Infrastructure Systems Research Articles

STRATEGIC MARKERS OF INVESTMENT IN CRITICAL INFRASTRUCTURE OBJECTS IN THE CONTEXT OF THE ECONOMIC SECURITY OF UKRAINE

The paper examines the strategic aspects of investing in Ukraine's critical infrastructure in the state's economic security context. The importance of critical infrastructure for the stable functioning of the economy in the face of modern challenges, including military threats, cyber-attacks and natural disasters, is analyzed. The issue of financial instability, which requires the involvement of private investors and international partners to restore and modernize infrastructure, is also considered separately. The study examines the role of public-private partnership and international cooperation as the introduction of innovative technologies, such as artificial intelligence and IoT, to increase the efficiency and sustainability of infrastructure facilities. Critical strategies for effective risk management and attracting investments to restore energy, transport and communications have been identified. Recommendations are offered for assessing investments' economic and social efficiency, considering the payback and impact on the population's well-being. The paper also outlines the prospects for long-term economic growth through investment in critical infrastructure, an essential element of the country's post-crisis recovery. This study delves into the strategic dimensions of investing in Ukraine's critical infrastructure, emphasizing its significance for economic security. The paper thoroughly examines Ukraine's financial constraints due to the ongoing war and economic instability. It underscores the necessity of engaging private investors and fostering international collaboration. Public-private partnerships (PPPs) and international financial institutions are identified as crucial players in providing the necessary funding and expertise for the recovery and modernization of infrastructure. The article also explores how integrating innovative technologies, such as artificial intelligence (AI) and the Internet of Things (IoT), can significantly enhance the resilience and efficiency of infrastructure systems. In conclusion, the article offers strategic recommendations for investing in Ukraine's critical infrastructure. The purpose of the study is to identify strategic priorities for the allocation of investment resources for the reconstruction of critical infrastructure, considering the aspects of economic security.

Contribution of the Telecommunications Industry to Sustainable Development Goals within the Framework of SASB General Issue Categories: The Case of a Telecommunications Company

Sustainable development is an important issue that shapes the future of our planet by addressing economic, social and environmental factors. The United Nations (UN) has set 17 Sustainable Development Goals (SDGs) to ensure sustainable development, the success of which depends on global cooperation and joint efforts. The SDGs set out the environmental, social and economic sustainability issues to be achieved by 2030. Private sector efforts have an important role in achieving these goals. As a result of social responsibility and stakeholder demands, companies share their sustainability activities and the SDGs to which these activities contribute through reports. Telecommunications companies also have the potential to play a key role in achieving many SDGs through the innovative, accessible and inclusive digital infrastructure systems they provide. This study’s goal is to reveal the impact of the telecommunications industry on the SDGs through the Sustainability Accounting Standards Board's (SASB) General Issue Categories (GIC). In this context, a methodological framework developed by SASB to identify important sustainability issues across sectors and industries matched SDGs with 26 general sustainability issues. In this framework, SDG impact indices were calculated for the technology and communication sector, which includes the telecommunications industry, and for a telecommunications company operating in Turkey, and SDG impact at the sector, industry and company level was tried to be revealed. According to the calculations, it was concluded that the goal known as SDG 9, which was established to establish strong infrastructures, support sustainable industrialization and strengthen and expand innovation, has an impact score of 37.50% for the telecommunication services industry, 31.25% for the technology&communication sector and 31.25% for the sample telecommunication company. SDG 9 has the highest impact score in telecommunications compared to other SDGs.

Analysis on addressing the threats to cloud computing on the basis of security safeguards for sap cloud services

Cloud computing has become an integral part of combination/multi-cloud infrastructures due to its many benefits, including quick deployment, flexibility, cheap costs, and scalability, which have attracted businesses of all sizes. New possibilities and threats in terms of security flaws are cropping up in this field, even if cloud storage provides substantial advantages and inexpensive choices for IT administration and growth. When we talk about safeguarding cloud infrastructure systems, we're referring to a set of rules, regulations, and systematic procedures. This is also known as cloud computing security. The purpose of implementing these security measures is to safeguard cloud-based data, facilitate the enforcement of legislation, ensure the privacy of consumer information, and set standards for encryption in specific devices and applications. Modern cloud computing and security concerns throughout the cloud's many layers are addressed in this study. Within this context, the current study would make a substantial contribution to lowering the frequency of security breaches in cloud computing, paving the way for the continued provision of safe and reliable services. Storage of databases on the cloud is expanding rapidly in the IT industry, including SAP networks. Because enterprises are ultimately responsible for the security of their data, migrating databases to cloud computing environments brings with it a plethora of security risks. To guarantee data integrity, availability, and secrecy, appropriate security measures should be put in place before a company migrates its sensitive data to the cloud. When data is at rest, it is most vulnerable to unauthorized access; when it is in transit, it must be subject to strict supervision.

