Description:FIELD OF THE INVENTION

[001] The present invention pertains to the field of Geospatial Knowledge Infrastructure (GKI). More particularly, the present invention is related to system and framework involving the adoption of geo-location technologies and the integration of geospatial data into everyday business processes, governmental operations, and digital infrastructures. The present invention aims to optimize decision-making, operational efficiencies, and the strategic use of location-based information through the continuous availability, standardization, and real-time processing of geospatial data.

BACKGROUND OF THE INVENTION

[002] Geospatial data indeed has transformative potential across a wide range of sectors including government, business, and public services due to its ability to provide valuable insights based on location and spatial relationships. From enhancing urban planning by enabling smarter cities to improving environmental monitoring by tracking changes in ecosystems, geospatial data supports more informed decision-making. In recent years, the importance of geospatial data has significantly increased. Geospatial knowledge plays a pivotal role in urban planning, environmental monitoring, disaster management, logistics, autonomous systems, and many other areas of modern society. However, despite the availability of geospatial technologies, their widespread integration into routine operations remains limited, often resulting in underutilization of this critical resource. This could be attributed to factors such as the lack of awareness, insufficient technical expertise, concerns around data privacy, and the need for better infrastructure to support large-scale geospatial data integration. Bridging this gap requires greater investment in technology, training, and collaboration between stakeholders to unlock its full potential.

[003] Current digital policies and frameworks often lack the emphasis on geospatial data sharing and interoperability among different platforms and agencies. This hinders the full potential of location-based information in fostering innovation, enhancing public services, and supporting sustainable development initiatives. Collaboration between technologists, data scientists, and geospatial experts is crucial to unlocking advanced applications, such as predictive analytics for market trends, real-time traffic management, and climate change mitigation strategies. Governments and organizations must adopt policies that prioritize data protection and privacy while enabling responsible data sharing for the betterment of society.

[004] The rapid expansion of digital infrastructure, cloud computing, and advanced data analytics is indeed driving the growth potential of geospatial data. By integrating geospatial knowledge into core business and government operations, organizations can make more precise and efficient decisions. For example, businesses can optimize supply chains, governments can enhance public services like transportation and waste management, and global initiatives such as climate action can leverage this data for better conservation strategies. Additionally, advancements in autonomous technologies, urban development, and environmental conservation rely heavily on accurate, continuously updated, and authoritative geospatial data sets. Trusted and reliable geospatial information is essential for supporting global initiatives and promoting sustainable practices across industries.

[005] Therefore there is an urgent need to develop a system and framework which can ensure that geospatial data adheres to international standards of accuracy, consistency, and accessibility.

[006] The present invention focuses on overcoming the current limitations of geospatial data utilization by introducing a comprehensive system and framework designed to integrate and amplify geospatial knowledge across digital infrastructures. A system which can transform geospatial data from a niche tool into a vital resource for everyday applications across sectors. The present invention, Geospatial Knowledge Infrastructure (GKI) provides a comprehensive blueprint for integrating digital economies, societies, and citizens with geospatial approaches, data, and technologies. GKI aims to deliver location-based knowledge, services, and automation expected in the Fourth Industrial Revolution (4IR). By moving beyond the current focus on data infrastructures to knowledge infrastructures, GKI supports the progression from data to applied knowledge and intelligence. The transition from traditional geospatial models to a multidimensional, integrated ecosystem driven by GKI will enable the transformation of knowledge into applied intelligence.

[007] The present invention provides such system and framework which promotes innovation by making geospatial data more accessible and interoperable, encouraging collaboration between organizations and industries that rely on location-based insights. It also emphasizes the enhancement of data-driven decision-making, allowing stakeholders to leverage real-time geospatial information for more accurate forecasting, efficient operations, and improved resource management.

[008] The present invention aligns with sustainable development goals by offering a framework for better environmental monitoring, urban planning, and disaster preparedness. The ultimate aim is to embed geospatial data into the global digital ecosystem, ensuring it becomes an indispensable tool for innovation, strategic planning, and long-term sustainability across various sectors.

[009] Furthermore, there are nearly similar concepts exists in the market like NSDI (National Spatial Data Infrastructure) and IGIF (Integrated Geospatial Information Framework) which are primarily aimed at government structures. While NSDI and IGIF provide foundational guidelines and structures for managing and utilizing geospatial data at the governmental level, the present invention provides a system and framework which offers a broader, more advanced framework encompassing and going beyond the existing frameworks aimed at government, geospatial practitioners, academia and research institutions, and technology providers.

