“Digital Twins” have been touted as an analytical and conceptual game changer, capturing the attention of academic researchers, industry, and policymakers alike. Applications of digital twin frameworks span engineering and medicine, as well as urban planning and the social sciences. Some examples align closely to common definitions of digital twins, integrating real-time data streams, system perspectives, state-of-the-art analytics and AI, and computational power. Others, especially those dealing with social systems or where human systems interface with natural and built environments, are perhaps better thought of as “in the spirit of” a digital twin. Despite the current prominence of digital twins, challenges and questions remain, especially around definitions, suitable applications, technical requirements, and the barriers to digital twins delivering on their promise.
This special issue of
Harvard Data Science Review (HDSR) will assemble state-of-the-art applications, methods, and perspectives, identify gaps and potential solutions, and assess the social, ethical, and economic impacts of a digital twin approach that is making inroads in nearly every aspect of society.
Contributions are invited that add clarity to general understanding of digital twins; we are especially interested in article submissions that endeavor to speak across disciplinary divides and application areas, finding commonalities in a fractured community of users, developers, and consumers of digital twin apparatuses, as well as on methods and theory to advance the quality and scientific rigor of digital twins.
SUBMISSION TOPICS
We especially welcome papers on the following topics:
- Defining digital twins, their historical development, and their relationships with synthetic
data and generative AI
- Essential elements of digital twins across domains
Innovative applications
- Data, technical, and other ongoing challenges
- Establishing the limits of digital twins and their unintended consequences
- Humans in the machine: dealing with behavior, preferences, and decisions
- Ethical aspects of digital twins (e.g., data, coverage, algorithms)
- Digital twin infrastructures and platforms
GUEST EDITORS
Michael Batty, University College London (UCL)
Rachel Franklin, Harvard University
S. V. Subramanian, Harvard University
Sarah Williams, Massachusetts Institute of Technology (MIT)
SUBMISSION CRITERIA
All submissions will undergo the standard HDSR review process: single-blind assessment by at least two independent peer reviewers. Submissions should be processed through Editorial Manager and author guidelines must be strictly followed. Special issue submissions should be submitted as full manuscripts in the format of an HDSR template.
Please contact the HDSR Editorial Office at datasciencereview@harvard.edu with questions.
Call for Submissions
Submission Deadline: January 15, 2026
Expected Publication: Summer/Fall 2026
SPECIAL ISSUE: “DIGITAL TWINS”
“Digital Twins” have been touted as an analytical and conceptual game changer, capturing the attention of academic researchers, industry, and policymakers alike. Applications of digital twin frameworks span engineering and medicine, as well as urban planning and the social sciences. Some examples align closely to common definitions of digital twins, integrating real-time data streams, system perspectives, state-of-the-art analytics and AI, and computational power. Others, especially those dealing with social systems or where human systems interface with natural and built environments, are perhaps better thought of as “in the spirit of” a digital twin. Despite the current prominence of digital twins, challenges and questions remain, especially around definitions, suitable applications, technical requirements, and the barriers to digital twins delivering on their promise.
This special issue of Harvard Data Science Review (HDSR) will assemble state-of-the-art applications, methods, and perspectives, identify gaps and potential solutions, and assess the social, ethical, and economic impacts of a digital twin approach that is making inroads in nearly every aspect of society.
Contributions are invited that add clarity to general understanding of digital twins; we are especially interested in article submissions that endeavor to speak across disciplinary divides and application areas, finding commonalities in a fractured community of users, developers, and consumers of digital twin apparatuses, as well as on methods and theory to advance the quality and scientific rigor of digital twins.
SUBMISSION TOPICS
We especially welcome papers on the following topics:
- Defining digital twins, their historical development, and their relationships with synthetic data and generative AI
- Essential elements of digital twins across domains Innovative applications
- Data, technical, and other ongoing challenges
- Establishing the limits of digital twins and their unintended consequences
- Humans in the machine: dealing with behavior, preferences, and decisions
- Ethical aspects of digital twins (e.g., data, coverage, algorithms)
- Digital twin infrastructures and platforms
GUEST EDITORS
Michael Batty, University College London (UCL)
Rachel Franklin, Harvard University
S. V. Subramanian, Harvard University
Sarah Williams, Massachusetts Institute of Technology (MIT)
SUBMISSION CRITERIA All submissions will undergo the standard HDSR review process: single-blind assessment by at least two independent peer reviewers. Submissions should be processed through Editorial Manager and author guidelines must be strictly followed. Special issue submissions should be submitted as full manuscripts in the format of an HDSR template.
Please contact the HDSR Editorial Office at datasciencereview@harvard.edu with questions.