Architecture Domain Research Articles

Neural dissociation between computational and perceived measures of curvature

There is substantial evidence to suggest that preference for visual curvature is a reliable phenomenon. Yet, little is known about the ways in which the encoding of curvature in the brain contributes to hedonic evaluation while participants are actively engaged in making choices about objects varying in curvature. To address this question, we reanalyzed fMRI data collected while participants made aesthetic judgments (beautiful vs. not beautiful) and approach-avoidance decisions (enter vs. exit) in relation to measures of (a) computational curvature, (b) perceived curvature, (c) perceived angularity, and (d) aesthetic pleasure in the domain of architecture. Our results show that a region in early visual cortex (BA 17) encompassing largely areas V2-V3 is sensitive to variation in computational curvature across both beauty judgments and approach-avoidance decisions, whereas a region encompassing the fusiform gyrus (BA 37) exhibits sensitivity to perceived curvature only when participants made beauty judgments. These results contribute to our understanding of the neurobiological basis of curvature preference by demonstrating that the sensitivity of the visual cortex to computational curvature is context invariant, whereas the sensitivity of the fusiform gyrus to perceived curvature varies by context.

Navigating complex riskscapes: the Koudiet Eddraouch GIS substation project in Sub-Saharan Africa

Learning outcomes Risk identification and qualitative assessment are the learning outcomes. Case overview/synopsis The Bharat Bijlee Construction Limited (BBCL) was one of the largest construction companies operating in the power sector in India. After successfully completing a few projects in the Middle East, BBCL decided to expand its presence into African region. The BBCL was awarded a $85m contract for three sub-station projects to modernise Algeria’s power grid system by the “Shariket Karhaba Koudiet Eddraouch Spa”, a state-owned company in charge of power generation, transmission and distribution in Algeria. The project, which is the first of BBCL in Saharan region in Algeria’s, presents many unique situations that company had never encountered before, including sand dunes, severe weather, remote locations, supply chain & logistics, strict contractual deadlines and a high level of construction risk. The project manager for BBCL was sceptic about how well his company would perform under the present project circumstances. How could he better align himself with the client, the various on-site local contractors and the numerous suppliers spread around the world? The case emphasises the identification of various project risks that the project manager might encounter in the project. What do the PESTLE and ASCE frameworks for risk identification each represent, and how are they helpful for the project team in understanding various risks? How should the project’s qualitative risk assessment be conducted? And how can a heat map be a better tool for comprehending the criticality of each risk in the project? Complexity academic level Undergraduate and post graduate courses in project management, civil engineering and architecture domain. Supplementary material Teaching notes are available for educators only. Subject code CSS 2: Built Environment.

Optimization of Electronic-Based Government System Architecture (SPBE) In The Application Architecture Domain In XYZ District

The Electronic-Based Government System (SPBE) is a government administration that utilizes information and communication technology to provide services to SPBE Users as stipulated in Presidential Regulation No. 95 of 2018. SPBE aims to create an integrated government business process between Central Agencies and Regional Governments, form a complete government unit and produce bureaucracy and high-performance public services. To support the implementation of SPBE, the National SPBE architecture is compiled as a detailed guide that covers technical and methodological aspects, ensuring the integration of government electronic systems. This architecture provides convenience in increasing efficiency and effectiveness, as well as being a guide for SPBE governance in Central Agencies and Regional Governments. The XYZ Regency Government has implemented the SPBE architecture as the basis for implementation in its area. This study analyzes the SPBE architecture in XYZ Regency based on the National SPBE architecture to provide optimization recommendations on the application architecture domain. Despite the existence of Presidential Regulation Number 95 of 2018 and Number 132 of 2022, the preparation of government architecture in Indonesia still faces challenges due to the lack of clear guidance. More detailed references are needed as derivatives of existing regulations to ensure consistent and optimal implementation, help agencies understand and implement the SPBE architecture, so that digital transformation towards Indonesia 4.0 is achieved by 2040.

