Spatial Data Infrastructure

The application of Geographic Information Systems (GIS) in the work of government bodies, economic subjects and units of regional and local self-government presents the real situation today in every European country, as well as in its regions. The organisation of collecting, storing, distribution and usage of spatial data, in accordance with the principals of spatial data infrastructure (SDI) presents the next (higher) level in the application of spatial data and GIS. Rapid development of GIS application in the last decade highlights two problems in the efficient usage of GIS technologies, entailing the usage of spatial data in general. The first problem is the lack of the concept in organising the spatial data that has been solved basically through the development of IPP concept. The other problem lies in the fact that the subjects and the users do not have enough knowledge of GIS and IPP. Therefore, special attention has been paid within the frame of INSPIRE project to the development of education concept for the subjects and users of IPP, in order to provide the possibility for them to use the advantages offered by the concept of enhanced technologies and IPP itself. The paper presents the current situation in the education referring to GIS and IPP, and describes the activities carried out for the purpose of creating the environment that would provide quicker and more efficient implementation of National SDI (NSDI) based on better information given to the subjects and users.

The development of a National Spatial Data Infrastructure (NSDI) represents a critical advancement in the management and accessibility of geospatial data, facilitating informed decision-making across sectors such as government administration, environmental monitoring, and urban planning { (Rajabifard and Williamson 2003), (Rajabifard and Williamson 2002), (Nebert 2001)}.In the context of Armenia, establishing a robust NSDI is particularly important, given the country's need to modernize its spatial data infrastructure and align with international standards, such as the European INSPIRE Directive (European Commission, 2007).One of the key components of this effort is the standardization of spatial data layers, which is essential for ensuring the effective use of data in various applications ranging from urban planning to environmental protection and resource management.This research focuses on developing a methodology for the standardization of basic layers in Armenia's NSDI, which are critical for the country's geospatial data infrastructure.These basic layers include administrative boundaries, real estate data (cadastral data), land valuation, property rights, land use (land cover), addresses, geographical names, surface water data, elevation models, relief, and transport infrastructure.Standardizing these layers involves creating consistent and interoperable datasets that can be utilized across various sectors, including land administration, environmental monitoring, disaster management, and infrastructure planning.The proposed methodology follows best practices outlined in international frameworks such as the INSPIRE Directive (European Parliament and Council, 2007), the ISO 19100 series of geographic information standards (ISO, 2002), and the Open Geospatial Consortium (OGC) standards (OGC, 2020), ensuring that the basic spatial data layers adhere to both national and international interoperability requirements.The methodology developed in this study consists of four key stages: (1) Data Collection and Preparation-gathering raw spatial data from a variety of sources, including orthophotos and existing topographic maps, to ensure comprehensive and up-to-date information; (2) Attribute Definition-establishing the mandatory attributes for basic spatial data layers based on NSDI standards for Armenia, ensuring completeness, consistency, and interoperability with other datasets {(Nogueras-Iso, Zarazaga, and Muro-Medrano 2005), (Tth et al. 2012), (Hadzilakos et al. 2000) }; (3) Data Structuring and Conversion-transforming raw data into standardized formats such as vector and raster formats, ensuring compatibility with NSDI requirements, and using standardized coordinate systems and metadata formats {(Heimovi, Marasovic, and Tavra 2014), (Rao et al. 2002)}; (4) Data Integration-combining basic spatial data layers with each other, such as administrative boundaries, land use, surface water, elevation models, and other relevant data, to create a cohesive and interoperable spatial database that can be used for multi-disciplinary applications.By following these stages, the research aims to contribute to the successful implementation of standardized and accessible basic spatial data layers within Armenia's NSDI framework.This approach not only aims to meet Armenia's national standards but also aligns with international initiatives for spatial data infrastructure development, ultimately enhancing the quality and availability of basic spatial data layers for a wide range of applications {(Craglia and Annoni 2006), (Kotsev et al.

This paper addresses the state of spatial data infrastructures within North America in late 1997. After providing some background underlying the philosophy and development of the SDI concept, the authors discuss effects of technology, institutions, and standardization that confront the cohesive implementation of a common infrastructure today. The paper concludes with a comparative framework and specific examples of elements and initiatives defining respective spatial data infrastructure initiatives in the United States and Canada.

