Mostrar el registro sencillo del ítem
dc.contributor.author | Blazquez, Desamparados | es_ES |
dc.contributor.author | Domenech, Josep | es_ES |
dc.date.accessioned | 2018-07-16T06:50:37Z | |
dc.date.available | 2018-07-16T06:50:37Z | |
dc.date.issued | 2018 | es_ES |
dc.identifier.issn | 0040-1625 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/105831 | |
dc.description.abstract | [EN] The Data Big Bang that the development of the ICTs has raised is providing us with a stream of fresh and digitized data related to how people, companies and other organizations interact. To turn these data into knowledge about the underlying behavior of the social and economic agents, organizations and researchers must deal with such amount of unstructured and heterogeneous data. Succeeding in this task requires to carefully plan and organize the whole process of data analysis taking into account the particularities of the social and economic analyses, which include the wide variety of heterogeneous sources of information and a strict governance policy. Grounded on the data lifecycle approach, this paper develops a Big Data architecture that properly integrates most of the non-traditional information sources and data analysis methods in order to provide a specifically designed system for forecasting social and economic behaviors, trends and changes. | es_ES |
dc.description.sponsorship | This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under Grant TIN2013-43913-R; and by the Spanish Ministry of Education under Grant FPU14/02386. | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Technological Forecasting and Social Change | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Big Data architecture | es_ES |
dc.subject | Forecasting | es_ES |
dc.subject | Nowcasting | es_ES |
dc.subject | Data lifecycle | es_ES |
dc.subject | Socio-economic data | es_ES |
dc.subject | Non-traditional data sources | es_ES |
dc.subject | Non-traditional analysis methods | es_ES |
dc.subject.classification | ECONOMIA APLICADA | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.title | Big Data sources and methods for social and economic analyses | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.techfore.2017.07.027 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TIN2013-43913-R/ES/EFICIENCIA ECONOMICA EN LA PLANIFICACION Y USO DE INFRAESTRUCTURAS CLOUD/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MECD//FPU2014-02386/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials | es_ES |
dc.description.bibliographicCitation | Blazquez, D.; Domenech, J. (2018). Big Data sources and methods for social and economic analyses. Technological Forecasting and Social Change. 130:99-113. https://doi.org/10.1016/j.techfore.2017.07.027 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.techfore.2017.07.027 | es_ES |
dc.description.upvformatpinicio | 99 | es_ES |
dc.description.upvformatpfin | 113 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 130 | es_ES |
dc.relation.pasarela | S\342360 | es_ES |
dc.contributor.funder | Ministerio de Educación, Cultura y Deporte | es_ES |
dc.contributor.funder | Ministerio de Economía, Industria y Competitividad | es_ES |