Data-Centric Engineering
Scope & Guideline
Advancing Innovations at the Data-Engineering Nexus
Introduction
Aims and Scopes
- Data-Driven Optimization:
The journal frequently publishes research on optimization techniques using data-driven models, highlighting how data can inform and enhance engineering design and decision processes. - Digital Twin Technologies:
A significant focus is placed on digital twin methodologies, which integrate real-time data with physical systems to improve monitoring, predictive maintenance, and operational efficiency. - Machine Learning Applications in Engineering:
The integration of machine learning techniques within engineering frameworks is a core area, with research exploring applications from structural health monitoring to predictive modeling in various engineering domains. - Uncertainty Quantification and Risk Assessment:
Research often addresses the quantification of uncertainties in engineering models, applying statistical and probabilistic methods to improve reliability and safety in engineering applications. - Multiphysics and Multiscale Modeling:
The journal emphasizes studies that combine multiple physical phenomena and scales in modeling, utilizing data-centric methods to enhance the understanding of complex systems.
Trending and Emerging
- Artificial Intelligence and Machine Learning Integration:
There is a marked increase in papers exploring the integration of AI and machine learning techniques into engineering practices, emphasizing their potential to transform predictive modeling and automation. - Advanced Digital Health Engineering:
Emerging research on digital health engineering, particularly in the context of aging infrastructure and healthcare applications, highlights the growing relevance of data-centric approaches in public health and safety. - Graph Neural Networks and Their Applications:
The application of graph neural networks is gaining momentum, particularly for modeling complex relationships in engineering problems, showcasing the versatility of these advanced methods. - Sustainable Engineering Practices:
A rising trend towards sustainability is evident, with research focusing on environmentally conscious engineering practices and the role of data in optimizing resource usage and reducing emissions. - Real-Time Data Analytics in Engineering:
The development of methodologies for real-time data analytics is becoming increasingly important, with papers addressing how immediate data insights can enhance decision-making and operational efficiency in engineering contexts.
Declining or Waning
- Traditional Statistical Methods:
There appears to be a waning interest in traditional statistical approaches to engineering problems, as researchers increasingly favor data-driven and machine learning methods that offer greater flexibility and predictive power. - Physical Experimentation:
Research relying heavily on physical experimentation without the integration of data-centric methodologies is becoming less common, reflecting a shift towards simulations and computational modeling. - Basic Data Management Techniques:
The focus on foundational data management techniques, such as simple database management or basic data collection methods, is declining in favor of more advanced analytics and big data solutions. - Generic Engineering Models:
The use of generic engineering models that do not leverage specific data insights is less prevalent, as there is a growing trend towards customized, data-informed models that address specific engineering challenges.
Similar Journals
Journal of Advanced Simulation in Science and Engineering
Transforming Research into Real-World ApplicationsJournal of Advanced Simulation in Science and Engineering, published by the Japan Society for Simulation Technology (JSST), stands as a pivotal platform in the dynamic field of simulation technology, focusing on cutting-edge research and applications in science and engineering. With the ISSN and E-ISSN of 2188-5303, this journal aims to disseminate high-quality research that drives innovation and enhances understanding among practitioners, academics, and students alike. As an essential resource for those engaged in simulation methodologies, it explores a wide range of topics, including but not limited to computational modeling, virtual simulations, and their applications across various engineering disciplines. The journal is indexed in prestigious databases, aiming for a strong impact factor that reflects its commitment to scholarly excellence and relevance. Its open access policy further facilitates wider dissemination and accessibility of research findings, thereby fostering greater collaboration and advancement in the field. Researchers and professionals are encouraged to contribute their findings and insights, establishing the Journal of Advanced Simulation in Science and Engineering as a leading authority in advancing simulation technologies for future applications.
