In the last years, there was a growing interest in the use of Big Data models to support advanced data analysis functionalities. Many companies and organizations lack IT expertise and adequate budget to have benefits from them. In order to fill this gap, a model-based approach for Big Data Analytics-as-a-service (MBDAaaS) can be used. The proposed model, composed by declarative, procedural and deployment (sub) models, can be used to select a deployable set of services based on a set of user preferences shaping a Big Data Campaign (BDC). The deployment of a BDC requires that the selection of services has to be carried out on the basis of coherent and non conflictual user preferences. In this paper we propose an OWL ontology in order to solve this issue.

In the last years, there was a growing interest in the use of Big Data models to support advanced data analysis functionalities. Many companies and organizations lack IT expertise and adequate budget to have benefits from them. In order to fill this gap, a model-based approach for Big Data Analytics-as-a-service (MBDAaaS) can be used. The proposed model, composed by declarative, procedural and deployment (sub) models, can be used to select a deployable set of services based on a set of user preferences shaping a Big Data Campaign (BDC). The deployment of a BDC requires that the selection of services has to be carried out on the basis of coherent and non conflictual user preferences. In this paper we propose an OWL ontology in order to solve this issue.

An OWL Ontology for Supporting Semantic Services in Big Data Platforms

Redavid D.
;
Corizzo R.;Malerba D.
2018-01-01

Abstract

In the last years, there was a growing interest in the use of Big Data models to support advanced data analysis functionalities. Many companies and organizations lack IT expertise and adequate budget to have benefits from them. In order to fill this gap, a model-based approach for Big Data Analytics-as-a-service (MBDAaaS) can be used. The proposed model, composed by declarative, procedural and deployment (sub) models, can be used to select a deployable set of services based on a set of user preferences shaping a Big Data Campaign (BDC). The deployment of a BDC requires that the selection of services has to be carried out on the basis of coherent and non conflictual user preferences. In this paper we propose an OWL ontology in order to solve this issue.
2018
978-1-5386-7232-7
In the last years, there was a growing interest in the use of Big Data models to support advanced data analysis functionalities. Many companies and organizations lack IT expertise and adequate budget to have benefits from them. In order to fill this gap, a model-based approach for Big Data Analytics-as-a-service (MBDAaaS) can be used. The proposed model, composed by declarative, procedural and deployment (sub) models, can be used to select a deployable set of services based on a set of user preferences shaping a Big Data Campaign (BDC). The deployment of a BDC requires that the selection of services has to be carried out on the basis of coherent and non conflictual user preferences. In this paper we propose an OWL ontology in order to solve this issue.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/406314
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