Note: In response to author requests, we have extended the submission deadline for this special collection in DCE to 2 September, 2024.
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Scope
Advancements in sensing and imaging technologies and a paradigm shift toward digitalization have both increased the availability as well as demands to process massive amounts of data. This high demand also brings in new challenges, such as the need to protect proprietary and private data, and ensure the explainability, trustworthiness, and fairness of the engineering solutions derived from a data-driven approach.
This special collection aims to provide a forum on the recent advances of data science and artificial intelligence that could potentially support discovery of new physics, advance the knowledge of geoscience and geoengineering, and provide reliable engineering solution to address broad and unsolved problems in geoscience and geoengineering, such as:
- large-scale predictive modeling and simulation for natural hazards;
- complex data-driven simulations for climate change adaptation, mitigation and recovery;
- developing autonomous systems to advance the development of urban environment and underground space;
- particulate-scale modeling to understand the mechanical and thermal behaviors of complex multiphase heterogeneous granular materials.
In particular, we seek contributions that advance the state-of-the-art in data-centric approach for geoscience, geomechanics, and geotechnical engineering in both big-data and limited data regimes.
Areas of Interest
Data:
- Data acquisition techniques across length scales;
- Data curation for multi-fidelities;
- Data denoising and signal processing;
- Data mining, inferential statistics;
- Secure data storage, exchange and processing.
Algorithms and modeling:
- Novel optimization techniques for Euclidean and non-Euclidean data;
- Machine learning for geoengineering applications;
- Graph and manifold learning for geoscience;
- Physics-informed machine learning predictive models;
- Causal discovery and explainable physics;
- Digital twins for earth.
Key Dates
- DCE Final Submission Deadline: 2 September 2024
Authors are encouraged to submit when ready, even if this ahead of the deadline. Articles sent to review typically take 90 days from submission to decision. Articles will be published as soon as possible after acceptance and at a later date added to a special collection page and introduced with an editorial reflecting upon all the published contributions.
Why Submit to DCE?
✔ A venue dedicated to the potential of data science for all areas of engineering.
✔ Welcoming research and translational articles from authors, whether they are based in academia or industry.
✔ Well-cited (2022 Impact Factor: 3.6; 2022 Cite Score: 3.4) and indexed in Web of Science, Scopus and Directory of Open Access Journals.
✔ #OpenAccess with support for unfunded authors thanks to the Lloyd's Register Foundation - no hard requirement to pay an article processing charge (APC).
✔ Promotes open sharing of data and code through Open Science Badges.
How to Submit
Key considerations for submitting are below, with full details available in the DCE Instructions for Authors.
Article types
DCE encourages the submission of:
- Research articles using data science methods and models for improving the reliability, resilience, safety, efficiency and usability of engineered systems.
- Translational papers demonstrating the downstream benefits of data-intensive engineering - and the underlying data science principles, techniques and technologies - to wider society, economy, environment, health and way of life. For some more detailed instructions, see this guide to translational papers. (Typically 6,000 words or less).
- Data papers that describe in a structured way, with a narrative and accompanying metadata, important and re-usable data sets in open repositories with potential for re-use in engineering research and practice. These papers promote data transparency and data re-use.
- Survey papers providing a detailed, balanced and authoritative current account of the existing literature concerning data-intensive methods in a particular facet of engineering sciences.
- Tutorial reviews providing an introduction and overview of an important topic of relevance to the journal readership. The topic should be of relevance to both students and researchers who are new to the field as well as experts and provide a good introduction to the development of a subject, its current state and indications of future directions the field is expected to take
- Position papers providing an overview of an important issue for this emerging field. (Typically 6,000 words or less).
In order to advance the availability of open data in geotechnical engineering, we are particularly interested to receive submission of data papers as part of this special collection. These would describe an already available data set in an open repository and authors should use a Data Availability Statement in their article to link to the data deposit. Zenodo is a free-to-use and reliable open data repository based at CERN and supported by the European Union; this where to share your data page also has advice on open data repositories to use.
Templates
Authors have the option but are not required to use the following templates:
- DCE LaTeX template files
- Overleaf (a LaTeX-based collaborative authoring tool; read about benefits of this tool)
- DCE Word template
Note that authors should provide both an abstract that summarises the paper (250 words or less) and beneath it an impact statement (120 words describing the significance of the findings in language that can be understood by a wide audience). Competing interest, funding and data availability statements should be provided at the end of the main text above the references (see disclosure statements).
Articles should be submitted through the DCE ScholarOne Manuscripts system, but note that if you use the Overleaf tool you can submit directly into the system without having to reupload files.
Data Availability
As noted above, we particularly encourage the submission of data papers to help promote the availability of open data for geotechnical engineering.
All authors are encouraged to make code and data that support the findings available in a recognised open repository such as Zenodo. All articles should contain a Data Availability Statement that describes where interested parties can access the data and code (providing the DOI or other permanent link) or alternatively explain why data and code could not be made open. Open Data and Open Materials badges will be displayed on published articles that link to replication materials, as a recognition of open practices. See the DCE Research Transparency Policy for more details on what makes a trusted repository and some example Data Availability Statements.
Editors
- Brian Sheil (University of Cambridge)
- Dayu Apoji (University of California Berkeley)
- Jelena Ninic (University of Birmingham)
- Kenichi Soga (University of California Berkeley)
- Steve Waiching Sun (Columbia University)
- Pin Zhang (University of Cambridge)