STEP: Sequence of time-aligned edge plots

We present sequence of time-aligned edge plots (STEP): a sequence- and edge-scalable visualization of dynamic networks and, more broadly, graph ensembles. We construct the graph sequence by ordering the individual graphs based on specific criteria, such as time for dynamic networks. To achieve scalability with respect to long sequences, we partition the sequence into equal-sized subsequences. Each subsequence is represented by a horizontal axis placed between two vertical axes. The horizontal axis depicts the order within the subsequence, while the two vertical axes depict the source and destination vertices. Edges within each subsequence are depicted as segmented lines extending from the source vertices on the left to the destination vertices on the right throughout the entire subsequence, and only the segments corresponding to the sequence members where the edges occur are drawn. By partitioning the sequence, STEP provides an overview of the graphs’ structural changes and avoids aspect ratio distortion. We showcase the utility of STEP for two realistic datasets. Additionally, we evaluate our approach by qualitatively comparing it against three state-of-the-art techniques using synthetic graphs with varying complexities. Furthermore, we evaluate the generalizability of STEP by applying it to a graph ensemble dataset from the architecture domain.

Developing a Performance Evaluation Benchmark for Event Sourcing Databases

In the domain of software architecture, Event Sourcing (ES) has emerged as a significant paradigm, especially for systems requiring high levels of auditability, traceability, and intricate state management. Systems such as financial transaction platforms, inventory management systems, customer relationship management (CRM) software, and any application requiring a detailed audit trail can significantly benefit from this approach. Numerous aspects of ES remain unexplored, as they have yet to be thoroughly investigated by scientific research. The unique demands of such systems, particularly in terms of database performance and functionality, are not adequately addressed by existing database benchmarks. By establishing benchmarks, organizations can compare different databases to determine which best meets their needs for applications. This aids in selecting the most appropriate technology based on empirical data rather than assumptions or marketing claims.This paper introduces a novel benchmarking framework specifically designed for evaluating databases in the context of event sourcing. The framework addresses critical aspects unique to ES, including event append performance, efficient handling of Projections (separate databases for read operations), strong consistency, ordered data insertion, and robust versioning controls. Through rigorous testing and analysis, this framework aims to fill the gap in existing database benchmarking tools, providing a more accurate and relevant assessment for ES systems. We also conducted experiments that not only demonstrated the effectiveness of our approach but also yielded meaningful results, substantiating its practicality and applicability.

BRIDGING THE GAP: INDUSTRY-ACADEMIA COLLABORATION IN ARCHITECTURE

This study delves into the ever-needed symbiotic relationship between industry and academia within the architecture domain, clarifying the benefits, and challenges of their collaboration. The multifaceted dimensions of industry-academia collaboration in architecture focuses on the interns' enhancing their understanding during training, fresh graduates' grasp of technical know-how at their first job, and the role of innovative industry partnerships in problem-solving and future building. Through a mixed-method research approach, the paper examines the perceptions of architectural interns and fresh graduates on the effectiveness of educational preparation, their technical know-how and their creative proficiencies encountered in their initial professional roles. Innovative partnerships between industry leaders and academic institutions are further evaluated to unveil the collaborative efforts in addressing contemporary architectural challenges and innovations. The findings suggest a significant discrepancy between academic training and industry requirements, indicating a need for curriculum reform and an enhanced framework for continuous collaboration. This study not only contributes to a deeper understanding of the transition from academic preparation to professional practice but also presents practical implications for curriculum development and strategic industry engagement.