COMPUTERS & STRUCTURES
Driving Progress in Engineering and Materials ScienceCOMPUTERS & STRUCTURES is a leading interdisciplinary journal published by Pergamon-Elsevier Science Ltd, focusing on the application of computer methods in the fields of civil and structural engineering, mechanical engineering, materials science, and modeling and simulation. With a prestigious history dating back to its inception in 1971, this journal is committed to advancing the knowledge and methodologies that integrate computational techniques with structural analysis and design. Recognized in 2023 with a Q1 ranking across several categories, including Civil and Structural Engineering and Computer Science Applications, COMPUTERS & STRUCTURES emphasizes the importance of innovative research that pushes the boundaries of traditional engineering practices. Although the journal does not currently offer open access, it remains an invaluable resource for researchers, professionals, and students seeking to disseminate and discuss groundbreaking findings that are shaping the future of engineering and materials science. The rigorous peer-review process ensures the publication of high-quality articles that contribute to the global discourse in these critical fields.
ADVANCED ENGINEERING INFORMATICS
Exploring the Intersection of Technology and EngineeringADVANCED ENGINEERING INFORMATICS is a prestigious journal published by Elsevier Science Ltd, dedicated to the interdisciplinary fields of Artificial Intelligence and Information Systems. Established in 2002, this journal serves as a vital platform for researchers and practitioners to disseminate groundbreaking insights and innovations that shape the future of engineering and technological integration. With an impressive impact factor and ranked in the Q1 category for both Artificial Intelligence and Information Systems in 2023, it holds a prominent position, with Scopus rankings placing it in the 92nd percentile among 394 journals in Computer Science Information Systems and the 87th percentile among 350 journals in Computer Science Artificial Intelligence. ADVANCED ENGINEERING INFORMATICS embraces an Open Access model, ensuring that cutting-edge research is accessible to a global audience, fostering collaboration and development across academic and professional circles. The journal is committed to advancing knowledge and influencing practice, paving the way for the next generation of technologies that enhance engineering informatics.
Nature Machine Intelligence
Exploring the Intersection of Technology and Human InteractionNature Machine Intelligence, published by NATURE PORTFOLIO, is an esteemed academic journal that significantly contributes to the fields of Artificial Intelligence, Computer Vision, Human-Computer Interaction, and Software Engineering. Launched in 2019, this journal has swiftly ascended to prominence, holding Q1 status across multiple categories in the 2023 Scopus rankings, highlighting its rigorous peer-review process and high-quality research output. With an impressive 99th percentile ranking in key area categories such as Computer Networks and Communications, it has established itself as a vital platform for disseminating innovative research and fostering scientific dialogue among scholars and professionals. Although the journal is not open access, it provides a wealth of information to its audience, making it essential for those engaged in cutting-edge research and development. Academic institutions, researchers, and industry professionals can rely on Nature Machine Intelligence for the latest advances and methodologies in artificial intelligence-driven technologies.
JOURNAL OF COMPUTATIONAL PHYSICS
Exploring the Intersection of Theory and ApplicationJOURNAL OF COMPUTATIONAL PHYSICS, an esteemed publication from ACADEMIC PRESS INC ELSEVIER SCIENCE, serves as a premier platform in the field of computational physics and its interdisciplinary applications. Since its inception in 1966, the journal has provided invaluable insights and significant advancements in areas such as applied mathematics, numerical analysis, and modeling and simulation. With a robust impact factor and ranking in the top quartile across various related categories, including Q1 in Applied Mathematics and Physics and Astronomy, it is essential reading for researchers and professionals aiming to stay at the forefront of computational techniques and methodologies. Although the journal is not open access, it remains highly regarded with a reputation for rigorous peer review and high-quality publications. As the field continues to evolve, the JOURNAL OF COMPUTATIONAL PHYSICS highlights innovative research that not only advances theoretical constructs but also offers practical applications in scientific and engineering domains. For scholars and students, this journal embodies a critical resource for deepening their understanding and fostering dialogue within the scientific community.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
Exploring New Frontiers in Civil Engineering with Computer Science.JOURNAL OF COMPUTING IN CIVIL ENGINEERING is a leading publication in the field of civil and structural engineering, with a specific focus on the application of computer science techniques in civil engineering projects. Published by the ASCE - American Society of Civil Engineers, this esteemed journal has been at the forefront of innovative research since its inception in 1987 and continues to maintain high academic standards with a remarkable impact factor. Achieving a prestigious Q1 ranking in both Civil and Structural Engineering and Computer Science Applications, it holds a commendable position within the top percentiles of Scopus ranks, at 94th and 91st respectively. The journal serves as a vital resource for researchers, practitioners, and students aiming to explore the integration of computational technologies and methodologies in civil engineering practices. By publishing cutting-edge research, it aims to advance knowledge and foster collaboration within the field, contributing significantly to the development of efficient, sustainable, and innovative engineering solutions.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