Leveraging SWOT Analysis in IS/IT Strategy for Enhancing Hospital Quality

The research conducted at the Datu Sanggul Hospital in Rantau focuses on developing a strategic plan for enhancing the quality of healthcare services through Information System (IS) and Information Technology (IT) implementation. The study aims to address the challenges faced by the hospital in optimizing its Management Information System and Medical Record (SIM & RM) unit. By utilizing the Ward & Peppard framework, the research progresses through stages including problem formulation, data collection, and strategy formulation. Through interviews, focus group discussions, and data analysis, the current business strategies and IT infrastructure are evaluated. External factors such as PEST analysis and Five Forces analysis are also considered to understand the hospital's position in the industry. The findings from these analyses serve as inputs for the SWOT analysis, which helps in identifying the hospital's current standing and areas for improvement. The study further delves into developing IS business strategies and IT roadmap planning based on critical success factors and business needs. By aligning IS/IT strategies with business goals, the research aims to provide recommendations for enhancing the hospital's information system infrastructure and management practices.

The legacy of STAHY: milestones, achievements, challenges, and open problems in statistical hydrology

ABSTRACT Statistical tools are crucial for a variety of hydrological applications, whether to model processes and enhance understanding and knowledge or to design infrastructure systems. Given the rapid evolution of statistical methods and the need for a solid theoretical foundation for their correct application, a multidisciplinary community STAtistics in HYdrology Working Group (STAHY-WG) aggregated under the International Association of Hydrological Sciences (IAHS) umbrella to contribute to this research field. Now, more than 15 years since its inception, this paper summarizes the main achievements of this productive community collaboration in four (of many) branches of statistical hydrology: extreme value analysis, multivariate analysis, time series analysis, and regionalization. The aim is to provide an overview of recent developments, offer practical suggestions (e.g. software packages), and outline future challenges to support scientists and practitioners in their endeavours within the realm of statistical hydrology studies.

A heterogeneous ring signcryption scheme with privacy protection and conditional tracing for smart grid

Smart grid develops rapidly, but there are still security risks such as user privacy leakage, power data tampering and audit data inconsistency. The existing schemes to ensure data security mainly use traceable ring signcryption, which is applied in distributed application scenarios such as smart grid. Traceable ring signcryption can ensure the anonymity, integrity, unforgeability and confidentiality of data, and can trace the real identity of anonymous users. However, the traceability of these schemes is arbitrary, any actor can trace the identity of anonymous users, and they do not resolve disputes caused by tampered or inconsistent data. To remedy these deficiencies, we combine ring signcryption with consortium blockchain technology for the first time to achieve privacy protection and conditional tracing, which can effectively avoid anonymous user identity being revealed at will. Consortium blockchain is a semi-distributed P2P network that can solve data disputes and is suitable for organizations that require certain access control mechanisms such as smart grid. In this paper, we propose a heterogeneous ring signcryption scheme with privacy protection and conditional tracing (CTHRSC) which between certificateless cryptographic system (CLC) and public key infrastructure (PKI). Besides, we prove that our scheme is secure under the discrete logarithm problem (DLP) and decisional Diffie–Hellman problem (DDHP) in random oracle model (ROM). Compared with other signature or signcryption schemes, our advantages are satisfying conditional tracing and known temporary session key security (KTSKS), requiring less computation cost and communication overhead.