SUMMARY OF THE INVENTION

[010] The objective of the present invention is to provide a comprehensive system and framework to integrate and amplify geospatial knowledge across various sectors, including public, private, and governmental domains. More particularly, the present invention involves the adoption of geo-location technologies and the integration of geospatial data into everyday business processes, governmental operations, and digital infrastructures.

[011] Yet another objective of the present invention is to integrate geospatial knowledge seamlessly into the global digital infrastructure, thereby enhancing digital connectivity and interoperability among diverse technologies and platforms. This includes the development of geospatial cloud computing services that can process and analyse large volumes of data efficiently, enabling real-time insights and responses.

[012] Yet another objective of the present invention is to amplify the capital value of geospatial knowledge across public and private sectors by promoting widespread adoption of geo-location technologies. This involves integrating geo-located data into standard business processes and governmental operations to enhance decision-making and operational efficiencies. The objective is to make geo-located knowledge indispensable for everyday applications, from urban planning to disaster management and logistics.

[013] Yet another objective of the present invention is to ensure the availability of continuously updated, trusted, and authoritative fundamental geospatial information at all levels. This supports not only conventional mapping and surveying but also advances in areas like autonomous driving, urban development, and environmental monitoring. It is essential for these data sets to adhere to international standards of accuracy, consistency, and accessibility to facilitate global initiatives.

[014] Yet another objective of the present invention is to encourage a culture of innovation and collaboration among technologists, data scientists, and geospatial experts. By focusing on location-based data, stakeholders can pioneer advanced applications such as predictive analytics for market trends, real-time traffic management systems, and sophisticated environmental monitoring techniques.

[015] Yet another objective of the present invention is to refine digital policies to maximize the strategic use of geospatial data and knowledge, enhancing public services and infrastructure management. Governments need to consider policies that promote data sharing between agencies and with the public, while implementing robust data protection and privacy regulations. This will ensure that geospatial data is used ethically and effectively to improve citizen services and societal well-being.

[016] Yet another objective of the present invention is to deepen the understanding of geospatial knowledge’s impact on sustainable development goals and to actively promote its role in fostering sustainable practices across industries. This includes leveraging geospatial data for environmental conservation, resource management, and climate change mitigation, emphasizing its critical role in building resilient and sustainable economies and communities.

FIGURES OF THE INVENTION

Figure 1 provides a comprehensive framework for a Geospatial Knowledge Infrastructure (GKI) system.

Figure 2 illustrates fundamental pillars of GKI which forms the backbone of the GKI system.
Figure 3 illustrates the evolving role of geospatial ecosystem from Spatial Data Infrastructure (SDI) to Integrated Geospatial Information (IGIF) and to a GKI system.

Figure 4 illustrates the maturity model of the geospatial ecosystem comprising of data infrastructure, technology infrastructure and workflow integration.

DETAILED DESCRIPTION OF THE INVENTION

[017] The following description describes various features and functions of the disclosed system and framework with reference to the accompanying figures. The terminology used herein is provided solely for the purpose of describing particular embodiments only and should not be construed as limiting the scope of the present invention. Variations, modifications, and equivalents that fall within the broader aspects of the disclosed embodiments are also considered part of the invention.

[018] The detailed description is construed as a description of the currently preferred embodiments of the present invention and does not represent the only form in which the present invention may be practiced. This is to be understood that the same or equivalent functions may be accomplished, in any order unless expressly and necessarily limited to a particular order, by different embodiments that are intended to be encompassed within the scope of the present invention.

[019] The embodiment is chosen and described to provide the best illustration of the principles of the invention and its practical application and to enable one of ordinary skill in the art to utilize the invention in various embodiments and with various modifications as are suited to the particular use contemplated.

[020] The “Geospatial Knowledge Infrastructure (GKI) system” refers to an advanced framework system designed to manage, analyse, and utilize geospatial data in a comprehensive and efficient manner. The GKI system integrates geographic information systems (GIS) with modern technologies like machine learning, artificial intelligence, and big data analytics, enabling the creation of a dynamic and scalable platform for geospatial intelligence.