The integration of marine and land based spatial information will support sustainable management and development of the coastal zone. Therefore, the development of a seamless platform covering the land and marine environments would facilitate more efficient and effective decision-making capabilities for any jurisdiction with land-marine interface. This paper discusses the potential for developing a seamless platform covering the land, marine and coastal environments as part of the National Spatial Data Infrastructure (SDI) enabling a more integrated and holistic approach to management of the land-marine interface. It addresses the feasibility of seamless platform towards spatially enabled society and government. Further, it provides an insight to the design and development of the Seamless SDI model by introducing Seamless SDI conceptual model. The Seamless SDI class and its inherited characteristics and properties will be discussed. In addition to the conceptual phase, the development of a Seamless SDI model also consists of two more stages: design phase and implementation phase. The Use Case Diagram and Class Diagram of the Enterprise Viewpoint will be developed. Finally, it highlights the importance of the creation of appropriate Seamless SDI governance structures that are both understood and accepted. This would help to develop an extended framework to support a spatially enabled jurisdiction covering the land-marine interface. Ideally this extended framework would result in harmonised and universal access, sharing and integration of coastal, marine and terrestrial spatial datasets across regions and disciplines.

With the advancement of GIS technology since its inception in 1960’s, many educational institutions, government departments, public/ private sectors and individuals have started its use for the production and management of spatial data. Spatial Data Infrastructure (SDI) concept was introduced in the early1990’s and provides a set of technologies, standards, protocols, policies and guidelines on the whole cycle of geospatial data production and distributions, i.e., from data capture to storage and to sharing. SDI initiative at national level, termed as National Spatial Data Infrastructure (NSDI), has been taken by different countries including India. Geospatial community is facing various challenges like handling of large volumes of geospatial data, requirement of high computing resources to process geospatial data, scalability and interoperability. Therefore, need of advanced technologies in the form of SDI and cloud computing is realized to resolve the above challenges. Cloud computing has several characteristics like scalability, elasticity and self-provisioning that offers high-performance computing resources to perform geoprocessing efficiently. The main aim of the present paper is to study SDI and its components along with analysis and comparison of NSDI of various countries as well as to conceptualize and discuss service oriented architecture of cloud enabled SDI. Several challenges of the spatial data handling and processing that occurred due to the high intensity of data and lack of processing capability can be solved by adopting proposed cloud enabled SDI architecture. This research will help geospatial community and SDI developers in various perspectives including data sharing and management, interoperability, security and reliability, fault tolerance, mass market solution, upfront cost and global collaboration.

Spatial data infrastructure (SDI) is a framework for collecting, storing, managing, and distributing spatial data. It is a critical component of any modern geographic information system (GIS) and is used in a wide range of applications, including land management, environmental monitoring, and emergency response. One important aspect of SDI is the legal component, which includes the laws and regulations that govern the collection, use, and sharing of spatial data. These laws and regulations can vary depending on the jurisdiction and can include issues such as data ownership, privacy and intellectual property rights. In the Republic of Armenia, with the concept of “Integrated Cadastre”, it is planned to implement and develop a National Spatial Data Infrastructure (NSDI). Nevertheless, in the Republic of Armenia, not all stages of the implementation of NSDI have been developed yet, including a legal document defining the availability of data at different levels. For the implementation and effective policy development of NSDI, it is necessary to give attention to the regulation of legal relations regarding spatial data at different levels. For this purpose, we studied the legal documents related to the regulation of the field of spatial data in the Republic of Armenia, identified the contradictions and problems in the existing legal documents, which made it possible to highlight the necessary relevant legal provisions.