MANAGEMENT OF SCALABILITY IN CLOUD-BASED APPLICATIONS

The following is an abstract of the article. The article presents an analysis of the challenges associated with monitoring and managing the scalability of a cloud application. To this end, a module for monitoring and managing the scalability of a cloud application has been developed as part of this study. The development process included the introduction of automatic scaling, and monitoring using Prometheus and Grafana, which allows for a high level of availability and resource efficiency. The study comprised a series of phases, including requirements analysis, system design, development, testing, and evaluation. Consequently, the system's performance, stability, and capacity to scale in response to fluctuating workloads were enhanced. The module exhibits a high degree of adaptability to changes in system requirements and load, which is a crucial attribute for the dynamic development of business applications. This solution assists in optimizing the allocation of resources and reducing infrastructure costs. The project has been found to fully meet the set goals and objectives, as well as the requirements for effective resource management of the Amazon Web Services cloud platform using Terraform, Prometheus, and Grafana. The practical value of the developed module is evidenced by a significant improvement in resource efficiency, service stability and cost optimisation. The module design has been subjected to rigorous testing and has been successfully implemented in a test environment, thereby demonstrating the sustainability and efficiency of the developed solution. The experience gained in the implementation and operation of this solution may prove useful for further expansion and optimization of cloud solutions in other projects and companies specializing in the provision of cloud solutions. The findings of this study were validated in a test environment at an IT company with a specialization in cloud technologies. The objective was to ascertain the functionality and efficiency of the developed module in a real-world context of cloud infrastructure operation. The testing process entailed the configuration of the module on pre-existing cloud infrastructure systems, its integration with Prometheus and Grafana for monitoring purposes, and the execution of a series of stress tests designed to assess the module's scalability. As a result of this testing, a number of critical points were identified that required further optimization. The results of the study and the issues identified during the project testing have enabled the identification of several areas for further improvement and development of the system. First and foremost, the optimization of automatic scaling algorithms represents a crucial avenue for improvement. The development of these algorithms should be oriented towards utilizing historical monitoring data to anticipate potential shifts in system load. Another pivotal area for enhancement is the precision of monitoring systems. The integration of supplementary tools and the expansion of existing monitoring systems' functionality will facilitate the acquisition of more comprehensive insights into the system's condition. This, in turn, will facilitate the expedient identification and eradication of potential issues.

Life-Cycle Performance Modeling for Sustainable and Resilient Structures under Structural Degradation: A Systematic Review

The performance of structures degrades during their service life due to deterioration and extreme events, compromising the social development and economic growth of structure and infrastructure systems. Buildings and bridges play a vital role in the socioeconomic development of the built environment. Hence, it is essential to understand existing tools and methodologies to efficiently model the performance of these structures during their life cycle. In this context, this paper aims to explore the existing literature on the life-cycle performance modeling, assessment, enhancement, and decision making of buildings and bridge infrastructure systems under deterioration and extreme events for a sustainable and resilient built environment. The main objectives are to (1) systematically review the existing literature on life-cycle performance modeling of buildings and bridges based on the PRISMA methodology, (2) provide a bibliometric analysis of the systematically assessed journal articles, (3) perform an analysis of the included articles based on the identified components of life-cycle performance modeling, and (4) provide a discussion on the utilized tools, techniques, methodologies, and frameworks for buildings and bridge infrastructure systems in the life-cycle context. The provided systematic literature review and subsequent discussions could provide an overview to the reader regarding the individual components and existing methodologies of life-cycle performance management under deterioration and extreme events.

Traffic and transportation management data storage terminal based on Internet of Things

Traditional data storage models are inadequate in the face of the growing demand for big data in transportation and transportation management. Its poor horizontal scalability makes it difficult to deal with the growth of massive data; on the other hand, its complex management makes it challenging to achieve unified management and effective resource utilization due to the differences in equipment from different manufacturers. In order to effectively store and manage this huge amount of information, it is urgent to rely on advanced technical tools. In this context, while ensuring data security and simplifying data management, it is also necessary to meet the terminal’s demand for high real-time performance, and these factors jointly promote the continuous attention and improvement of data storage terminal performance. This paper proposes a Hadoop solution based on distributed computing. As a distributed system infrastructure, Hadoop allows users to develop distributed programs without a deep understanding of distributed details, fully using the high-speed computing and storage capabilities of Hadoop clusters, which is especially suitable for big data processing tasks on the Internet of Things (IoT) platform. The experimental results show that for a 10 GB data file, the traditional terminal (Terminal 1) can store 7.8 GB, while the Hadoop-based terminal (Terminal 2) can store 9.9 GB. For 50 GB of data files, Terminal 1 and Terminal 2 can store 40.4 GB and 49.8 GB of data respectively. These results show that Hadoop terminals have significant advantages in processing large-scale data, especially in terms of data storage efficiency, and can use storage resources more effectively to meet the high-performance requirements of traffic and transportation management for data storage terminals.

