Automatic Integration and Querying of Semantic Rich Heterogeneous Data

Saeed, Muhammad Rizwan; Chelmis, Charalampos; Prasanna, Viktor K.

doi:10.1016/b978-0-12-809764-9.00012-3

Cited by 6 publications

(1 citation statement)

References 17 publications

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“…In this paper, we try to implement the ETL procedure in context of Big data. The idea exploited here is the Semantic Web technologies [33] which is the most used technique exploited for meaningful description of data from a number of heterogeneous sources. For this, we extract data from the web and then try to transform them into a structured dataset, more specifically into csv format.…”

Section: Methodsmentioning

confidence: 99%

Extracting and Transforming Heterogeneous Data from XML files for Big Data

Das,

Saha,

Saha

2019

IJEAT

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Digital technology is fast changing in the recent years and with this change, the number of data systems, sources, and formats has also increased exponentially. So the process of extracting data from these multiple source systems and transforming it to suit for various analytics processes is gaining importance at an alarming rate. In order to handle Big Data, the process of transformation is quite challenging, as data generation is a continuous process. In this paper, we extract data from various heterogeneous sources from the web and try to transform it into a form which is vastly used in data warehousing so that it caters to the analytical needs of the machine learning community.

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Section: Methodsmentioning

confidence: 99%

Extracting and Transforming Heterogeneous Data from XML files for Big Data

Das,

Saha,

Saha

2019

IJEAT

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Application Ontology for Multi-Agent and Web-Services’ Co-Simulation in Power and Energy Systems

et al. 2020

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Power and energy systems are very complex, and several tools are available to assist operators in their planning and operation. However, these tools do not allow a sensitive analysis of the impact of the interaction between the different sub-domains and, consequently, in obtaining more realistic and reliable results. One of the key challenges in this area is the development of decision support tools to address the problem as a whole. Tools Control Center-TOOCC-proposed and developed by the authors, enables the co-simulation of heterogeneous systems to study the electricity markets, the operation of the smart grids, and the energy management of the final consumer, among others. To this end, it uses an application ontology that supports the definition of scenarios and results comparison, while easing the interoperability among the several systems. This paper presents the application ontology developed. The paper addresses the methodology used for its development, its purpose and requirements, and its concepts, relations, facets and instances. The ontology application is illustrated through a case study, where different requirements are tested and demonstrated. It is concluded that the proposed application ontology accomplishes its goals, as it is suitable to represent the required knowledge to support the interoperability among the different considered systems.

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Extracting Entity-Specific Substructures for RDF Graph Embedding

Saeed

Prasanna

2018

2018 IEEE International Conference on Information Reuse and Integration (IRI)

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Automatic Integration and Querying of Semantic Rich Heterogeneous Data

Cited by 6 publications

References 17 publications

Extracting and Transforming Heterogeneous Data from XML files for Big Data

Extracting and Transforming Heterogeneous Data from XML files for Big Data

Application Ontology for Multi-Agent and Web-Services’ Co-Simulation in Power and Energy Systems

Extracting Entity-Specific Substructures for RDF Graph Embedding

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