A Model-Driven Framework for the Modeling and the Description of Data-as-a-Service to Assist Service Selection and Composition
Alili, Hiba; Drira, Rim; Belhajjame, Khalid; Ben Ghezala, Henda Hajjami; Grigori, Daniela (2019), A Model-Driven Framework for the Modeling and the Description of Data-as-a-Service to Assist Service Selection and Composition, in Hartmann, Sven; Küng, Josef; Chakravarthy, Sharma, Database and Expert Systems Applications, Proceedings, Part I, Springer : Cham, p. 396-406. 10.1007/978-3-030-27615-7_30
Type
Communication / ConférenceDate
2019Conference title
30th International Conference on Database and Expert Systems Applications (DEXA 2019)Conference date
2019-08Conference city
LinzConference country
AustriaBook title
Database and Expert Systems Applications, Proceedings, Part IBook author
Hartmann, Sven; Küng, Josef; Chakravarthy, SharmaPublisher
Springer
Published in
Cham
ISBN
978-3-030-27614-0
Number of pages
447Pages
396-406
Publication identifier
Metadata
Show full item recordAuthor(s)
Alili, HibaLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Laboratoire de recherche en Génie Logiciel, Applications distribuées, Systèmes décisionnels et Imagerie intelligente [Manouba] [RIADI]
Drira, Rim
Laboratoire de recherche en Génie Logiciel, Applications distribuées, Systèmes décisionnels et Imagerie intelligente [Manouba] [RIADI]
Belhajjame, Khalid
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Ben Ghezala, Henda Hajjami

Grigori, Daniela
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
Data as a Service (DaaS) is seen as a promising cloud offering for wrangling the overload of information and making it available across cloud platforms anytime and anywhere. While there exist a large number of DaaS providers in the market, each one has a different way to describe its provided services as well as supplied datasets. The lack of a well-defined machine-readable model strongly hinders the automatic selection and composition of DaaSs. This paper presents MoDaaS, a model-driven framework for the modeling and the description of DaaS services. MoDaaS enables DaaS providers to describe their services capabilities and concerns according to a shared ontology, thereafter it enables them to automatically generate service views in order to assist the integration and data exchange between heterogeneous services.Subjects / Keywords
Cloud computing; Data-as-a-Service (DaaS); Web services; Semantic annotation; Domain ontologies; Model driven engineering; Reuse and specializationRelated items
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