ArchGPT: harnessing large language models for supporting renovation and conservation of traditional architectural heritage

The renovation of traditional architecture contributes to the inheritance of cultural heritage and promotes the development of social civilization. However, executing renovation plans that simultaneously align with the demands of residents, heritage conservation personnel, and architectural experts poses a significant challenge. In this paper, we introduce an Artificial Intelligence (AI) agent, Architectural GPT (ArchGPT), designed for comprehensively and accurately understanding needs and tackling architectural renovation tasks, accelerating and assisting the renovation process. To address users’ requirements, ArchGPT utilizes the reasoning capabilities of large language models (LLMs) for task planning. Operating under the use of tools, task-specific models, and professional architectural guidelines, it resolves issues within the architectural domain through sensible planning, combination, and invocation. Ultimately, ArchGPT achieves satisfactory results in terms of response and overall satisfaction rates for customized tasks related to the conservation and restoration of traditional architecture.

Visual analysis of fitness landscapes in architectural design optimization

In architectural design optimization, fitness landscapes are used to visualize design space parameters in relation to one or more objective functions for which they are being optimized. In our design study with domain experts, we developed a visual analytics framework for exploring and analyzing fitness landscapes spanning data, projection, and visualization layers. Within the data layer, we employ two surrogate models and three sampling strategies to efficiently generate a wide array of landscapes. On the projection layer, we use star coordinates and UMAP as two alternative methods for obtaining a 2D embedding of the design space. Our interactive user interface can visualize fitness landscapes as a continuous density map or a discrete glyph-based map. We investigate the influence of surrogate models and sampling strategies on the resulting fitness landscapes in a parameter study. Additionally, we present findings from a user study (N = 12), revealing how experts’ preferences regarding projection methods and visual representations may be influenced by their level of expertise, characteristics of the techniques, and the specific task at hand. Furthermore, we demonstrate the usability and usefulness of our framework by a case study from the architecture domain, involving one domain expert.

SegCFT: Context-aware Fourier Transform for efficient semantic segmentation

Semantic segmentation has been one of the most critical tasks in computer vision. Recent works mainly focus on improving segmentation performance by designing high-capacity transformer architectures. They try to solve the high data consumption and computing costs required for model training and deployment in the cloud, but the high computation overhead still makes it difficult to be directly applied to limited resource devices. In this paper, we propose a novel fast Fourier Transform (FFT) based Context-aware Feature Mixer under the transformer-like architecture for precise and efficient semantic segmentation, called SegCFT. Different from the self-attention-based transformer, SegCFT uses a Hierarchical Fourier Transform (HFT) to reduce computational cost via non-parametric calculation and promote segmentation performance by fusing the channel-wise and pixel-wise contexts. To integrate the features from the frequency domain of DFT into the spatial domain of the transformer-like architecture, an Adaptive Modulation Unit (AMU) is designed to modulate the frequency-domain features and ensure consistency between the frequency domain and the spatial domain. Experimental evaluation on two semantic segmentation benchmarks, ADE20k and Cityscapes, shows that SegCFT achieves competitive segmentation performance, while the training and inference costs are superior to the previous methods.

Exploration of Natural Element Form Optimization Algorithm using Spatial-Temporal Multi-Scale Alignment Graph Neural Network in Architectural Design Based on Morphological Theory

The construction industry has experienced important changes in recent years due to advancements in digital, artificial intelligence, and construction technologies, as well as the sector's on-going development and the advancement of science and technology. The creative growth of building industry, creative creation of architectural forms are partially supported technically by sophisticated parametric design apparatuses, the potent computing benefits of computer technology. In this manuscript, Exploration of Natural Element Form Optimization Algorithm using Spatial-Temporal Multi-Scale Alignment Graph Neural Network in Architectural Design Based on Morphological Theory (ENEF-OA-ADMT) is proposed. The STMSA-GNN and the Chaotic Coyote Algorithm (CCA) are two tools used by the proposed ENEF-OA-ADMT approach to improve architectural design based on morphological theory. The ST-MSA GNN's ability to capture intricate interactions and dependencies between several components in both space and time allows it to perform a comprehensive study of the morphological aspects of architectural designs. This graph neural network's integration of spatial and temporal dimensions enables a deeper understanding of how the architectural structural form design changes over time. The CCA optimized the ST-MSA-GNN to enhance the architectural structural form design. The proposed ENEF-OA-ADMT methodology skill fully combines these methodologies, creating a strong framework that allows architects and designers to work together to explore, refine, and create architectural structural design forms. The framework provided serves as a spur for further research, encouraging a more complete integration of technology and environment in the architectural domain. The effectiveness of proposed method is executed in python, evaluated through performance metrics encompassing accuracy, precision, specificity, Recall, computational time, F1 score, population diversification, randomness. Proposed ENEF-OA-ADMT method 34.56%, 28.63% and 21.89% higher accuracy, 34.97%, 32.13% and 21.89% higher precision and 34.68%, 20.84% and 29.76% higher randomness when compared with the existing methods such as Study of Morphological Design of Architecture from Geometric Logic Perspective (SOT-MDA-GLP), learning deep morphological networks by neural architecture search (LD-MN-NAS) and identifying degrees of deprivation from space utilizing deep learning with morphological spatial analysis of deprived urban areas (IDDS-DLMSA-DUA) respectively.

