| dc.contributor.author | Košeleva, Natalija | |
| dc.contributor.author | Ropaitė, Guoda | |
| dc.date.accessioned | 2023-09-18T16:46:44Z | |
| dc.date.available | 2023-09-18T16:46:44Z | |
| dc.date.issued | 2017 | |
| dc.identifier.issn | 1877-7058 | |
| dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/116541 | |
| dc.description.abstract | Data generation has increased drastically over the past few years. Data management has also grown in importance because extracting the significant value out of a huge pile of raw data is of prime important thing to make different decisions. One of the important sectors nowadays is construction sector, especially building energy efficiency field. Collecting big amount of data, using different kinds of big data analysis can help to improve construction process from the energy efficiency perspective. This article reviews the understanding of Big Data, methods used for Big Data analysis and the main problems with Big Data in the field of energy. | eng |
| dc.format | PDF | |
| dc.format.extent | p. 544-549 | |
| dc.format.medium | tekstas / txt | |
| dc.language.iso | eng | |
| dc.relation.isreferencedby | Conference Proceedings Citation Index - Science (Web of Science) | |
| dc.relation.isreferencedby | Scopus | |
| dc.relation.isreferencedby | ScienceDirect | |
| dc.rights | Laisvai prieinamas internete | |
| dc.source.uri | https://doi.org/10.1016/j.proeng.2017.02.064 | |
| dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:23033986/datastreams/MAIN/content | |
| dc.subject | SD04 - Tvarus statinių gyvavimo ciklas / Sustainable lifecycle of the buildings | |
| dc.title | Big data in building energy efficiency: understanding of big data and main challenges | |
| dc.type | Straipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB | |
| dcterms.accessRights | This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) | |
| dcterms.references | 12 | |
| dc.type.pubtype | P1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB | |
| dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
| dc.contributor.faculty | Statybos fakultetas / Faculty of Civil Engineering | |
| dc.subject.researchfield | T 002 - Statybos inžinerija / Construction and engineering | |
| dc.subject.ltspecializations | L102 - Energetika ir tvari aplinka / Energy and a sustainable environment | |
| dc.subject.en | Energy Efficiency | |
| dc.subject.en | Big Data | |
| dc.subject.en | Characteristics of Big Data | |
| dc.subject.en | Big Data analysis | |
| dc.subject.en | Construction | |
| dc.subject.en | Web of Science | |
| dcterms.sourcetitle | Procedia Engineering. Modern Building Materials, Structures and Techniques, MBMST 2016 | |
| dc.description.volume | Vol. 172 | |
| dc.publisher.name | Elsevier | |
| dc.publisher.city | Amsterdam | |
| dc.identifier.doi | 000410919400070 | |
| dc.identifier.doi | 2-s2.0-85016299095 | |
| dc.identifier.doi | 10.1016/j.proeng.2017.02.064 | |
| dc.identifier.elaba | 23033986 | |