Symmetry and Asymmetry in Big Data Analytics
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 168
Special Issue Editors
Interests: business intelligence; analytics; decision support systems; data mining; e-business; digital transformation; research methodologies
Special Issues, Collections and Topics in MDPI journals
Interests: analytics; e-assessment; financial mathematics; quantitative methods; data mining; mathematics education; research methodologies
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The concept of symmetry is a key organising principle in many scientific fields, playing a central role in mathematical formalisation, computational modelling and the organisation of complex systems. In the context of big data analytics, properties such as invariance, structural regularity, balance and self-similarity underpin the development of efficient algorithms, scalable architectures and generalisable models. However, asymmetry—manifested through heterogeneity, skewed distributions, directional relationships, causal dependencies and informational imbalances—is a defining feature of most contemporary digital ecosystems, challenging traditional modelling assumptions. This Special Issue will explore the relationship between symmetry and asymmetry as a conceptual axis for advancing the analysis of large volumes of data. The aim is to promote contributions that examine the following: (i) the mathematical foundations of symmetry in data structures, complex networks and information theory; (ii) the formal metrics of asymmetry and entropy in large-scale data environments; (iii) analytical architectures and data pipelines that preserve structural invariants; (iv) the modelling of organisational, behavioural and decision-making asymmetries in business systems; and (v) the impact of informational asymmetry on data governance, algorithmic fairness and explainability. Approaches combining mathematical rigour with organisational applicability will be particularly relevant, including empirical studies, formal models, computational simulations, and applied cases in contexts such as finance, health, public administration, smart industry, and digital services. By integrating theoretical foundations with IS implementation challenges, this Special Issue will contribute to a more structured understanding of how symmetry and asymmetry patterns shape the architecture, performance, governance and strategic value of data-driven systems.
Dr. Ana Azevedo
Dr. Jose Manuel Azevedo
Dr. Tiago Azevedo
Guest Editors
Manuscript Submission Information
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Keywords
- symmetry and asymmetry
- invariance
- entropy and information theory
- complex networks
- big data analytics
- informational asymmetry
- data governance
- decision support systems
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