Sapphire stories: the symbolic representation of blue motifs in Islamic architecture of Pakistan

This article focuses on analyzing and exploring the implication of blue motifs in terms of the representation of Islamic architecture in Pakistan. Architecture holds a great deal of importance within every nation's social and cultural domains. In the same way, architecture has played a significant role in dispensing Islam as a religion. The manifestation and reflection of blue motifs are present in various forms, such as formal, structural, and spatial. Moreover, these shapes carry symbolic connotations when presented in the form of ornamentation, geometrical patterns, floral displays, and arabesque. Furthermore, this study provides a valuable contribution to enhancing the awareness of the significance and representation of blue motifs in the Islamic architecture of Pakistan for the research. Secondary and primary data were collected to achieve the objectives of the study. The study concludes that mosques and shrines in Pakistan are loaded with examples in which the representation of blue motifs within the domain of Islamic architecture is quite evident.

Our Common Gulf Cities: agenda for equitable AEC industries for sustainable urban development

PurposeThis paper delves into the critical role of women in the domains of architecture, engineering, construction and urban planning, particularly within the context of the United Nations sustainable development goals (SDGs) and the imperative of achieving gender parity. Concentrating on the Gulf Cooperation Council (GCC) countries, this paper explores the profound importance of women as essential contributors to urbanisation and sustainable development. It scrutinizes the existing gender disparities within the architecture, engineering and construction (AEC) industries; evaluates prevailing women empowerment indices in diverse sectors; and presents a strategic framework for harnessing women’s engagement to cultivate inclusive and sustainable urban cultures in the GCC. This conceptual paper introduces an actionable framework that can serve as a guiding agenda for empowering women in the AEC sectors by incorporating their socio-cultural, economic and ecological contributions towards creating sustainable cities.Design/methodology/approachCentring its focus on Gulf Cities, this paper employs a comprehensive approach to examine the current gender disparities within the architecture, engineering and construction sectors. It probes potential barriers and advocates for leveraging women’s participation to foster inclusive and sustainable urban development in the GCC. The study introduces the Women’s Empowerment Index (WEI) for the Gulf AEC industry elucidating how these measures are translated into a tailored framework.FindingsThe paper presents a practical framework that provides actionable guidance for engaging various stakeholders, including governments, academia and industry players, to empower women within the AEC industries. An “Agenda for equitable AEC industries for sustainable urban development: Our Common Gulf Cities” is culminated in a Women Empowerment Index for the AEC Industry (WEI-AEC) designed to serve as a guidance tool to monitor progress within industry, governments and academia.Research limitations/implicationsFuture research endeavours could advance the framework by conducting institutional support analyses, multi-stakeholder collaboration studies and practical testing of the framework within real-world scenarios.Practical implicationsThe findings of this study can guide and influence a diverse range of initiatives, including policy development, educational strategies, corporate endeavours, awareness campaigns, capacity-building programs, skill enhancement initiatives and knowledge exchange among the Gulf Cooperation Council countries.Originality/valueThis conceptual paper introduces a practical framework that can serve as a roadmap for implementing the study’s potential to shape policies, educational programs and corporate initiatives aimed at advancing both gender equality and the development of sustainable cities.