In this thesis, concepts for developing Spatial Data Infrastructures with an emphasis on visualizing 3D landscape and city models in distributed environments are discussed. Spatial Data Infrastructures are important for public authorities in order to perform tasks on a daily basis, and serve as research topic in geo-informatics. Joint initiatives at national and international level exist for harmonizing procedures and technologies. Interoperability is an important aspect in this context - as enabling technology for sharing, distributing, and connecting geospatial data and services. The Open Geospatial Consortium is the main driver for developing international standards in this sector and includes government agencies, universities and private companies in a consensus process. 
\n3D city models are becoming increasingly popular not only in desktop Virtual Reality applications but also for being used in professional purposes by public authorities. Spatial Data Infrastructures focus so far on the storage and exchange of 3D building and elevation data. For efficient streaming and visualization of spatial 3D data in distributed network environments such as the internet, concepts from the area of real time 3D Computer Graphics must be applied and combined with Geographic Information Systems (GIS). For example, scene graph data structures are commonly used for creating complex and dynamic 3D environments for computer games and Virtual Reality applications, but have not been introduced in GIS so far. 
\nIn this thesis, several aspects of how to create interoperable and service-based environments for 3D spatial data are addressed. These aspects are covered by publications in journals and conference proceedings. The introductory chapter provides a logic succession from geometrical operations for processing raw data, to data integration patterns, to system designs of single components, to service interface descriptions and workflows, and finally to an architecture of a complete distributed service network.
\nDigital Elevation Models are very important in 3D geo-visualization systems. Data structures, methods and processes are described for making them available in service based infrastructures. A specific mesh reduction method is used for generating lower levels of detail from very large point data sets. An integration technique is presented that allows the combination with 2D GIS data such as roads and land use areas. This approach allows using another optimization technique that greatly improves the usability for immersive 3D applications such as pedestrian navigation: flattening road and water surfaces. It is a geometric operation, which uses data structures and algorithms found in numerical simulation software implementing Finite Element Methods. 
\n3D Routing is presented as a typical application scenario for detailed 3D city models. Specific problems such as bridges, overpasses and multilevel networks are addressed and possible solutions described. The integration of routing capabilities in service infrastructures can be accomplished with standards of the Open Geospatial Consortium. An additional service is described for creating 3D networks and for generating 3D routes on the fly. Visualization of indoor routes requires different representation techniques.
\nAs server interface for providing access to all 3D data, the Web 3D Service has been used and further developed. Integrating and handling scene graph data is described in order to create rich virtual environments. Coordinate transformations of scene graphs are described in detail, which is an important aspect for ensuring interoperability between systems using different spatial reference systems. The Web 3D Service plays a central part in nearly all experiments that have been carried out. It does not only provide the means for interactive web-visualizations, but also for performing further analyses, accessing detailed feature information, and for automatic content discovery.
\nOpenStreetMap and other worldwide available datasets are used for developing a complete architecture demonstrating the scalability of 3D Spatial Data Infrastructures. Its suitability for creating 3D city models is analyzed, according to requirements set by international standards. A full virtual globe system has been developed based on OpenStreetMap including data processing, database storage, web streaming and a visualization client.
\nResults are discussed and compared to similar approaches within geo-informatics research, clarifying in which application scenarios and under which requirements the approaches in this thesis can be applied.
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Recently, Spatial Data Infrastructures (SDIs) has been a rapidly expanding field and broadly assumed to underpin the development of information society and the knowledge economy. In this paper, we argue that the anticipated benefits of SDIs have largely not yet been generally realized in practice due to a lack of a robust theoretical framework as well as insufficient empirical research to guide the implementation efforts. We posit that learnings from the allied discipline of Information Infrastructures, which has matured during the 1990s in response to the proliferation of distributed, complex, and heterogeneous networked systems, can provide a useful theoretical lens to inform the emerging domain of SDIs. We focus on three key concepts identified in the domain of information infrastructure theory, viz. the installed base, reflexive standardization, and cultivation approach to design, to develop a theoretical framework, which is then applied to analyse the ongoing initiative to establish National Spatial Data Infrastructure (NSDI) in India. This analysis helps us to provide the basis to articulate a potential research agenda—for both theory and practice—which, we believe, offers the promise to better conceptualize and implement SDIs, particularly in developing country settings like India.

Most national Spatial Data Infrastructures (SDI) were built based on a clearinghouse concept. The concept requires all of the service providers to maintain a Web (map) service recourse which leads to duplication of efforts from data collectors. The objectives of developing a geo-service broker are to make data services and other services within an SDI centrally organized, available and accessible to consumers. A geo-service broker offers a centralized and harmonized view on resources. The objective of this research is to investigate how a geo-service broker is built as a tool for intelligent search and information retrieval in the semantic Web for better service delivery of geo-services over the Internet.

The spatial data plays a vital role in any developmental activities whether it is natural resource management or socio-economic development. Most land-related government departments in Botswana have over the years since independence in 1966 developed systems to support their principal areas of operations as regards to spatial data. The adequacy and currency of spatial data in government operations improved leading to a need for integrated systems. This has progressively led to issues of building a National Spatial Data Infrastructure (NSDI) and an initiative modeled around Federal Geographic Data Committee (FGDC) has been established. Several facilitative committees were set and several meetings held in attempt to develop the idea to a realizable level and integrate it into the greater workings of the national economy. This noble idea has stalled for some time now and it is the intention of this paper to report on how the idea was initiated in Botswana and look at the probable causes for its stalling. The paper will then go ahead and suggest what could be done to revitalize the idea by relating it to what is considered the best practices in Spatial Data Infrastructure (SDI) programmes globally.

Cartography and spatial data infrastructures (SDIs) are mutually dependent on each other: SDIs provide geographic information for maps; and maps help to understand geographic information provided by an SDI. SDIs emerged in the 1990s when paper maps were replaced by map production from digital geographic information. They evolved from government-funded initiatives within the geographic information science (GISc) community to SDIs with a variety of data producers and an audience much beyond the relatively small GISc community. SDIs continue to evolve in response to new technologies and developments. This chapter traces SDI evolution over the last three decades and considers how SDI technical developments have impacted map production and how they are likely to impact map production in the future.