[021] “Geospatial knowledge” refers to the understanding and interpretation of spatial data related to the Earth's surface, including the geographic locations of objects, regions, or phenomena and the relationships between them. It involves using geographic information systems (GIS), satellite imagery, remote sensing, and other data sources to analyse and derive insights about patterns, trends, and spatial dynamics in both natural and human-made environments.

[022] As can be seen from Figure 1 of the present invention, which provides a comprehensive framework for a "Geospatial Knowledge Infrastructure" (GKI) system.

[023] The said system consists of interconnected elements that define key components, principles, and partnerships required to build and maintain a geospatial knowledge ecosystem. Detailed description of the invention based on the image is mentioned below:

[024] Core elements of GKI includes following parts:

1) Data Infrastructure (mentioned in blue) constitutes:

a) Allied Information Enterprise: A collaborative framework that integrates geospatial data and information from diverse sources, fostering cooperation across multiple platforms and stakeholders.

b) Fundamental Data: Critical baseline geospatial datasets required for applications. These datasets are critical for accurate mapping, spatial analysis, and decision-making.

c) Real-time Information: The system continuously provides up-to-date geospatial data, enabling timely and accurate decision-making across different domains such as urban planning, disaster response, and logistics.

d) Global Reference Framework: A standardized data structure that ensures interoperability of geospatial data across regions and countries, allowing seamless integration and use of geospatial information on a global scale.

e) Real-time Digital Twin: A real-time digital replica of the physical world, which is continuously updated to reflect current changes and conditions, enabling advanced simulations and predictive analytics.

f) Open Positioning Systems: Tools and systems that provide accurate and real-time positioning and location-based data, essential for navigation, tracking, and spatial analysis.

g) Automated Data Processing and Sharing: Automated systems for data processing, management, and sharing, which streamline the handling of large geospatial datasets and facilitate quick dissemination of information to users.

2) Integrated Policy Framework (mentioned in orange) constitutes:

a) Diversity and Human Capacity Development: Initiatives aimed at fostering geospatial capacity through education, training, and the promotion of diversity in the geospatial field. This includes building expertise and developing human resources to support the sustainable growth of geospatial technologies and applications.

b) Integrate Core Geospatial Policies: The coordination and harmonization of geospatial data policies across various sectors, ensuring that regulations, standards, and best practices are consistently applied in different industries and areas of governance.

c) Global Alignment - Single Nation: Ensuring synchronization of national geospatial data policies with international standards, allowing for coherent global integration. This facilitates cross-border collaboration, data sharing, and the application of geospatial technologies at both local and global levels.

d) Alignment with ICT, Innovation, Trade, and Other Policies: Integrating geospatial policies with broader technology frameworks such as Information and Communication Technology (ICT), innovation strategies, and trade policies. This ensures that geospatial data and technologies are aligned with national and international agendas in related fields, driving innovation and economic growth.

3) Industry Ecosystem (mentioned in teal green):

a) Incubation and Commercialization of Geospatial Capabilities: Fostering innovation by supporting the development, incubation, and commercialization of emerging geospatial technologies and services. This encourages start-ups and established companies to bring cutting-edge geospatial solutions to market.

b) Investment: Promoting targeted financial support, including venture capital, public funding, and private investment, to boost growth within the geospatial industry. This ensures adequate funding for new technologies, infrastructure, and market expansion.

c) Accelerator and R&D: Driving innovation through accelerators and research and development (R&D) programs specifically focused on advancing geospatial technologies. These initiatives foster collaboration between industry, academia, and government to promote breakthroughs in geospatial solutions.

d) Ease of Doing Business: Simplifying regulatory processes, reducing bureaucratic barriers, and creating a favourable business environment for companies operating in the geospatial sector. This promotes the growth and sustainability of geospatial enterprises.

e) Geospatial within Data Economy: Recognizing geospatial data as an integral component of the broader data-driven economy. By integrating geospatial information into the data economy, businesses and governments can leverage spatial insights for enhanced decision-making, economic development, and innovation.

