The Keçeci Layout: A Structural Approach for Interdisciplinary Scientific Analysis

The Keçeci Layout: A Structural Approach for Interdisciplinary Scientific Analysis Mehmet Keçeci1 1ORCID : https://orcid.org/0000-0001-9937-9839, İstanbul, Türkiye Received: 02.07.2025 Özet/Abstract: The visualization of scientific data is a fundamental step in uncovering hidden patterns and relationships within complex systems. While conventional force-directed graph layout algorithms (e.g., spring layout) are effective at displaying the general topology and clustering tendencies of systems, they possess a critical shortcoming: they are inherently non-deterministic and obscure the natural, sequential, or index-based identities of nodes. This poses a significant limitation when analysing systems that contain an intrinsic sequential logic, such as quantum circuits, metabolic pathways, crystal structures, or chronological data structures. This paper introduces the "Keçeci Layout," a deterministic and order-preserving algorithm designed to fill this analytical gap. The algorithm operates by arranging nodes sequentially along a primary axis according to their IDs, employing a predictable zigzag pattern on a secondary axis to prevent node overlaps. This approach establishes a direct and intuitive bridge between a system's abstract data structure (e.g., qubit indices, reaction steps) and its visual representation. To demonstrate the versatility and efficacy of the Keçeci Layout, four case studies from distinct scientific disciplines are presented: Chemistry, Physics, Biology, Quantum Computing, Materials Science, Molecular Biology, Computer Science, etc. In conclusion, the Keçeci Layout is proven to be a powerful scientific tool that offers analytical depth by remaining faithful to the underlying data structure, moving beyond purely aesthetic presentation. The algorithm provides a significant advantage over conventional methods, particularly for the visual analysis of ordered, hierarchical, or index-dependent systems. Keywords: Deterministic Algorithm, Deterministic Layout, Graph Layout, Graph Visualization, Interdisciplinary Data Visualization, Keçeci Layout, KececiLayout, Keçeci Zigzag Layout Algorithm, Keçeci Deterministic Zigzag Layout, Node Positioning, Order-Preserving Algorithms, Sequential Layout, Scientific Computing, Structural Analysis, Zigzag Layout.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-04
DOI
https://doi.org/10.5281/zenodo.15802506
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
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article

The Keçeci Layout: A Structural Approach for Interdisciplinary Scientific Analysis

Zenodo (CERN European Organization for Nuclear Research)
Data Visualization and Analytics
article

The Keçeci Layout: A Structural Approach for Interdisciplinary Scientific Analysis

article en

Abstract

The Keçeci Layout: A Structural Approach for Interdisciplinary Scientific Analysis Mehmet Keçeci1 1ORCID : https://orcid.org/0000-0001-9937-9839, İstanbul, Türkiye Received: 02.07.2025 Özet/Abstract: The visualization of scientific data is a fundamental step in uncovering hidden patterns and relationships within complex systems. While conventional force-directed graph layout algorithms (e.g., spring layout) are effective at displaying the general topology and clustering tendencies of systems, they possess a critical shortcoming: they are inherently non-deterministic and obscure the natural, sequential, or index-based identities of nodes. This poses a significant limitation when analysing systems that contain an intrinsic sequential logic, such as quantum circuits, metabolic pathways, crystal structures, or chronological data structures. This paper introduces the "Keçeci Layout," a deterministic and order-preserving algorithm designed to fill this analytical gap. The algorithm operates by arranging nodes sequentially along a primary axis according to their IDs, employing a predictable zigzag pattern on a secondary axis to prevent node overlaps. This approach establishes a direct and intuitive bridge between a system's abstract data structure (e.g., qubit indices, reaction steps) and its visual representation. To demonstrate the versatility and efficacy of the Keçeci Layout, four case studies from distinct scientific disciplines are presented: Chemistry, Physics, Biology, Quantum Computing, Materials Science, Molecular Biology, Computer Science, etc. In conclusion, the Keçeci Layout is proven to be a powerful scientific tool that offers analytical depth by remaining faithful to the underlying data structure, moving beyond purely aesthetic presentation. The algorithm provides a significant advantage over conventional methods, particularly for the visual analysis of ordered, hierarchical, or index-dependent systems. Keywords: Deterministic Algorithm, Deterministic Layout, Graph Layout, Graph Visualization, Interdisciplinary Data Visualization, Keçeci Layout, KececiLayout, Keçeci Zigzag Layout Algorithm, Keçeci Deterministic Zigzag Layout, Node Positioning, Order-Preserving Algorithms, Sequential Layout, Scientific Computing, Structural Analysis, Zigzag Layout.

Zenodo (CERN European Organization for Nuclear Research)
International Network for Advancing Science and Policy (GB)
Openalex Percentile: Top 55%
Data Visualization and Analytics
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