Empowering Innovation through Modeling & SimulationCMES-COMPUTER MODELING IN ENGINEERING & SCIENCES is a premier journal published by Tech Science Press, dedicated to advancing knowledge in the fields of computer science applications, modeling and simulation, and software engineering. With an impressive convergence of research from 2000 to 2024, this journal stands out as a vital resource for researchers, professionals, and students alike, fostering innovation and collaboration in computational methodologies. The journal currently holds a Q3 category ranking in multiple disciplines according to the latest metrics, including Scopus, which reflects its growing significance in the academic community. By providing a platform for high-quality research and open discourse, CMES aims to enhance the understanding of complex systems through effective modeling techniques and computational tools. Despite its current classification under open access, the journal remains a cornerstone for those looking to deepen their expertise in cutting-edge computational engineering and science.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
Innovating Solutions through Computational ExcellenceCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, published by WILEY, stands as a leading journal in the domains of civil and structural engineering, computational theory, and computer-aided design since its inception in 1986. With an impressive ISSN of 1093-9687 and E-ISSN of 1467-8667, this esteemed UK-based journal holds a prestigious position in the academic community, reflected by its Q1 ranking in numerous relevant categories, including Civil and Structural Engineering and Computer Graphics as of 2023. The journal is renowned for promoting innovative research that utilizes computational techniques to solve complex engineering problems, making it an essential resource for researchers, professionals, and students alike. Despite its lack of open access options, the journal garners significant interest due to its rigorous peer-review process and high-impact articles, underlining its importance in the advancement of infrastructure engineering practices and technologies. With a Scopus ranking placing it among the top journals in various engineering and computer science fields, COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING continues to foster knowledge and collaboration, ultimately contributing to the future of smart and resilient infrastructure development.
Multiscale and Multidisciplinary Modeling Experiments and Design
Empowering researchers with open access to groundbreaking methodologies.Multiscale and Multidisciplinary Modeling Experiments and Design is a dynamic journal published by SPRINGERNATURE, dedicated to advancing the fields of applied mathematics, materials science, and mechanics of materials. With an ISSN of 2520-8160 and an E-ISSN of 2520-8179, this journal provides a platform for innovative research and multidisciplinary approaches that address complex modeling and experimental challenges from 2018 to 2024. Ranked in the Q3 quartile across its categories and holding respectable positions within Scopus rankings, it serves as a vital resource for researchers and professionals seeking to explore emerging techniques and solutions in their fields. Despite its recent inception, Multiscale and Multidisciplinary Modeling Experiments and Design fosters a collaborative environment for knowledge exchange, making it essential for anyone at the forefront of scientific discovery. Open access availability ensures that the groundbreaking research published within is accessible to a broad audience, promoting global collaboration and innovations.
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering
Pioneering Research on Risk in Civil Engineering Systems.ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering, published by the American Society of Civil Engineers (ASCE), is a leading journal dedicated to advancing the understanding and application of risk and uncertainty in civil engineering systems. With an ISSN of 2376-7642, this journal has been a pivotal platform for researchers and practitioners since its inception in 2015, converging its rigorous exploration through to 2024. It holds a commendable position in the academic community, securing a Q2 rating in categories such as Building and Construction, Civil and Structural Engineering, and Safety, Risk, Reliability and Quality as of 2023. The journal aims to disseminate innovative research that tackles the critical challenges posed by uncertainty in engineering systems, thus promoting safety, sustainability, and reliability in infrastructure. With impressive Scopus rankings, including a 76th percentile in Building and Construction, it continues to attract high-quality contributions from scholars worldwide. Emphasizing open dialogue, the journal does not currently adopt an open access model but remains committed to providing essential insights for the enhancement of civil engineering practices. Researchers, professionals, and students alike will find invaluable resources to enhance their knowledge and practice in this dynamic field.