HaLo‐NeRF: Learning Geometry‐Guided Semantics for Exploring Unconstrained Photo Collections

AbstractInternet image collections containing photos captured by crowds of photographers show promise for enabling digital exploration of large‐scale tourist landmarks. However, prior works focus primarily on geometric reconstruction and visualization, neglecting the key role of language in providing a semantic interface for navigation and fine‐grained understanding. In more constrained 3D domains, recent methods have leveraged modern vision‐and‐language models as a strong prior of 2D visual semantics. While these models display an excellent understanding of broad visual semantics, they struggle with unconstrained photo collections depicting such tourist landmarks, as they lack expert knowledge of the architectural domain and fail to exploit the geometric consistency of images capturing multiple views of such scenes. In this work, we present a localization system that connects neural representations of scenes depicting large‐scale landmarks with text describing a semantic region within the scene, by harnessing the power of SOTA vision‐and‐language models with adaptations for understanding landmark scene semantics. To bolster such models with fine‐grained knowledge, we leverage large‐scale Internet data containing images of similar landmarks along with weakly‐related textual information. Our approach is built upon the premise that images physically grounded in space can provide a powerful supervision signal for localizing new concepts, whose semantics may be unlocked from Internet textual metadata with large language models. We use correspondences between views of scenes to bootstrap spatial understanding of these semantics, providing guidance for 3D‐compatible segmentation that ultimately lifts to a volumetric scene representation. To evaluate our method, we present a new benchmark dataset containing large‐scale scenes with ground‐truth segmentations for multiple semantic concepts. Our results show that HaLo‐NeRF can accurately localize a variety of semantic concepts related to architectural landmarks, surpassing the results of other 3D models as well as strong 2D segmentation baselines. Our code and data are publicly available at https://tau‐vailab.github.io/HaLo‐NeRF/.

REDCap to Epic interfaces create an efficient hybrid software solution for a public health registry.

A public health registry and intervention was created in response to the Flint water crisis to identify and refer exposed individuals to public health services to ameliorate the deleterious impact of lead exposure. Traditional technology architecture domains, funded scope of work, as well as community input were considered when defining the requirements of the selected solutions. A hybrid software solution was created using Research Electronic Data Capture (REDCap) to deploy an open participant survey and bypass requirements to create user accounts, and Epic to manage deduplication and participant communication and tracking. To bridge the two software systems, REDCap to Epic unidirectional ADT and Documentation Flowsheet interfaces were built to automate creation of subject records in Epic identical to those created in REDCap and to copy key protocol-driving variables from REDCap to Epic. The interfaces were critical to deliver a successful hybrid solution in which the desired features of each software could be leveraged to satisfy specific protocol requirements and community input. Data from the start of survey administration (December 2018) through 31 December 2020 are reported to demonstrate the usefulness of the interfaces.

