APGAS model
for efficient implementation of dictionary encoding and contributes to the
engineering of larger scale Semantic Web applications
Ontology-based knowledge representation and semantic search information retrieval: case study of the underutilized crops domain
The aim of using semantic technologies in domain knowledge modeling is to introduce the semantic meaning of concepts in knowledge bases, such that they are both human-readable as well as machine-understandable. Due to their powerful knowledge representation formalism and associated inference mechanisms, ontology-based approaches have been increasingly adopted to formally represent domain knowledge. The primary objective of this thesis work has been to use semantic technologies in advancing knowledge-sharing of Underutilized crops as a domain and investigate the integration of underlying ontologies developed in OWL (Web Ontology Language) with augmented SWRL (Semantic Web Rule Language) rules for added expressiveness.
The work further investigated generating ontologies from existing data sources and proposed the reverse-engineering approach of generating domain specific conceptualization through competency questions posed from possible ontology users and domain experts. For utilization, a semantic search engine (the Onto-CropBase) has been developed to serve as a Web-based access point for the Underutilized crops ontology model. Relevant linked-data in Resource Description Framework Schema (RDFS) were added for comprehensiveness in generating federated queries.
While the OWL/SWRL combination offers a highly expressive ontology language for modeling knowledge domains, the combination is found to be lacking supplementary descriptive constructs to model complex real-life scenarios, a necessary requirement for a successful Semantic Web application. To this end, the common logic programming formalisms for extending Description Logic (DL)-based ontologies were explored and the state of the art in SWRL expressiveness extensions determined with a view to extending the SWRL formalism. Subsequently, a novel fuzzy temporal extension to the Semantic Web Rule Language (FT-SWRL), which combines SWRL with fuzzy logic theories based on the valid-time temporal model, has been proposed to allow modeling imprecise temporal expressions in domain ontologies
Evolution of Software Engineering in the Changing Scenario of Modern Hardware Architecture, Semantic Web and Cloud Computing Platform
Traditional way of software engineering is no longer fully suitable in the changing scenario of modern hardwareand software architecture of parallel and distributed computing on Semantic web and Cloud computing platform. A parallelhardware architecture can support high performance computing but needs changes in programming style. Also the capabilityof Semantic web can link everything on the internet making an interoperable intelligent system. And with this capabilitymany beneficial business models like Web services and Cloud computing platform have been conceptualized. Cloudcomputing is the most anticipated future trend of computing. These changes in hardware and software architecture means weneed to re-visit the traditional software engineering process models meant for a single computer system. This paper firstsurveys the evolution of hardware architecture, newer business models, newer software applications and then analyses theneed for changes in software engineering process models to leverage all the benefits of the newer business models. Thispaper also emphasizes the vulnerability of the web applications and cloud computing platform in terms of risk managementof web applications in general and privacy and security of customer information in shared cloud platform which maythreaten the adoption of the cloud platform.Keywords/Index Terms— Agile Process Model , Cloud Computing Platform, Privacy and Security Issues, RiskManagement, Semantic Web, Software Evolution
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