국가공간정보체계(NSDI)는 국가 공공기관의 공간정보를 통합 연계하여 공동 활용하기 위한 목적으로 2008년부터 추진되어 2012년 그 사업을 완료하였다. NSDI의 존재에도 불구하고 각 기관의 공간정보와 NSDI의 공간정보가 동시에 갱신되지 않는 방식을 사용하기 때문에 최신성 확보에 어려움이 있다. 공공기관의 공간정보를 활용한 서비스 사용현황을 살펴보면, 재활용이 가능한 비슷한 서비스가 중복 구축 및 운영되고 있으며 이에 따라 국가 예산이 낭비되고 있다. 이러한 이슈들은 전산자원을 공유하기 위한 목적의 클라우드 시스템을 NSDI에 적용함으로써 해결될 수 있다. 본 논문에서는 서비스 클라우드 기반의 NSDI 확대발전 방안을 다룬다. 제안되는 NSDI의 확대 발전 방안은 공간정보 서비스 클라우드 시스템 구축방안과 거버넌스 체계 수립방안을 포함한다. 시스템 구축방안에서는 서비스 시나리오, 목표 시스템의 개념도, 그리고 서비스 기능이 도출된다. 서비스 기능에서는 제안된 두 가지 모듈에 대한 단위 기능과 세부 기능을 도출한다. 거버넌스 체계 수립방안에서는 서비스 클라우드 기반의 NSDI 운영을 위한 서비스 라이프사이클 단계별 조직의 필요역할을 정의하고 업무 프로세스를 도출한다. 제안된 시스템 구축방안을 기반으로 상세 시스템을 설계하고 조직을 구성함으로써 서비스 클라우드 기반의 NSDI 체계가 구축될 수 있을 것으로 기대된다. The construction of National Spatial Data Infrastructure (NSDI) started from 2008 and was completed at 2012, with the aim of co-utilizing public agencies' national spatial information by integrating and linking. Despite the existence of the NSDI, an update of spatial data is not fully reflected because the spatial information has not been updated simultaneously by NSDI and public agencies. By examining the public agencies' services using the spatial information, a national budget is wasted because the re-usable similar services are duplicated. These issues could be solved by adopting a cloud system, whose concept is co-utilizing IT resources, to the NSDI. This study examined the service cloud based expansion and development plan for NSDI. The plan included an implementation strategy for a spatial information service cloud system and an establishment plan for a governance system. The service scenarios, concept diagram, and service functions for the system were derived in a system implementation plan. For the service functions, the unit functions of two modules were proposed and specific functions were derived. In the establishment of a governance system, the business roles and business processes were defined for organizations managing service cloud based NSDI. The business role and process were defined and derived by each service life-cycle step. With the proposed system implementation plan, a detail system design and composition of the organization could be possible, and a service cloud-based NSDI system could be implemented.

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book discusses some of the key issues related to the development of the US National Spatial Data Infrastructure or National Spatial Data Infrastructure (NSDI). It describes the main components of the NSDI, the National Digital Geospatial Data Framework, the Clearinghouse, and Metadata Standards, and the issues being faced in implementing it. The book examines the factors that contribute to the development of effective infrastructures for information sharing. It provides an overview and a comparative evaluation of geographic information systems diffusion in local government in nine European countries based on a series of studies and surveys undertaken in each country by a local team of experts. The book highlights the importance of modelling the geometry of linear features for their generalisation.

Abstract. The new concept of Open Spatial Data Infrastructures (Open SDIs) has emerged from an increased interest in open data initiatives together with national and international directives, such as the EU Open Data Directive (Directive (EU) 2019/1024), and the large investment of European public authorities in developing SDIs for sharing spatial data within public authorities. Open SDIs have the potential to boost reaching SDIs’ general aims and goals of facilitating the exchange and sharing of spatial data to support planning and decision-making by including public participation and increased openness in all aspects of SDIs, including Open SDI Education. The open SPatial data Infrastructure eDucation nEtwoRk (SPIDER) project aims to address Open SDI Education by particular emphasis on studying Active Learning and Teaching (ALT) methods for SDI education. This article provides a theoretical basis of ALT for SDI methodologies. We show in which way ALT practices were already implemented in SDI education at the Partner universities before the COVID-19 pandemic. We also describe how the pandemic functioned as a catalyst for implementing ALT practices to an online environment, and how students evaluated these practices. The outcomes of our research can serve as an inspiration for SDI education in other countries.

Spatial data infrastructures for cities in developing countries