An Enterprise Architecture Planning for Tour and Travel Company Using TOGAF ADM

Purpose: This study aims to address inefficiencies in service delivery processes within PT. Auva Eqtena Tour and Travel, particularly concerning manual operations and administrative document management. By utilizing the TOGAF ADM (The Open Group Architecture Framework Architecture Development Method) methodology, the research seeks to develop a strategic plan for information systems that enhances service efficiency and streamlines operations. Methods: The research employs the TOGAF ADM methodology to guide the strategic planning process for information systems improvement. Four key aspects are considered: vision architecture, business architecture, information system architecture, and technology architecture. Through a systematic approach, the study identifies areas for improvement and proposes strategic initiatives to optimize the utilization of information systems and technology. Results and Discussion: Analysis of the current operational processes within PT. Auva Eqtena Tour and Travel reveals inefficiencies in manual operations and document management, leading to delays and increased resource consumption. The application of TOGAF ADM methodology facilitates the development of strategic plans across various architectural domains. The proposed initiatives include enhancements in vision architecture, business processes, information system integration, and technological infrastructure to optimize information system utilization and improve service delivery efficiency. Implications of the Research: The findings have significant implications for PT. Auva Eqtena Tour and Travel, providing actionable insights for enhancing service efficiency and operational effectiveness through strategic information systems planning. By aligning business objectives with technology capabilities, the proposed initiatives aim to streamline processes, reduce costs, and enhance customer satisfaction. Originality/Value: This study contributes to the existing literature by applying the TOGAF ADM methodology to address operational challenges within the tour and travel industry. By integrating strategic planning principles with architectural frameworks, the research offers a structured approach to information systems development and optimization. The proposed strategic plan provides a roadmap for PT. Auva Eqtena Tour and Travel to leverage information systems effectively, thereby enhancing its competitive position and service delivery capabilities in the market.

Theoretical formation in the field of critique: a critical reading of Chinese architectural anti-waste campaign in 1955

ABSTRACT This study appraises the ideological criticism that emerged in the Chinese architectural sphere during the anti-waste campaign of 1955, which marks a pivotal moment in the history of modern Chinese architecture. Within this timeframe, architects and architectural scholars such as Chen Gan, Shui Fengman, and Liu Dunzhen, respectively questioned, defended, and criticized Liang Sicheng’s architectural ideas. Their articles were published in prominent Chinese publications including People’s Daily, Wenyi Bao [Art News], Jianzhu Xuebao [Journal of Architecture], and Xin Jianshe [Journal of New Construction]. By delving deep into the conceptual framework and the logical structure of these long-neglected critique articles, this study unveils the intricate debates in Chinese architectural practice and theoretical concepts during the 1950s. The findings highlight that the ideological critique during the anti-waste campaign not only reflects the infiltration of politicized rhetoric into the architectural domain but also assumes a profound significance in terms of the early attempts of Chinese architects to re-evaluate architectural historiography through the lens of Marxist theory. This pivotal event laid the foundation for the gradual formation and consolidation of a series of discursive patterns within the Chinese architectural community, exerting a lasting influence on contemporary architectural discussions and writings in multifarious ways.

Identification and empowerment of capabilities and potentials in urban tourism with an approach to enhancing brand image and personality: A case study of Tabriz City

<p>This research focuses on identifying and enhancing the capabilities and potentials of urban tourism with the aim of improving the brand image and personality in Tabriz City. The research methodology, given its practical nature, is based on the analytical-survey method. The statistical population includes all city managers and experts in the tourism sector of Tabriz City. The data were analyzed using SPSS software, and the ANP and TOPSIS Fuzzy decision-making models were employed for prioritizing criteria. The results indicate that Tabriz City possesses exceptional tourism power, capacity, and potential. The examination of urban tourism capabilities and potentials in Tabriz demonstrates that its tourism capacity is particularly pronounced in the social, cultural, traditional, historical, and architectural domains. The social and cultural identity index of the city (celebrities, music) with a normalized weight of 0.0277, the presence of historical entities in the city with a normalized weight of 0.0274, the old context with traditional architecture (houses, mosques, etc.) with a normalized weight of 0.0272, great variety in souvenirs and food products with a normalized weight of 0.0271, creating a sense of belonging to a neighborhood among residents with a normalized weight of 0.0270, and special customs in the city (food styles, etc.) with a normalized weight of 0.0270 are among the most important indicators. Therefore, city managers and officials in the tourism sector of Tabriz should pay special attention to the social and cultural capacities and historical and architectural components to introduce Tabriz as a cultural and historical city at both the national and international levels. The tourism planning for Tabriz should be based on the city's cultural, architectural, and historical attractions.<strong></strong></p>

Advanced hierarchical planning and design for low-carbon landscape architecture leveraging virtual reality technology

