dc.contributor.author | Gómez Brandón, Adrián | |
dc.contributor.author | Paramá Gabia, José Ramón | |
dc.contributor.author | Villalobos Rodríguez, Kevin | |
dc.contributor.author | Illarramendi Echave, María Aránzazu ![ORCID](/themes/Mirage2//images/orcid_16x16.png) | |
dc.contributor.author | Rodríguez Brisaboa, Nieves | |
dc.date.accessioned | 2021-12-09T09:18:28Z | |
dc.date.available | 2021-12-09T09:18:28Z | |
dc.date.issued | 2021-11 | |
dc.identifier.citation | Computers in Industry 132 : (2021) // Article ID 103503 | es_ES |
dc.identifier.issn | 0166-3615 | |
dc.identifier.issn | 1872-6194 | |
dc.identifier.uri | http://hdl.handle.net/10810/54392 | |
dc.description.abstract | [EN]The new opportunities generated by the data-driven economy in the manufacturing industry have caused many companies opt for it. However, the size of time series data that need to be captured creates the problem of having to assume high storage costs. Moreover, these costs, which are constantly growing, begin to have an impact on the profitability of companies. Thus, in this scenario, the need arises to develop techniques that allow obtaining reduced representations of the time series. In this paper, we present a lossless compression method for industrial time series that allows an efficient access. That is, our aim goes beyond pure compression, where the usual way to access the data requires a complete decompression of the dataset before processing it. Instead, our method allows decompressing portions of the dataset, and moreover, it allows direct querying the compressed data. Thus, the proposed method combines the efficient access, typical of lossy methods, with the lossless compression. | es_ES |
dc.description.sponsorship | For the A Coruna team: This work was supported by CITIC, as Research Center accredited by Galician University System, is funded by "Conselleria de Cultura, Educacion e Universidade from Xunta de Galicia", supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014-2020, and the remaining 20% by "Secretaria Xeral de Universidades" (Grant ED431G 2019/01) , Xunta de Galicia/FEDER-UE under Grants [IG240.2020.1.185; IN852A 2018/14] and Ministerio de Ciencia, Innovacion under Grants [TIN2016-78011-C4-1-R; RTC-2017-5908-7] . For the Basque team: Ministerio de Ciencia, Innovacion y Universidades under Grant [FEDER/TIN2016-78011-C4-2-R] and the Basque Government under Grant No. [IT1330-19] . Funding for open access charge: Universidade da Coruna/CISUG. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/TIN2016-78011-C4-1-R; | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/RTC-2017-5908-7 | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/TIN2016-78011-C4-2-R | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | compression | es_ES |
dc.subject | smart manufacturing | es_ES |
dc.subject | time series | es_ES |
dc.title | Lossless compression of industrial time series with direct access | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | (c) 2021 The Author(s). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | es_ES |
dc.rights.holder | Atribución-NoComercial-SinDerivadas 3.0 España | * |
dc.relation.publisherversion | https://www-sciencedirect-com.ehu.idm.oclc.org/science/article/pii/S016636152100110X?via%3Dihub | es_ES |
dc.identifier.doi | 10.1016/j.compind.2021.103503 | |
dc.departamentoes | Lenguajes y sistemas informáticos | es_ES |
dc.departamentoeu | Hizkuntza eta sistema informatikoak | es_ES |