4) Partnerships and Collaborations (mentioned in red):

a) Co-creating Geospatial Knowledge Infrastructure: Collaborative efforts between public and private stakeholders, including governments, industries, and research institutions, to design, build, and maintain the GKI system. These partnerships are essential for ensuring a comprehensive and inclusive geospatial framework.

b) Value-chain Partnership: Establishing partnerships across the entire geospatial data value chain, from data generation to processing, analysis, and distribution. These collaborations enhance the quality and utility of geospatial products and services..

c) Citizen Partnership: Engaging citizens directly in geospatial initiatives, such as crowd-sourcing geospatial data or contributing to local mapping efforts. Citizen involvement empowers communities and improves the accuracy and relevance of geospatial data.

d) Partnership with Data Providers: Building strong, ongoing relationships with geospatial data providers, including satellite operators, government agencies, and private organizations, to ensure the continuous supply of high-quality, up-to-date geospatial data.

e) Collaborative Information Management: Facilitating joint management of geospatial data by various organizations, ensuring that data is shared efficiently and responsibly among all relevant parties for mutual benefit.

f) Broadening Stakeholders: Expanding the range of stakeholders involved in geospatial initiatives, including those from sectors like technology, telecommunications, agriculture, transportation, and environmental conservation, to foster a more inclusive and diverse geospatial ecosystem.

5) Apps Analytics and Modelling (mentioned in Green):

a) Predictive Modelling, Virtual Testing, and Simulation: Utilizing geospatial data to create predictive models and conduct virtual testing and simulations. This approach allows for forecasting potential scenarios and outcomes based on spatial variables and historical data.

b) Integration of Data Sources for National Systems: Merging various geospatial datasets from multiple sources to provide a comprehensive overview of national geospatial conditions. This integration will support informed decision-making and policy development at the national level.

c) Assurance: Implementing processes to ensure the quality, reliability, and accuracy of geospatial data and applications. This will includes validation, verification, and quality control measures to maintain high standards in geospatial analytics.

d) Apps: Developing applications that leverage geospatial data for diverse purposes, including urban planning, environmental monitoring, disaster management, transportation, and more. These applications will not only enhances the accessibility but also ensures usability of geospatial information for various stakeholders.

6) Spatial Web (mentioned in purple):

a) Semantic Web: An advanced geospatial web framework that enables the understanding and meaningful processing of spatial data. It will utilize ontologies and linked data principles to enhance data interoperability and contextual relevance.

b) Knowledge on Demand: Providing users with immediate access to relevant geospatial data and knowledge as needed. This feature will allow stakeholders to obtain insights and information quickly, facilitating informed decision-making in various contexts.

c) Real-time Processing: The capability to process geospatial data in real-time, enabling dynamic decision-making and responsiveness to changing conditions. This functionality will be crucial for applications in areas such as emergency response, traffic management, and environmental monitoring.

[025] The central component of the said infrastructure system is spatial dimension to data ecosystem which emphasizes the critical role of spatial data in various sectors, including economics, governance, security, safety, and business applications. Spatial data forms the backbone of the said system, ensuring that geospatial insights are not limited to governments but are also accessible and beneficial to businesses, public safety, and citizen-centric initiatives. By embedding spatial intelligence within the broader digital ecosystem, this component enhances decision-making across multiple domains, driving value for both public and private stakeholders in a wide range of applications.

[026] The invention, as embodied by this framework, represents a comprehensive, dynamic, and user-centric Geospatial Knowledge Infrastructure (GKI) system. It integrates real-time data processing, decentralized systems, and a diverse industry ecosystem to deliver predictive models, applications, and foster collaborative knowledge sharing. By seamlessly uniting policy frameworks with strategic partnerships and an open, accessible data infrastructure, the GKI system serves as a robust foundation for various sectors. This system will ensure enhanced accountability, transparency, and adaptability, addressing both current demands and future needs across governance, business, safety, and public services. This infrastructure system is designed by an expert group in this filed to evolve with technological advancements and is geared toward supporting decision-making in an increasingly interconnected world. The said system balances scalability with precision, making it a vital tool for ensuring sustainable development and responsive action in diverse global contexts.

