Jul 2026· Systems Engineering· 0 citations· 8 references
TL;DR
This article argues that advancing science in an interconnected world requires treating collaboration as a designed system capability rather than an emergent by‐product of individual research efforts, and identifies three key structural elements that support sustained scientific collaboration.
Abstract
Many of today's most pressing scientific challenges arise from interactions among natural, human, and technical systems. Yet the institutions through which science is conducted remain largely organized along disciplinary and organizational boundaries. As a result, the limiting factor in addressing complex problems is increasingly not only knowledge, data, or computational capability, but the ability to integrate expertise across domains and institutions over time. From a systems engineering perspective, the scientific enterprise can be viewed as a complex socio‐technical system whose performance depends on how effectively its human and institutional components are organized and connected. This article argues that advancing science in an interconnected world requires treating collaboration as a designed system capability rather than an emergent by‐product of individual research efforts. Drawing on insights from organizational science, sociology of science, and team science, it identifies three key structural elements that support sustained scientific collaboration: a cohesive core that provides coordination and continuity, boundary‐spanning connectors that integrate knowledge across communities, and long‐term commitment expressed through structures that sustain relationships and learning over time. Together, these elements represent architectural features of the human systems through which science is conducted. Deliberately designing these human systems offers a pathway for science to more effectively address complex societal challenges characterized by interaction, interdependence, and cascading effects.
The concept of Systems-of-Systems (SoS) has become increasingly important across domains such as engineering, defence, healthcare, and digital infrastructure, describing complex assemblies of independent systems that collectively deliver capabilities beyond individual components. However, the concept remains debated: a...
Pedro B. Água, A. Correia, António Gonçalves· AHFE International· 0 citations
An analytical framework is developed that brings Otto Neurath’s and Thomas Kuhn’s views on scientific development into dialogue, theorizing CSS as a non-paradigmatic science whose epistemic commitments remain strongly shaped by more established disciplines.
Systems perspectives offer a powerful alternative paradigm for understanding social phenomena as dynamic wholes characterized by emergent outcomes arising from interdependent interactions among diverse elements across multiple levels of analysis. Despite growing interest in systems thinking within organization and mana...
Jonathan H. Westover· Human Performance· 0 citations
The Future of Systems Engineering (FuSE) programme has called for the discipline to evolve as a transdiscipline capable of engaging complex eco‐socio‐technical challenges. Yet the pace of that evolution has been slower than the arguments for it would predict. This article examines why. It argues that systems engi...
Raul Ricardo Leal Ascencio· Systems Engineering· 0 citations
The HCSAIGF contributes to AI governance research by providing an integrated explanatory architecture and offers a conceptual basis for future empirical research and more coherent governance practices.
Emre İmamoğlu· Journal of Perspectives in M...· 0 citations
This report synthesizes insights from the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing into eight priorities for community action spanning shared research infrastructure, trust and traceability, user experience, human-AI teaming, workforce development, cross-sector coordination, stewardship and...
L. McInnes, Dorian Arnold, Prasanna Balaprakash et al.· 0 citations
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