Databases for Data-Centric Geotechnics
Databases for Data-Centric Geotechnicsforms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This first volume pertains to site characterization. The opening chapter presents an in-depth...
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Taylor & Francis
2025
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| description | Databases for Data-Centric Geotechnicsforms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This first volume pertains to site characterization. The opening chapter presents an in-depth analysis of site data attributes, including the establishment of a new taxonomy of site data under “4S” (site generalizations, spatial features, sampling characteristics, and smart data) to provide a novel agenda for data-driven site characterization. Type 3 machine learning methods (disruptive value) are possible as sensors become more pervasive and more intelligent. A comprehensive overview of site characterization information is also presented with a focus on its availability, coverage, value to decision making, and challenges. The remaining 13 chapters cover databases of soil and rock properties and the application of these databases to rock socket behavior, rock classification, settlement on soft marine clays, permeability of fine-grained soils, and liquefaction among others. The databases were compiled from studies undertaken in many countries including Austria, Australia, Brazil, Canada, China, France, Finland, Germany, India, Iran, Japan, Korea, Malaysia, Mexico, New Zealand, Norway, Singapore, Sweden, Thailand, the United Kingdom, and the United States.
This volume on site characterization is a companion to the volume on geotechnical structures. Databases for Data-Centric Geotechnics represents the most diverse and comprehensive assembly of database research in a single publication (consisting of two volumes) to date. It follows from Model Uncertainties for Foundation Design, also published by CRC Press, and suits specialist geotechnical engineers, researchers and graduate students. |
| format | Online |
| id | doab-20.500.12854ir-163179 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Taylor & Francis |
| publisherStr | Taylor & Francis |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1631792025-07-31T05:49:23Z Databases for Data-Centric Geotechnics Phoon, Kok-Kwang Tang, Chong geotechnical risk,ground investigation,georisk,artificial neural networks,numerical modelling in geotechnics,numerical modelling of soils,ISSMGE TC 304 CPT,machine learning,VSPDB,Shear-Wave Velocity,Next Generation Liquefaction,Soil Profile Database,Deep Foundation Load Test Database,DFLTD,micropile and helical pile load,Databases to Interrogate Geotechnical Observations thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation thema EDItEUR::U Computing and Information Technology::UD Digital Lifestyle and online world: consumer and user guides::UDH E-book readers, tablets and other portable devices: consumer / user guides thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building::TNC Structural engineering::TNCC Soil and rock mechanics Databases for Data-Centric Geotechnicsforms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This first volume pertains to site characterization. The opening chapter presents an in-depth analysis of site data attributes, including the establishment of a new taxonomy of site data under “4S” (site generalizations, spatial features, sampling characteristics, and smart data) to provide a novel agenda for data-driven site characterization. Type 3 machine learning methods (disruptive value) are possible as sensors become more pervasive and more intelligent. A comprehensive overview of site characterization information is also presented with a focus on its availability, coverage, value to decision making, and challenges. The remaining 13 chapters cover databases of soil and rock properties and the application of these databases to rock socket behavior, rock classification, settlement on soft marine clays, permeability of fine-grained soils, and liquefaction among others. The databases were compiled from studies undertaken in many countries including Austria, Australia, Brazil, Canada, China, France, Finland, Germany, India, Iran, Japan, Korea, Malaysia, Mexico, New Zealand, Norway, Singapore, Sweden, Thailand, the United Kingdom, and the United States. This volume on site characterization is a companion to the volume on geotechnical structures. Databases for Data-Centric Geotechnics represents the most diverse and comprehensive assembly of database research in a single publication (consisting of two volumes) to date. It follows from Model Uncertainties for Foundation Design, also published by CRC Press, and suits specialist geotechnical engineers, researchers and graduate students. 2025-07-29T17:44:04Z 2025-07-29T17:44:04Z 2025-07-21T09:08:31Z 2025 book https://library.oapen.org/handle/20.500.12657/104307 9781003441946 9781032578958 9781032579887 https://directory.doabooks.org/handle/20.500.12854/163179 eng Challenges in Geotechnical and Rock Engineering open access Taylor & Francis CRC Press 10.1201/9781003441946 10.1201/9781003441946 fa69b019-f4ee-4979-8d42-c6b6c476b5f0 9781003441946 9781032578958 9781032579887 CRC Press open access |
| spellingShingle | geotechnical risk,ground investigation,georisk,artificial neural networks,numerical modelling in geotechnics,numerical modelling of soils,ISSMGE TC 304 CPT,machine learning,VSPDB,Shear-Wave Velocity,Next Generation Liquefaction,Soil Profile Database,Deep Foundation Load Test Database,DFLTD,micropile and helical pile load,Databases to Interrogate Geotechnical Observations thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation thema EDItEUR::U Computing and Information Technology::UD Digital Lifestyle and online world: consumer and user guides::UDH E-book readers, tablets and other portable devices: consumer / user guides thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building::TNC Structural engineering::TNCC Soil and rock mechanics Databases for Data-Centric Geotechnics |
| title | Databases for Data-Centric Geotechnics |
| title_full | Databases for Data-Centric Geotechnics |
| title_fullStr | Databases for Data-Centric Geotechnics |
| title_full_unstemmed | Databases for Data-Centric Geotechnics |
| title_short | Databases for Data-Centric Geotechnics |
| title_sort | databases for data centric geotechnics |
| topic | geotechnical risk,ground investigation,georisk,artificial neural networks,numerical modelling in geotechnics,numerical modelling of soils,ISSMGE TC 304 CPT,machine learning,VSPDB,Shear-Wave Velocity,Next Generation Liquefaction,Soil Profile Database,Deep Foundation Load Test Database,DFLTD,micropile and helical pile load,Databases to Interrogate Geotechnical Observations thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation thema EDItEUR::U Computing and Information Technology::UD Digital Lifestyle and online world: consumer and user guides::UDH E-book readers, tablets and other portable devices: consumer / user guides thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building::TNC Structural engineering::TNCC Soil and rock mechanics |
| topic_facet | geotechnical risk,ground investigation,georisk,artificial neural networks,numerical modelling in geotechnics,numerical modelling of soils,ISSMGE TC 304 CPT,machine learning,VSPDB,Shear-Wave Velocity,Next Generation Liquefaction,Soil Profile Database,Deep Foundation Load Test Database,DFLTD,micropile and helical pile load,Databases to Interrogate Geotechnical Observations thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation thema EDItEUR::U Computing and Information Technology::UD Digital Lifestyle and online world: consumer and user guides::UDH E-book readers, tablets and other portable devices: consumer / user guides thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building::TNC Structural engineering::TNCC Soil and rock mechanics |
| url | https://library.oapen.org/handle/20.500.12657/104307 |