[027] As can be seen form Figure 2, which provides an expanded view of a Geospatial Knowledge Infrastructure (GKI), outlining its key pillars and their functions. Here’s a detailed breakdown of the content based on the image:

[028] Key Pillars of the Geospatial Knowledge Infrastructure (GKI) system:

1) DATA INFRASTRUCTURE
This is the foundation of the GKI system, consisting of several critical components that ensure the collection, processing, and availability of geospatial data:

a) Real time Information: Data generated in real-time from various sources, including:
• Citizen-generated data
• Commercial service providers
• Earth observation
• Internet of Things (IoT)

b) Allied Information Enterprise: Diverse data streams including:
• Weather
• Environmental information
• Building information modelling (BIM)
• Business data

c) Positioning Infrastructure: Geospatial positioning systems providing location-based services, such as:
• Continuously Operating Reference Stations (CORS) Network
• GNSS augmentation
• Indoor positioning

d) Foundational Data: Core geospatial datasets that underpin various applications, including:
• Foundational layers
• Thematic data
• Reference data

2) INTEGRATED POLICY FRAMEWORK
This component ensures that policies align with the broader data ecosystem and technology landscape:

a) Integrated Geospatial Policy Framework:

• Topography and Photogrammetry: Critical for accurate mapping and land-use planning.
• Earth Observation Systems: Satellite and aerial imagery for monitoring environmental and land changes
• Cadastre and Land Information: Essential for managing land ownership, use, and legal boundaries.
b) Alignment with ICT, Innovation, Trade & Other Policies:

• Innovation and technology policies to support the advancement of geospatial technologies.
• Open and linked data policies to promote data sharing.
• Data sovereignty and protection, including personal privacy and intellectual property rights.
• Emergency and safety frameworks to ensure geospatial data is used for public safety and disaster response.

3) SPATIAL DIMENSION TO NATIONAL DATA ECOSYSTEM

a) Foundational Role: Geospatial data serves as a core element for the knowledge economy, governance, security, public safety, business enterprise, and citizen services.
b) Good Governance and Transparency: Ensuring data is used responsibly, transparently, and effectively.
c) Accountability, Efficiency, and Productivity: Using geospatial data to improve outcomes in governance, services, and business operations.
d) Value Impact and ROI: Measuring the return on investment and impact of geospatial data on various sectors.

4) PARTNERSHIPS & COLLABORATIONS
Partnerships are crucial for building and sustaining the GKI through various modes:

a) Collaborative Engagement with Multiple Stakeholders
b) Public-Private Partnerships: Working together with governments, businesses, and academia to build geospatial infrastructure.
c) Partnership with User Departments: Collaboration with the departments and agencies that use geospatial data.
d) Equity Inclusive Approach: Ensuring that all groups and communities benefit from geospatial data and infrastructure.
e) Co-creating Geospatial Knowledge Infrastructure: Building the infrastructure together with stakeholders from both public and private sectors.

[029] The present invention presents a comprehensive, user-centric Geospatial Knowledge Infrastructure (GKI) system designed to harness the power of geospatial data for enhanced analysis, real-time processing, and predictive modelling. By leveraging decentralized systems, real-time data dissemination, and tailored knowledge services, the system empowers organizations across various sectors to make data-driven decisions, ensuring transparency, accountability, and adaptability in addressing current and future challenges.

[030] Apart from aforesaid features, further features of a robust GKI system are summarized below:

a) Analytical Capability: The system's ability to measure value, impact, and return on investment (ROI) derived from geospatial data. This capability will allow organizations to assess the effectiveness of their geospatial initiatives and make informed decisions based on quantifiable outcomes.

b) Delivery of Knowledge Services: There is provision of insights, reports, and services based on geospatial data analysis. This will encompass tailored solutions which will meet the specific needs of users and stakeholders, enhancing decision-making processes.

c) Real-time Data Processing and Dissemination: The ability to quickly process and share geospatial data, ensuring timely access to information for users. This feature is essential for applications that require immediate insights, such as emergency response or operational planning.

d) Decentralized System: A distributed architecture that enables various entities to contribute to and access geospatial data without relying on a central authority. This will promote collaboration, data sharing, and resilience within the geospatial ecosystem.

e) Predictive and Prescriptive Modelling: Using data not only to understand the present but to forecast future conditions and prescribe actions.

[031] The present invention introduces a comprehensive Geospatial Knowledge Infrastructure (GKI) system that seamlessly integrates data from diverse sources, fosters strategic partnerships, and aligns with existing policy frameworks to create a dynamic, interconnected ecosystem. The GKI supports a broad spectrum of applications, including governance, business operations, public safety, and citizen services. By promoting real-time data processing, decentralized systems, and advanced analytics, the infrastructure empowers stakeholders to harness geospatial data for enhanced decision-making, predictive insights, and improved service delivery across various sectors.

