Recent advances in sensor and data capture technologies have led to massive amounts of data being collected routinely in the physical, chemical and engineering sciences. In addition to volume, the data have other complexities such as streaming data, images, network structure and so on. The advent of Big Data has led to a pressing need to develop sophisticated methodologies and tools that will enable: (i) the handling of the rich data streams obtained from complex engineering systems, (ii) the extraction of pertinent knowledge about the environmental and operational dynamics driving these systems, and (iii) combining the empirical information with domain knowledge for more enhanced design, analysis, and control of systems.
Addressing this need is very challenging due to an array of factors that include: the inherent complexity of the system itself, the uncertainty associated with the system's operation and its environment, the heterogeneity and the high dimensionality of the data communicated by the system, and the increasing expectations and requirements posed by real-time decision-making. We believe that neither conventional engineering-based modeling and analysis methods nor purely data-driven modeling techniques can effectively address those challenges in isolation. The effective and seamless integration of physical and analytical models with data-driven methodologies is critical for improving the design, analysis, and control of complex systems. The term System Informatics has been recently used to characterize such an integrated framework. This special issue will publish original high-quality papers that deal with the development of new methodologies, innovative applications, or both.
We have listed below some examples to give potential authors some concrete ideas. However, these are meant to be indicative and are not by any means comprehensive.
• Innovative system modeling: Modeling and analysis methods that combine engineering knowledge (formal model, physical model, or empirical representation) with data to improve complex production or service systems;
• Monitoring, diagnostics, and prognostics: A holistic, system-level approach to monitoring, diagnosis, and prognostics that use integrated measures of functionalities and performance indices over the entire life cycle (quality, reliability, sustainability, etc.);
• Planning and control: Development of analytical frameworks, that integrate subject matter knowledge with empirical information, to facilitate design, planning and real-time control aiming at lead-time and productivity improvements.
The special issue will cover a broad range of application domains: hardware and software systems, production systems, energy systems, nano-manufacturing applications, transportation and communication networks, and service systems. In other words, papers in any application domain that fits within the broad scope of Technometrics will be considered.
Papers must contain high-quality original contributions that deal with the development of new methodology and/or innovative applications. Papers must be prepared in accordance with the Technometrics standards and guidelines. Submitted papers should be original, not previously published, and not under consideration for publication elsewhere. All papers will be reviewed following the regular review procedure of Technometrics.
Paper Submission
Please submit your manuscript through the on-line Manuscript Central at http://mc.manuscriptcentral.com/amstat. Please select “Special Issue” under Manuscript Type of your submission. If you have difficulties, please contact Editorial Coordinator Ms. Janet Wallace at [email protected].
Guest Editorial Board:
Important Dates:
-- September 1, 2013: Paper submission deadline;
-- January 1, 2014: Completion of the first review;
-- April 1, 2014: First revision due;
-- June 1, 2014: Completion of the second review;
-- September 15, 2014: Final decision on paper acceptance;
-- Februrary 2015: Publication of the special issue.