Semantic Segmentation and Classification of Active and Abandoned Agricultural Fields through Deep Learning in the Southern Peruvian Andes

The monumental scale agricultural infrastructure systems built by Andean peoples during pre-Hispanic times have enabled intensive agriculture in the high-relief, arid/semi-arid landscape of the Southern Peruvian Andes. Large tracts of these labor-intensive systems have been abandoned, however, owing in large measure to a range of demographic, economic, and political crises precipitated by the Spanish invasion of the 16th century CE. This research seeks to better understand the dynamics of agricultural intensification and deintensification in the Andes by inventorying through the semantic segmentation of active and abandoned agricultural fields in satellite imagery across approximately 77,000 km2 of the Southern Peruvian Highlands. While manual digitization of agricultural fields in satellite imagery is time-consuming and labor-intensive, deep learning-based semantic segmentation makes it possible to map and classify en masse Andean agricultural infrastructure. Using high resolution satellite imagery, training and validation data were manually produced in distributed sample areas and were used to transfer-train a convolutional neural network for semantic segmentation. The resulting dataset was compared to manual surveys of the region and results suggest that deep learning can generate larger and more accurate datasets than those generated by hand.

Toward a new growth pole for the world: Rethinking the strategies for Huaihua International Inland Port in China

This article aims to analyze the existing Huaihua International Inland Port studies and regional economic development. On this basis, the strategic positioning of the port is redefined, and its impact on the economic growth of China and the world is examined. Furthermore, the article explores the port’s main challenges under the Belt and Road Initiative and proposes sustainable and healthy development strategies. It demonstrates that in the era of globalization, the importance of international trade and logistics has become increasingly prominent. As the world’s second-largest economy, China’s solid internal logistics infrastructure and well-developed transportation systems are vital to maintaining and expanding its economic vitality. It finds that the Huaihua International Inland Port is integral to China’s Western Development Strategy and has become an essential hub connecting Western China with international markets. The port profoundly impacts the economic vitality of Huaihua and surrounding areas, promoting employment and improving residents’ living standards. However, it also faces many challenges in its development. It suggests that the port administrative team needs to improve operational efficiency, efficiently coordinate various modes of transportation, attract more industries, and balance economic development and environmental protection. Based on the in-depth analysis indicates the strategic orientations and recommendations for the future development of the port. At the same time, it is expected to provide a reference for other regional economic development projects.

Risk-based decision-making for infrastructure systems under extreme events

Risk-based decision-making for infrastructure systems under extreme events

Low-altitude intelligent transportation: System architecture, infrastructure, and key technologies

In the context of the burgeoning low-altitude economy, low-altitude intelligent transportation (LAIT) has emerged as the focal point of research. This study comprehensively explores the current state, challenges, and future development prospects of LAIT from three key aspects: system architecture, infrastructure, and critical technologies. First, we propose a future LAIT system framework based on a cyber-physical system (CPS) layered architecture to provide a potential solution for urban air transport. Second, we introduce a framework for the entire lifecycle and management chain of the LAIT system, offering an in-depth analysis of each stage from design, construction, and operation to management, with the aim of realizing intelligent management and operation of low-altitude transportation. Finally, this study discusses the technical, security, and social challenges that future LAIT will face in the context of Industry 4.0, while envisioning the pathways of technological innovation. It summarizes the need for advanced infrastructure and breakthroughs in key technologies such as the Internet of Things (IoT), 6G, artificial intelligence (AI), and low-altitude geographic information system. This study provides a systematic framework and technical guidelines for the future development of low-altitude intelligent transportation, supporting continuous innovation, and upgrading the low-altitude economy.

Sulfide stress corrosion cracking in L360QS pipelines: A comprehensive failure analysis and implications for natural gas transportation safety

This research investigates the severe weld failures in L360QS pipelines, which are integral to the infrastructure of high-pressure natural gas transportation systems. Even with strict compliance to engineering standards, two pivotal welds experienced sulfide stress corrosion cracking (SSCC) due to continuous exposure to hydrogen sulfide and stresses from construction activities. A comprehensive material analysis and stress simulation has been utilized, revealing a maximum stress concentration of 544.9 MPa that surpasses the yield strength of the pipeline material. This discovery prompts a reevaluation of current safety margins and underscores the urgent need for enhanced pipeline integrity management. Our findings, corroborated by stress distribution simulations, not only illuminate the complex interplay of material properties and environmental factors in SSCC but also provide a new perspective for the safe service of pipeline.

