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dc.contributor.authorBenítez-Hidalgo, Antonio
dc.contributor.authorBarba-González, Cristóbal 
dc.contributor.authorGutiérrez-Moncayo, Pedro
dc.contributor.authorPaneque, Manuel
dc.contributor.authorNebro-Urbaneja, Antonio Jesús 
dc.contributor.authorRoldán-García, María del Mar
dc.contributor.authorAldana-Montes, José Francisco 
dc.contributor.authorNavas-Delgado, Ismael 
dc.date.accessioned2022-04-20T06:42:17Z
dc.date.available2022-04-20T06:42:17Z
dc.date.issued2021-11-28
dc.identifier.citationBenítez-Hidalgo, Antonio ; Barba-González, Cristóbal ; Gutiérrez-Moncayo, Pedro ; Paneque, Manuel ; Nebro-Urbaneja, Antonio Jesus ; Roldan-Garcia, Maria del Mar ; Aldana-Montes, Jose Francisco ; Navas-Delgado, Ismael. TITAN: A knowledge-based platform for Big Data workflow management. Knowledge-Based Systems Volume 232, 28 November 2021, 107489. https://doi.org/10.1016/j.knosys.2021.107489es_ES
dc.identifier.urihttps://hdl.handle.net/10630/23947
dc.description.abstractModern applications of Big Data are transcending from being scalable solutions of data processing and analysis, to now provide advanced functionalities with the ability to exploit and understand the underpinning knowledge. This change is promoting the development of tools in the intersection of data processing, data analysis, knowledge extraction and management. In this paper, we propose TITAN, a software platform for managing all the life cycle of science workflows from deployment to execution in the context of Big Data applications. This platform is characterised by a design and operation mode driven by semantics at different levels: data sources, problem domain and workflow components. The proposed platform is developed upon an ontological framework of meta-data consistently managing processes and models and taking advantage of domain knowledge. TITAN comprises a well-grounded stack of Big Data technologies including Apache Kafka for inter-component communication, Apache Avro for data serialisation and Apache Spark for data analytics. A series of use cases are conducted for validation, which comprises workflow composition and semantic meta-data management in academic and real-world fields of human activity recognition and land use monitoring from satellite images.es_ES
dc.description.sponsorshipThis work has been partially funded by the Spanish Ministry of Science and Innovation via Grant PID2020 112540RB-C41 (AEI/FEDER, UE) and Andalusian PAIDI program with grant P18-RT-2799. Funding for open access charge: Universidad de Málaga / CBUA.
dc.language.isoenges_ES
dc.publisherELSEVIERes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectDatos masivoses_ES
dc.subject.otherBig Data analyticses_ES
dc.subject.otherSemanticses_ES
dc.subject.otherKnowledge extractiones_ES
dc.titleTITAN: A knowledge-based platform for Big Data workflow managementes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.identifier.doihttps://doi.org/10.1016/j.knosys.2021.107489
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*


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