Automatic spatial metadata systems – the case of Australian urban research infrastructure network

Australia invests significant resources in environmental data acquisition, management and publication. Although data are abundant, users are typically hampered by an inability to discover, access and re-use the data. The National Environmental Information Infrastructure (NEII) activity will improve the effectiveness and efficiency of discovering, accessing and re-using environmental data beyond its primary purpose. The NEII is envisioned as a federation of environmental data nodes adopting common standards to create a data infrastructure with an initial focus on nationally significant environmental data. Its primary focus is on the discovery and re-use of national environmental data that is already well-managed, but that currently has limited application beyond its original business purpose. In common with spatial data infrastructures, the NEII encompasses common data models, exchange formats and standard network protocols along with centralised catalogues of uniform metadata descriptions. It also includes standardised models for describing environmental measurements, monitoring sites and methods used to observe the environment to address the unique requirements of environmental information. These architectural elements are more fully described in the NEII Reference Architecture (Bureau of Meteorology, 2014b, www.neii.gov.au). The Bureau of Meteorology is leading the development of the NEII including provision of core coordination and integration infrastructure, as well as the governance and collaboration framework for its development and operation. However its ongoing success is dependent on establishing enduring partnerships with major national environmental information organisations. The NEII Programme is framed around five focus areas including (a) Communication, (b) Engagement, (c) Policies and frameworks, (d) Data management, and (e) ICT build. This paper provides a more detailed overview of one component of the Data Management area regarding the development of the NEII Conformance Framework. Conformance means following established guidelines, specifications and standards or working towards them. A conformance framework is a structured set of guidelines that detail the levels at which a participant provides services that comply with the NEII architecture. The NEII Conformance Framework has been developed to (a) enable partners to set priorities against specific expectations that will jointly lead to developing a sustainable federated environmental information system; (b) enable users of the NEII to rapidly assess the suitability of data for their business needs; and (c) provide a common measurement system to monitor progress in the development of the NEII. The framework adopts a capability maturity model approach to describe the steady improvement required for NEII nodes to progress from a basic data release (experimental data service with limited operational support) to an enduring federated system providing environmental information. The design of the model is informed by other maturity-based approaches for open data such as the Open Data Institute's certification approach (Open Data Institute 2015). The paper also presents a worked example of the conformance framework against the Bureau of Meteorology's Australian Hydrologic Geospatial Fabric NEII data services. The paper concludes with an overview of major learnings from the programme to-date. These relate primarily to reducing the cost of participation in NEII by data custodians given the challenge of delivering data using NEII standards; and developing approaches to better support users to use the portfolio of NEII data given some of the methods of data delivery may be new to non-technical users. The NEII programme has prioritised both these and developed work packages to achieve improvements.

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.

Web mapping is the process of using geo-spatial information through the cyberspace. Itconsists both a service activities and end-user activities. Web GIS emphasises geo-datadistribution aspects more involved with design aspects such as data accruing, storage,processing with server software architecture such as data storage and algorithms. Web basedsystem is more advanced than stand-alone system because its provide pathway to overcomegeographical boundaries. As a result of this one, any user who has internet facility will beable to access the system.This paper aims to address the role of Spatial Data Infrastructure (SDI) as a framework forthe development of a web-based system as a tool for facilitating forestry management byresolving current problems with spatial data. Centralise web GIS tool facilitates tovisualisation and update geo-spatial data for forestry management sector in Sri Lanka. Thisresearch is a one of node to open the gate to access the cyberspace which consists of SDI.Collected forest data were cross checked with existing GIS data sources and Google Earthbefore incorporate to the system. Web system was created using HTML5 and PHP language.Google Map class library and Java script library were used to render the Google Map to theweb GIS system and Arc GIS cloud database is used as a geo-database for storing forestrydata. in addition to that, several software packages have been used such as AdobeDreamweaver, Adobe Photoshop, PHP editor, MySQL database, Java, Ajax, Arc GIS, Arcserver etc.Web administrator will be able to maintain and update the system using the givenauthentication facility and to maintain and change query function of the geo-database. Enduser will be able to read the map and gather information using attribute data. In addition tothat, the system facilities to get the print out of the selected area with all map componentssuch as legend, map title, scale etc.Keywords: Web GIS, Cloud GIS, Forest management, SDI, GIS modelling

This research presents an operational framework to assess organizational Spatial Data Infrastructures (SDIs) from a risk perspective to develop a stable SDI. The core of the framework is constructed based on a survey, fuzzy inference system and cluster analysis, providing quantitative indicators to measure and prioritize the risks to SDI. This framework could mainly contribute to identifying, mitigating or avoiding the potential risks of different aspects of an SDI, such as spatial data and information, organizational and technological aspects. Additionally, it could be considered as an approach that supports multi-view SDI assessment framework toward a more comprehensive assessment of SDIs. A prototype implementation to assess and prioritize the risks of the spatial data and information demonstrates the framework merit, flexibility and usability for assessing the risks of SDI initiatives at different levels, such as organizational, local and national levels; however, the risks and SDIs change over time; thus, the development of stable SDI initiatives depends on a continuous process for coping with the risks.

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.

