Big Data in civil engineering: a state-of-the-art survey

Kaplinski, Oleg; Košeleva, Natalija; Ropaitė, Guoda

doi:10.3846/2029882X.2016.1257373

Use this URL to cite this publication: https://hdl.handle.net/20.500.14911/117121

Big Data in civil engineering: a state-of-the-art survey

Details

Publication Type (CRIS)

Straipsnis kitoje duomenų bazėje / Article in other database (S4)

Publication Type (eLABa)

Straipsnis kitoje DB / Article in other DB (S3)

VILNIUS TECH Research Priorities and Topics

Tvarus statinių gyvavimo ciklas / Sustainable lifecycle of the buildings (SD04)

Lithuanian Intelligent Specialization

Energetika ir tvari aplinka / Energy and a sustainable environment (L102)

Author(s)

Author	Affiliation
Kaplinski, Oleg	Poznan university of technology
Košeleva, Natalija	Statybos valdymo ir nekilnojamojo turto katedra / Department of Construction Management and Real Estate (0261)
Ropaitė, Guoda	Statybos valdymo ir nekilnojamojo turto katedra / Department of Construction Management and Real Estate (0261)

Title

Big Data in civil engineering: a state-of-the-art survey

[en]

Oleg Kapliński, Natalija Košeleva, Guoda Ropaitė

Is part of

Engineering structures and technologies

Published In

Year	Volume	Issue	Start Page	End Page
2016	8	4	165	175

Publisher

Vilnius; London : Technika; Taylor & Francis

Referenced in Database(s)(DBs)

Gale's Academic OneFile

Index Copernicus

ICONDA

Extent

p. 165-175

URI

URI	Access Rights
https://hdl.handle.net/20.500.14911/117121
Straipsnis	Viso teksto dokumentas (atviroji prieiga) / Full Text Document (Open Access)

DOI

10.3846/2029882X.2016.1257373

Cited references

140

Science / Art Area

Socialiniai mokslai / Social sciences (S)

Field of Science / Art

Vadyba / Management (S003)

Statybos inžinerija / Civil engineering (T002)

Informatikos inžinerija / Informatics engineering (T007)

Keywords (en)

Abstract (en)

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 importance while making different decisions. This article reviews the concept of Big Data. The Thomson Reuters Web of Science Core Collection academic database was used to overview publications that contained “BIG DATA” keywords and were included in Web of Science Category under “Engineering”. The analysis of publications was made according to year, country, journal, authors, language and funding agency.