[032] The present invention further provides a comprehensive and holistic assessment framework featuring GKI readiness index. As the world's only index that measures a country's geospatial readiness, this novel framework system will evaluate a wide range of parameters critical to the development of national geospatial infrastructures. These parameters include foundational geospatial data, public policies, standards, industry growth, innovation, access to geospatial knowledge, user adoption, digital readiness, and academic and research infrastructure. By providing a detailed understanding of a country's strengths and weaknesses in these areas, the index equips geospatial stakeholders with actionable insights to enhance the maturity and effectiveness of their national geospatial infrastructures, supporting strategic decision-making and sustainable development efforts.

[033] The present invention also facilitates the development of a strategic national roadmap for implementing Geospatial Knowledge Infrastructure system. The GKI framework empowers countries to assess the maturity of their national geospatial infrastructures and their readiness for geospatial knowledge adoption. By providing these tools, decision-makers can evaluate whether their national geospatial infrastructure is progressing in the right direction and identify areas that require adjustment. This framework system offers actionable insights for course correction, ensuring that the strategic development of geospatial infrastructures aligns with national goals, enhances operational efficiency, and promotes sustainable development.

[034] The GKI system of the present invention provides supporting tools to measure progress in the implementation and maturity of GKI readiness through the GKI Readiness Index framework. This tool complements existing tools from other related and unrelated technology frameworks, offering a comprehensive means for assessing the development and integration of geospatial infrastructures. By aligning with various frameworks, the GKI readiness tools ensure that countries can evaluate their progress holistically, facilitating better decision-making and cross-sector collaboration.

[035] The framework or system of the present system harmonizes geospatial technology with both emerging and established digital infrastructures. The unified ecosystem, the system creates delivers location based knowledge, services and automation which are essential for economies, societies, and citizens in the Fourth Industrial Revolution (4IR) era.

[036] In the 4IR era, characterized by rapid technological advancements and digital transformation, GKI system plays a crucial role in providing location-based knowledge that drives innovation and automation. This is essential for various sectors, including urban planning, environmental monitoring, disaster management, transportation, and more. By delivering precise and timely geospatial intelligence, the system of the present invention supports the development of smart cities, sustainable environments, and efficient resource management systems.

[037] Through extensive research and industry expertise, a framework (and a supporting index) is meticulously designed that encapsulates the critical elements essential for comprehensive understanding and informed decision-making within the geospatial domain. The framework delves deep into the nuances of each parameter and sub-parameter and provides a comprehensive understanding regarding the national geospatial infrastructures, thereby enabling the geospatial governance stakeholders to make informed evidence-based decisions.

[038] The lack of alternatives specifically tailored for the geospatial domain emphasizing the uniqueness and significance of the Geospatial Knowledge Infrastructure framework developed by an expert group in the field. While broader technology indices may exist, they often lack the depth and specificity required to address the intricacies of the geospatial industry ecosystem. Advantages over other known alternatives are as follows:

a) Uniqueness: Existing frameworks often provide generalized data management and decision-making tools that are not tailored to the unique demands of the geospatial sector. The GKI framework is specifically designed to offer geospatial domain-specific insights, integrating spatial data with critical contextual information such as public policy, environmental factors, industry capacity, and more.

b) Tailored solutions: The GKI framework is specifically engineered for the geospatial field, making it distinct from generic knowledge management tools that serve multiple industries without focusing on the unique characteristics of geospatial data.

c) Comprehensive: The system captures a comprehensive array of data points across public policies, foundation data, industry capacity and innovation, user adoption, academic and research infrastructure, digital readiness, standards, etc. Provides a deeper understanding of the national geospatial infrastructure.
d) Informed decision making among stakeholders.
e) Offers information crucial for shaping strategies, fostering collaborations, and driving innovation.
f) Promotes collaboration and knowledge sharing among stakeholders.
g) Facilitates access to a complete picture of the geospatial ecosystem.
h) Contributes to the growth and advancement of the geospatial technology sector.

[039] The system of the present invention integrates geospatial data, technologies, and methodologies with broader digital infrastructures such as cloud computing, the Internet of Things (IoT), artificial intelligence (AI), and big data analytics. This integration creates a holistic digital ecosystem. This approach eliminates data silos, allowing for seamless data flow and interoperability among various systems. As a result, geospatial information becomes part of a larger narrative, facilitating more comprehensive analyses and decision-making processes.

