Scientific Programming

From Big Data to Digital Twins: Theories and Methods


Publishing date
01 Aug 2021
Status
Closed
Submission deadline
26 Mar 2021

Lead Editor

1Shanghai University of Engineering Science, Shanghai, China

2Iwate Prefectural University, Takizawa, Japan

3Commonwealth Scientific and Industrial Research Organisation, Canberra, Australia

This issue is now closed for submissions.

From Big Data to Digital Twins: Theories and Methods

This issue is now closed for submissions.

Description

As the development of information communication technology (ICT) continues, Internet of Things (IoT), intelligent networks, and social media are becoming increasingly prevalent in every aspect of daily life. This has resulted in numerous efforts into big data and software services related research, exploring how the potential of collected data can be realised and offered as cloud services. However, major challenges, such as the fusion of massive heterogenous data, the coordination of multi-source data, and automatic composition of software and data services, are still open for research.

Meanwhile, Cyber Physical Systems (CPS) are a key concept of Industry 4.0 architecture. A CPS is a complex network, comprising interacting digital, analogue, physical, and human components engineered for function through integrated physics and logic. Its physical and software components are deeply intertwined and are able to operate on different spatial and temporal scales, exhibit multiple and distinct behavioural modalities, and interact with each other in ways that change with context. As the digital replica of physical devices, this virtual part eventually forms a "Digital Twin". In recent years, digital twin technology has been attracting increasing attention from researchers who explore new ideas and methods for the realisation of CPS through information fusion and cloud service composition. At present, the integration of digital twin and big data technology has a wide range of applications in different fields, including supply chain management, intelligent workshops, equipment manufacturing, product research and development, fault diagnosis, and smart cities.

The aim of this Special Issue is to present comprehensive systematic reviews, to share new research findings, and to bring forward new challenges facing digital twins and big data. More specifically, this Special Issue will focus on the state-of-the-art research into digital twins and big data as well as software modelling for its system platform to be developed, maintained, and reused. Therefore, we will focus on the system architecture, modelling, programming language, development methods, and technologies for CPS. At the same time, we will combine the latest technology in the field of big data with CPS to study the relevant theories and methods from big data to digital twin.

Potential topics include but are not limited to the following:

  • Design architecture and modelling of digital twins
  • Software systems for sensors and sensing technologies as a service
  • Big data distribution, acquisition, and transmission
  • Big data management and analytic services
  • Automatic service composition for big data and software offerings
  • Scientific programming and simulations verification for sensor-based services
  • Real-time data-driven systems control
  • IoT device management and programming
  • Asset management and services based on digital twins
  • Scientific programming in digital twins and intelligent manufacturing
  • Ontology and knowledge graphs of software systems
  • Security and privacy preserving for digital twin
  • Scientific programming-based modelling language, methods, and technology for CPS and digital twins
Scientific Programming
 Journal metrics
See full report
Acceptance rate7%
Submission to final decision126 days
Acceptance to publication29 days
CiteScore1.700
Journal Citation Indicator-
Impact Factor-

We have begun to integrate the 200+ Hindawi journals into Wiley’s journal portfolio. You can find out more about how this benefits our journal communities on our FAQ.