Special issue —— GEOAI Benchmark Examples
This virtual collection contains papers published under the “GEOAI benchmark examples” article type. Benchmark testing or benchmarking is necessary to foster unbiased and competitive evaluation of emerging ML/AI methods. For data-centric geotechnics or other geo-disciplines, benchmark examples should be constructed based on the following guidelines: (1) configurations must be 3D, realistic in scale, stratigraphy, and properties; (2) range of ground conditions should be sufficiently representative; (3) training datasets should be realistic, i.e. should be restricted to only data that an engineer has at his/her disposal in practice; and (4) validation datasets and performance metrics should be selected to demonstrate the value of ML/AI to decision making in practice. The recommended format for this article type is:
(1) Title of paper should be “GEOAI Benchmark Example” followed by the name of the example “BM/challenge/GEO AI Volume /year of publication”.
Cai, Y. and Phoon, K. K. 2024. GEOAI benchmark example BM/FootingDesign/1/2024. Geodata and AI, 1, 100002.
(2) Abstract
(3) Challenge statement
(4) Description of the problem that has value to decision making in practice
(5) Description of the site conditions
(6) Soil/rock data, including specification of training and validation datasets
(7) Sample solution
(8) Performance metrics
(9) Data availability – training and validation datasets must be provided
(10) References
Articles in this special issue:
Y. Otake, J.Y. Ching, T. Saito, K. Asano. (2025) GEOAI benchmark problems BM/AirportSoilProperties/2/2025. Geodata and AI, 2,100012.
Click here for the original paper
Y. Cai, K.K. Phoon. (2024) GEOAI benchmark examples BM/FootingDesign/1/2024. Geodata and AI, 2,100002.
Click here for the original paper
Special issue —— Open Access Geo-databases
This virtual collection contains descriptions of open access geo-databases published under the “Open access geo-databases” article type. This article type is restricted to 2000 words and 4 figures. The purpose of a communication article is to bring a single definite milestone to the attention of the GEOAI community. Examples of milestones are theories, algorithms, databases, and case histories that advance research (short communication) or practice (industry communication). This virtual collection focuses on open access geo-databases only. The recommended format for this short communication (geo-database) is:
(1) Title of paper should be “Introduction” followed by the name of the database(s)
Example paper is given in: Ching, J. and Phoon, K. K. 2024. Introduction to CLAY-Cc/6/6203 Database, Geodata and AI, 1, 100005.
(2) Abstract
(3) Introduction
(4) Description of the database(s)
(5) Exploratory data analysis
(6) Value of the database(s)
(7) Data availability – database should be made available in Mendeley
(8) References
Articles in this special issue:
K.K. Phoon, J.Y. Ching. (2024) Introduction to CLAY-Cc/6/6203 database. Geodata and AI, 1,100005.
Click here for the original paper
Articles
Volume 2
Editorial
K.K. Phoon. (2025) Privacy enhancing technologies (PETs) for geo-disciplines: GEOAI Editorial Volume 2. Geodata and AI, 2,100013.
Click here for the original paper
Research article
T. Saito, Y. Otake, S. Wu, K. Yano. (2025) Exploring high-order multivariate geotechnical features using the minimum information dependence model. Geodata and AI, 2,100009.
Click here for the original paper
Research article
H. Li, C. Shi. (2025) Few-shot learning of geological cross-sections from sparse data using large language model. Geodata and AI, 2,100010.
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Review article
Y. Otake, J.Y. Ching, T. Saito, K. Asano. (2025) GEOAI benchmark problems BM/AirportSoilProperties/2/2025. Geodata and AI, 2,100012.
Click here for the original paper
Book review
Y. Wang. (2025) Review of “Bayesian machine learning in geotechnical site characterization (authored by Jianye Ching)”. Geodata and AI, 2,100011.
Click here for the original paper
Volume 1
Editorial
K.K. Phoon, J.Y. Ching, X.M. Fan, L.M. Zhang, Z.J. Cao and C. Tang. (2024) Connecting geodata to machine learning and AI. Geodata and AI, 1,100001.
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Review article
K.K. Phoon. (2024) Trustworthy data-centric geotechnics. Geodata and AI, 1,100008.
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Review article
T. Murakami, S. Wu, J.Z. Zhang, D.M. Zhang, K. Asano, Y. Otake, K.K. Phoon. (2024) Differential Privacy in Geotechnical Engineering. Geodata and AI, 1,100004.
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Research article
S. Mostafa, R.L. Sousa. (2024) Deep learning uncertainty quantification for enhancing TBM operational predictions. Geodata and AI, 1,100003.
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Research article
K.L Ding, J.Y. Luo, H.H. Huang, et al. (2024) I-BALLAST: Computer vision solutions for ballast degradation analysis using deep-learning and data fusion methods. Geodata and AI, 1,100007.
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Case report
Y.M. Cai, K.K. Phoon. (2024) GEOAI benchmark example BM/FootingDesign/1/2025. Geodata and AI, 1,100002.
Click here for the original paper
Short communication
J.Y. Ching, K.K. Phoon. (2024) Introduction to CLAY-Cc/6/6203 database. Geodata and AI, 1,100005.
Click here for the original paper
Book review
Y. Wang. (2024) Book review databases for data-centric geotechnics: Site characterization edited by Kok-Kwang Phoon and Chong Tang. Geodata and AI, 1,100006.
Click here for the original paper