[040] The combination of geospatial data with other digital technologies fosters a contextually aware understanding of phenomena. This means that stakeholders can make informed decisions and interconnections can be identified. For instance, by viewing geospatial data alongside social, economic, and environmental variables, users can identify correlations and causations that may not be apparent when examining data in isolation.

[041] Furthermore, the system of the present invention prioritizes the transformation of raw geospatial data into actionable knowledge and wisdom which moves through various critical stages. This process involves not only data collection and analysis but also the application of insights derived from this data to solve real-world problems. The system not only addresses real-world challenges but also fosters collaboration between human and machine intelligence. This transformative approach ensures that stakeholders are equipped to take informed and effective actions, ultimately contributing to more sustainable and resilient systems in the face of complex societal issues.

[042] The system of the present invention is meticulously designed with users in mind, addressing their specific needs and challenges. The inherent user-centric nature of the GKI framework, combined with its scalability and adaptability, positions it as a powerful tool for addressing contemporary challenges in the geospatial domain. It is driven by the needs for knowledge rather than mere data collection. This agility enables GKI to respond effectively to global challenges, technological advancements, and evolving user expectations, ensuring its relevance and utility over time.

[043] Reflecting the decentralized nature of the web, GKI system supports complex data and application value chains with diverse partnerships. This decentralized approach fosters collaboration among different stakeholders, including governments, private sector companies, academic institutions, and civil society. By leveraging the strengths and expertise of these diverse partners, GKI addresses global sustainability challenges and works to bridge the digital divide, ensuring that the benefits of geospatial knowledge are accessible to all.

[044] By integrating data, technology, policy, and people, the system of the present invention ensures the smooth provision and utilization of geospatial intelligence within an interconnected platform. This platform supports comprehensive, geospatial-driven decision-making systems that are essential for addressing complex, multidimensional challenges. Whether it is optimizing supply chains, managing natural resources, or enhancing public health responses, the system of the present invention provides the critical location-based insights needed for effective solutions.

[045] The present invention provides a framework for integrating and amplifying geospatial knowledge across public, private and governmental domains through various steps:

a) Collecting geospatial data from multiple sources, including public databases, private networks, and real-time geo-location technologies;
b) Standardizing the collected geospatial data into a common format for uniformity and ease of use across sectors;
c) Storing the standardized geospatial data in a central or decentralized data repository accessible to authorized users in public, private, and governmental sectors;
d) Integrating the stored geospatial data into existing business processes, governmental operations, and digital infrastructures by embedding geospatial insights within decision-making tools, management systems, and applications.
e) Analyzing the geospatial data to extract actionable insights, including impact assessment, return on investment (ROI), and predictive analytics for future planning;
f) Delivering geospatial knowledge and insights via customized reports, visualizations, and dashboards tailored to specific stakeholders’ needs;
g) Facilitating real-time dissemination of geospatial data and insights to ensure up-to-date information is accessible to relevant entities for timely decision-making.

[046] GKI system contributes significantly to global sustainability by providing the geospatial knowledge necessary to manage natural resources, mitigate environmental impacts, and support sustainable development goals.

• Natural Resource Management: By analyzing geospatial data, the system or framework helps stakeholders monitor and manage natural resources such as water, forests, and minerals. This includes identifying optimal extraction methods, tracking resource depletion, and implementing conservation strategies to ensure sustainable use.
• Mitigating Environmental Impacts: The system provides insights that enable organizations to assess the environmental consequences of various activities, such as urban development, industrial operations, and agriculture. This knowledge is crucial for implementing strategies that minimize ecological footprints and protect biodiversity.
• Supporting Sustainable Development Goals (SDGs): The system offers tools and insights that facilitate progress toward various goals, including clean water and sanitation, climate action, and sustainable cities and communities. For instance, GKI can help identify areas most at risk from climate change, guiding intervention strategies.

[047] Additionally, by fostering collaboration with governments, NGO’s and businesses and communities, and bridging the digital divide, the system will ensure that even underserved and remote communities can benefit from advanced geospatial technologies. By providing access to geospatial tools and knowledge, GKI system enables these communities to engage in decision-making processes and benefit from technology-driven solutions.

[048] The foregoing description of the specific embodiments will so fully reveal the general nature of the objectives herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific objective without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed objectives. , Claims:We Claim:

1) A Geospatial Knowledge Infrastructure (GKI) system for integrating and amplifying geospatial knowledge, comprising:
an integrated platform that combines geospatial data from diverse sources;
a readiness index designed to assess the geospatial readiness of nations based on parameters including foundational geospatial data, public policies, industry capacity, and user adoption;
real-time data processing capabilities facilitating dynamic decision-making across sectors including governance, business operations, and public safety.