Understanding Drinking Water Quality in Appalachia

Key TakeawaysWhile the Safe Drinking Water Act (SDWA) applies to all public water systems in the United States, the severity and prevalence of violations vary among locations.A study investigated drinking water quality, indicated by statistics of the SDWA in the 13 Appalachian states from 2010 to 2022, to identify any differences in violations.The need for better water system management and infrastructure in economically disadvantaged regions is clear, along with public education and effective policies.

Developing resilience pathways for interdependent infrastructure networks: A simulation-based approach with consideration to risk preferences of decision-makers

In this study, we propose a methodological framework to identify and evaluate cost-effective pathways for enhancing resilience in large-scale interdependent infrastructure systems, considering decision-makers’ risk preferences. We focus on understanding how decision-makers with varying risk preferences perceive the benefits from infrastructure resilience investments and compare them with upfront costs in the context of high-impact low-probability (HILP) events. First, we compute the costs of interventions as the sum of their capital costs and maintenance costs. The benefits of the interventions include the reduction in physical damage costs and business disruption losses resulting from the improved resilience of the network. In the final stage, we develop statistical models to predict the perceived net benefits of different network resilience configurations in power, water, and transport networks. These models are employed in an optimization framework to identify optimal resilience investment pathways. By incorporating Cumulative Prospect Theory (CPT) in the optimization framework, we show that decision-makers who assign higher weights to low probability events tend to allocate more resources towards post-disaster recovery strategies leading to increased resilience against HILP events, like earthquakes. We illustrate the methodology using a case study of the interdependent infrastructure network in Shelby County, Tennessee.

Toward integrated dam assessment: evaluating multi-dimensional impacts of the Grand Ethiopian Renaissance Dam on Sudan

Abstract The Grand Ethiopian Renaissance Dam (GERD) on the Nile is expected to influence many ecosystem services, such as flood regulation, hydro-electricity production, food supply, and habitat provision, among others. Understanding these impacts (positive and negative) requires a comprehensive evaluation framework. This study develops and applies an integrated simulation framework for assessing the impacts of the GERD on Sudan, focusing on the simultaneous economywide effects of riverine flood hazards, irrigation water supply, hydropower generation, and floodplain-dependent industries, namely traditional fired clay brick production. The simulation framework incorporates three models: a river infrastructure system model, a flood model, and a Computable General Equilibrium Model. Results indicate positive impacts for hydropower generation and flood control, marginal benefits for water supply to existing irrigation, and negative consequences for brick production and the construction sector. Assuming that the GERD starts its long-term operation in 2025, we find an overall positive economic impact on Sudan’s Gross Domestic Product in 2025, with an increase of up to just over 0.1%, subject to river flow conditions. Recognizing the differences in impacts across sectors and income groups, the study emphasizes the need for interventions that ameliorate negative effects. While the study captures several impacts, other effects on the environment, recession agriculture, and soil fertility require further investigation. Still, our findings underscore the importance of adopting an integrated simulation approach to dam evaluation, acknowledging the interconnected nature of water and related sectors in national economies.

Institutional Bases for The Formation of the Subject of Aviation Infrastructure Management in the System of Ensuring the Sustainability of the Northern Sea Route

The development of the Northern Sea Route (NSR) infrastructure is one of the priority areas of managerial thought in the development of the Arctic zone of the Russian Federation. Commercial use of high-latitude caravan routes in the waters of the NSR should significantly change the situation with the organization of logistical maritime flows around the Eurasian continent. Ensuring uninterrupted traffic along with fulfilment of the conditions of urgency of delivery and cargo safety form the category of stability of the NSR functioning. Its northern part runs exclusively in domestic seas, and ensuring regular vessel traffic is Russia’s priority task in the competition for transporting cargo from east to west (and back) by sea. The movement of ships along the NSR falls directly under the authority of the management of Rosatom State Corporation, while the management of the infrastructure that ensures the continuous movement of transport along the NSR is carried out collegially. At the same time, such an important aspect as the management of the infrastructure complex supporting the movement of container ships with transit cargo has been assigned to three components of a single management entity: the Ministry of Transport of the Russian Federation, the Ministry of the Russian Federation for the Development of the Russian Far East and the Arctic, and Rosatom Corporation, without clearly defining the boundaries of responsibility for interdepartmental management decisions. To date, this approach has already caused a series of organizational and technical difficulties. The aim of the study is to identify the rational organization of the infrastructure of the management subject, allowing to ensure the sustainability of the movement of passenger and cargo ships throughout the water area of the NSR; it is based on such scientific methods as induction, systematization, grouping Key results of the work may be in demand both in the course of scientific research in the field of infrastructure development in the regions of the Arctic zone of the Russian Federation, and in the framework of improving the existing management system of aviation infrastructure of these territories.