Abstract The incorporation of sophisticated artificial intelligence technologies and data mining methodologies is critical for the planning and design of low-carbon landscape architectural environments. To enhance the three-dimensional reconstruction capabilities and visual esthetics of hierarchical planning and design within low-carbon landscape architectural environments, this study introduces a novel methodology predicated on virtual reality (VR) technology. This approach harnesses the diverse pictorial structure feature distribution inherent to low-carbon landscape architectural environments, amalgamated with VR's feature structure reorganization and enhancement techniques. Furthermore, we propose methodologies for joint measurement and multi-level integration to refine the hierarchical planning and design process within these environments. Simulation outcomes demonstrate the efficacy of this method in achieving superior three-dimensional reconstruction and visual representation, thereby augmenting the planning and design quality within the domain of low-carbon landscape architecture.

Lived experience in human-building interaction (HBI): an initial framework

The emerging field of human-building interaction (HBI) has its roots in the historical trends of the development of architecture and human-computer interaction (HCI). Advancements in building information modelling (BIM), sensing, and actuation technologies as well as the commodification and miniaturisation of microprocessors over the past two decades are transforming what once were quixotic visions of a cybernetic architecture into reality. This new reality which integrates computation with architecture opens up different kinds of engagements in the ways we design, use, and inhabit our built environments. A question that follows this new reality is: how can we conceptualise human experience in such environments? Thus far, the lived human experience of such interactions has been an overlooked aspect in HBI-related research. In this article, we provide an initial experience framework for HBI underpinned by existing literature from the HCI and architecture domains on the subjective, lived-in experience of architecture and findings derived from a case study of a field-deployed HBI interface. The research objective of our framework is to outline aspects of HBI lived experiences that can be used as guiding lenses for HBI designers and practitioners who wish to design for and assess such experiences.

Go.Data as a digital tool for case investigation and contact tracing in the context of COVID-19: a mixed-methods study

BackgroundA manual approach to case investigation and contact tracing can introduce delays in response and challenges for field teams. Go.Data, an outbreak response tool developed by the World Health Organization (WHO) in collaboration with the Global Outbreak Alert and Response Network, streamlines data collection and analysis during outbreaks. This study aimed to characterize Go.Data use during COVID-19, elicit shared benefits and challenges, and highlight key opportunities for enhancement.MethodsThis study utilized mixed methods through qualitative interviews and a quantitative survey with Go.Data implementors on their experiences during COVID-19. Survey data was analyzed for basic univariate statistics. Interview data were coded using deductive and inductive reasoning and thematic analysis of categories. Overarching themes were triangulated with survey data to clarify key findings.ResultsFrom April to June 2022, the research team conducted 33 interviews and collected 41 survey responses. Participants were distributed across all six WHO regions and 28 countries. While most implementations represented government actors at national or subnational levels, additional inputs were collected from United Nations agencies and universities. Results highlighted WHO endorsement, accessibility, adaptability, and flexible support modalities as main enabling factors. Formalization and standardization of data systems and people processes to prepare for future outbreaks were a welcomed byproduct of implementation, as 76% used paper-based reporting prior and benefited from increased coordination around a shared platform. Several challenges surfaced, including shortage of the appropriate personnel and skill-mix within teams to ensure smooth implementation. Among opportunities for enhancements were improved product documentation and features to improve usability with large data volumes.ConclusionsThis study was the first to provide a comprehensive picture of Go.Data implementations during COVID-19 and what joint lessons could be learned. It ultimately demonstrated that Go.Data was a useful complement to responses across diverse contexts, and helped set a reproducible foundation for future outbreaks. Concerted preparedness efforts across the domains of workforce composition, data architecture and political sensitization should be prioritized as key ingredients for future Go.Data implementations. While major developments in Go.Data functionality have addressed some key gaps highlighted during the pandemic, continued dialogue between WHO and implementors, including cross-country experience sharing, is needed ensure the tool is reactive to evolving user needs.