2) The Geospatial Knowledge Infrastructure (GKI) system, as claimed in Claim 1, further comprising a comprehensive assessment framework that provides actionable insights for enhancing national geospatial infrastructures, thereby supporting strategic decision-making and sustainable development.

3) The Geospatial Knowledge Infrastructure (GKI) system, as claimed in Claim 1, wherein the geospatial data includes but is not limited to demographic information, environmental data, transportation networks, and resource distribution.

4) The Geospatial Knowledge Infrastructure (GKI) system, as claimed in Claim 1, wherein the said index is the only globally recognized measure that encapsulates the unique parameters necessary for assessing national geospatial infrastructures, including digital readiness and research capabilities.

5) The Geospatial Knowledge Infrastructure (GKI) system, as claimed in Claim 1, wherein integrated platform harmonizes with emerging digital infrastructures such as cloud computing and the Internet of Things (IoT) to eliminate data silos and foster interoperability.

6) The Geospatial Knowledge Infrastructure (GKI) system, as claimed in Claim 1, wherein the system facilitates partnerships among government, private sector, academia, and civil society to bridge the digital divide and enhance global sustainability efforts.

7) A framework for integrating and amplifying geospatial knowledge, comprising the steps of:

collecting geospatial data from multiple sources, including public databases, private networks, and real-time geo-location technologies;
standardizing the collected geospatial data into a common format for uniformity and ease of use across sectors;
storing the standardized geospatial data in a central or decentralized data repository accessible to authorized users in public, private, and governmental sectors;
integrating the stored geospatial data into existing business processes, governmental operations, and digital infrastructures by embedding geospatial insights within decision-making tools, management systems, and applications;
analyzing the geospatial data to extract actionable insights, including impact assessment, return on investment (ROI), and predictive analytics for future planning;
delivering geospatial knowledge and insights via customized reports, visualizations, and dashboards tailored to specific stakeholders’ needs;
facilitating real-time dissemination of geospatial data and insights to ensure up-to-date information is accessible to relevant entities for timely decision-making.

8) The framework for integrating and amplifying geospatial knowledge as claimed in Claim 7, provides following characteristics of Geospatial Knowledge Infrastructure:
Knowledge-Centric Approach: Unlike its predecessors, GKI is knowledge-centric, emphasizing the application of advanced intelligence to transform data into contextual, actionable insights that can inform policy, strategy, and operations;
Distributed Cloud-Based Spatial Computing: GKI leverages distributed cloud-based spatial computing, enhancing the computational power, storage, and processing capabilities necessary for handling complex geospatial datasets and real-time analytics;
4D/5D Representation: With 4D and 5D data representations, GKI supports the visualization of changes over time and the analysis of multi-dimensional data, providing a comprehensive understanding of spatial phenomena;
Demand-Centric Orientation: GKI moves away from a purely supply-driven approach to one that is demand-centric, focusing on the value impact of data in terms of economic, social, and environmental outcomes;
Dynamic Data Integration: GKI integrates dynamic data from a wide range of sources, including crowd sourced data, mobile devices, IoT sensors, and real-time spatial data feeds, enabling holistic analysis and situational awareness;
Advanced Analytics and Prescriptive Solutions: GKI utilizes advanced augmented analytics and prescriptive solutions to support complex decision-making processes, leveraging AI and ML for predictive modelling and scenario planning;
Inclusion of Machines: With the advent of automated processes and intelligent systems, GKI includes machines as part of its user group, where autonomous systems can access, analyse, and derive insights from geospatial data;
Broader Stakeholder Group: GKI engages a broader stakeholder group, including not just geospatial professionals but also stakeholders from economics, statistics, and other sectors, enabling cross-disciplinary collaboration and integration;
Web 3.0 Semantic Web: GKI is built on the principles of Web 3.0, incorporating semantic web technologies to ensure interoperability, data linking, and contextual understanding across different datasets and applications; and
Network of Integrated Ecosystems of Ecosystems: GKI envisions a network of integrated ecosystems, where various geospatial systems, services, and solutions can interact and collaborate to form a cohesive geospatial knowledge environment.