Urban Drainage Network Structure Optimization Using Emperor Penguin Optimization Algorithm

Urban drainage systems are an essential component of urban infrastructure that plays a critical role in managing stormwater and preventing flooding in urban areas. With the changing climate and urbanization, the challenges faced by urban drainage systems are becoming increasingly complex. Additionally, aging infrastructure further exacerbates the problem, creating anurban sewage line that must be made more resilient. Redundancy is just a fundamental characteristic of such a robust urban drainage network. Redundancy in urban drainage systems can help to ensure that the system continues to function during extreme weather events or emergencies, reducing the likelihood of flooding and damage. However, the exact locations where redundancy should be increased and its contribution to resilience are not well understood. In recent years, several studies have focused on developing frameworks for optimising urban drainage structures which account pipeline redundancy.One similar research presented a paradigm for constructing the ideal network layout for urban drainage infrastructure, which considers pipeline redundancy under consideration. The original architecture and structure of the urban drainage network was developed using emperor penguin optimizer algorithms and graph theory in the research. Complicated system modelling was done to find extra water pathways or redundancy which might well be implemented to boost resistance. The suggested approach has been utilised to the test region in Dongying City, Shandong Province, China, and its findings revealed even under rainfall above the design specification, the entire overflow capacity of such urban drainage network including pipeline redundancy significantly decreased about 20-30%, compared to the network without pipeline redundancies. The interest in creating optimization algorithms had also increased recently that can be used to design and manage urban infrastructure systems. One such algorithm is the Emperor Penguin Optimization (EPO) algorithm. EPO was a recently developed swarm-based optimization An algorithm which simulates Emperor penguins behaviour in their search for food in Antarctica. The algorithm has shown promising results in solving complex optimization problems in different fields, including engineering, computer science, and management. The EPO algorithm's key features include an emperor search strategy, local search, and randomization, enabling that to efficiently and successfully examine the search process. The algorithm's emperor penguin search strategy enables it to dynamically adjust the search parameters based on the problem's characteristics and progress. The local search feature allows it to escape local optima and explore the search space further. Finally, the randomization feature adds stochasticity to the search process, helping to ensure that the algorithm can avoid getting stuck in a sub-optimal solution. In this article, we aim to explore the potential of EPO as a tool for optimizing Urban drainage solutions which take into account pipeline redundancy. We will start by reviewing the existing Literature upon that optimization in urban drainage facilities, particularly the application of particle swarm optimization, genetic algorithms, and ant colony enhancement. The EPO algorithm will next be described in full including its working principle, key features, and the steps involved in applying it to an optimization problem. Finally, we will present a case study that applies the EPO technique was developed to optimise the network model of such an urban drainage infrastructure taking into account pipeline redundancies, and compare the results with other optimization algorithms. Through this, we aim to demonstrate the potential of EPO as a powerful tool for designing and managing urban infrastructure systems, particularly for enhancing the resilience of urban drainage systems. The study will provide valuable insights into the optimal design of urban drainage technologies which take into account pipeline redundancy, helping policymakers and urban planners make informed decisions about improvingthe adaptability of urban drainage networks. The findings can contribute to the development of sustainable and resilient urban infrastructure systems, which are essential for ensuring the well-being and prosperity of urban residents.

A Review of Pakistan’s National Spatial Data Infrastructure Using Multiple Assessment Frameworks

Efforts to establish Pakistan’s National Spatial Data Infrastructure (NSDI) have been underway for the past 15 years, and therefore it is necessary to gauge the current progress to channelize efforts into areas that need improvement. This article assessed Pakistan’s NSDI implementation efforts through well-established approaches, including the SDI readiness model, organizational aspects, and state of play. The data were collected from Spatial Data Infrastructure (SDI) and Geographic Information System (GIS) experts. The findings underscored challenges related to human resources, SDI education/culture, long-term vision, lack of awareness of geoinformation (GI), sustainable funding, metadata availability, online geospatial services, and geospatial standards hindering NSDI development in Pakistan. However, certain factors exhibit favorable standings, such as the legal framework for NSDI establishment, web connectivity, geospatial software availability, the unavailability of core spatial datasets, and institutional leadership. Thus, to enhance the development of NSDI in Pakistan, recommendations include bolstering financial and human resources, improving online geospatial presence, and fostering a long-term vision for NSDI.