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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Abstract. The Japanese government, local governments and businesses are working closely together to establish spatial data infrastructures in accordance with the Basic Act on the Advancement of Utilizing Geospatial Information (NSDI Act established in August 2007). Spatial data infrastructures are urgently required not only to accelerate computerization of the public administration, but also to help restoration and reconstruction of the areas struck by the East Japan Great Earthquake and future disaster prevention and reduction. For construction of a spatial data infrastructure, various guidelines have been formulated. But after an infrastructure is constructed, there is a problem of maintaining it. In one case, an organization updates its spatial data only once every several years because of budget problems. Departments and sections update the data on their own without careful consideration. That upsets the quality control of the entire data system and the system loses integrity, which is crucial to a spatial data infrastructure. To ensure quality, ideally, it is desirable to update data of the entire area every year. But, that is virtually impossible, considering the recent budget crunch. The method we suggest is to update spatial data items of higher importance only in order to maintain quality, not updating all the items across the board. We have explored a method of partially updating the data of these two geographical features while ensuring the accuracy of locations. Using this method, data on roads and buildings that greatly change with time can be updated almost in real time or at least within a year. The method will help increase the availability of a spatial data infrastructure. We have conducted an experiment on the spatial data infrastructure of a municipality using those data. As a result, we have found that it is possible to update data of both features almost in real time.

Environmental monitoring and evaluation (M&E) systems are indispensable tools for sustainable land management, especially in dry and fragile ecosystems. The reporting and dissemination of its products and indicators are the key roles to perform their missions. Furthermore, the overall success of such multilateral projects and networks depends on well-organized infrastructures for spatial data management. A spatial data infrastructure (SDI) is an efficient framework to centralize the management of spatial data and information related to multilateral projects for the best sharing and exchange between partners and stakeholders in order to ensure that they are interactively connected to use the data efficiently and in a flexible manner. This paper outlines the work undertaken in partnership between the Geography and GIS Department of the Faculty of Arts, King Abdulaziz University, Saudi Arabia Kingdom, the Geomatics, Earth and Land Settlement Branch of the Department of Geology, Faculty of Sciences of Tunis, Tunis El Manar University, Tunisia, and the Sahara and Sahel Observatory OSS which is an intergovernmental organization, in order to build a Spatial Data Infrastructure (SDI) for the ROSELT/OSS program (Long-Term Environmental Monitoring Observatories Network in the Circum-Sahara of the Sahara and Sahel Observatory). This SDI is entirely developed using Open Source technologies and the extensive suite of OGC (Open Geospatial Consortium) standards and specifications, to enable interoperability among and between its different components.

Spatial data infrastructures for cities in developing countries

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.

This paper aims at reevaluating the role of Spatial Data Infrastructure (SDI) as an initiative which can facilitate disaster management by providing a better way for managing spatial data. SDI contains technological and non-technological aspects for sharing and exploiting geo-information resources. The results of the research have shown that a prototype emergency spatial data sharing system using an SDI framework can assist the disaster management in such a way that they can improve the efficiency and quality of data for the decision making and increase the effectiveness in data collection and sharing activities during the management of emergency spatial data.

The need to create multi-participant, decision-supported environments to address the issues of sustainable development and improving the quality of life creates a growing need to organise data across disciplines and organisations through different forms of spatial data infrastructure (SDI). This infrastructure is fundamentally a concept about facilitation and coordination of the exchange and sharing of spatial data between stakeholders from different jurisdictional levels in the spatial data community. The concept is well explained as an integrated, multi-levelled hierarchy of interconnected SDIs based on partnerships at corporate, local, state/provincial, national, regional (multi-national) and global (GSDI) levels. The creation of such an infrastructure and understanding the role of dynamic partnerships within an SDI hierarchy are essential to develop any SDI initiative. This paper reviews the nature and concept of SDIs, including the SDI hierarchy, which has helped to build understanding about the impo...

Abstract. The aim of a spatial data infrastructure (SDI) is to make data available for the economical and societal benefit to a wide audience. A geoportal typically provides access to spatial data and associated web services in an SDI, facilitating the discovery, display, editing and analysis of data. In contrast, a spatial information infrastructure (SII) should provide access to information, i.e. data that has been processed, organized and presented so as to be useful. Thematic maps are an example of the representation of spatial information. An SII geoportal requires intelligence to orchestrate (automatically coordinate) web services that prepare, discover and present information, instead of data, to the user. We call this an intelligent geoportal. The Open Geospatial Consortium's Web Processing Service (WPS) standard provides the rules for describing the input and output of any type of spatial process. In this paper we present the results of an evaluation of two orchestration platforms: the 52° North framework and ZOO project. We evaluated the frameworks' orchestration capabilities for producing thematic maps. Results of the evaluation show that both frameworks have potential to facilitate orchestration in an intelligent geoportal, but that some functionality is still lacking; lack of semantic information and usability of the framework; these limitations creates barriers for the wide spread use of the frameworks. Before, the frameworks can be used for advance orchestration these limitations need to be addressed. The results of our evaluation of these frameworks, both with their respective strengths and weaknesses, can guide developers to choose the framework best suitable for their specific needs.

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.

The need for spatially explicit thematic data is currently increasing in parallel to the development of observing, storing and processing capabilities. This requires an integrated data management structure in which human and institutional aspects play a key role as part of a Spatial Data Infrastructure (SDI). We focus in this study on the African continent to evaluate the status of its SDI implementation. Because assessing SDI at a continental scale in a traditional way (i.e. following methods developed for national assessments) requires financial resources and mechanisms only affordable to developed countries (e.g. European Union), alternative ways have been explored based on fourteen key SDI indicators that were validated by SDI experts in a previous study. Data was collected for each African country through the African leading SDI institution (UN Economic Commission for Africa) and through Internet searches. We found relatively weak scores of the fourteen SDI indicators for African countries compared to the rest of the World, but with notable differences within Africa. We discuss the implication of the lack of information available on the Internet to assess SDI status in Africa. We conclude that it is necessary to improve statistical information in most African countries. This requires an agreed-on geospatial data structure and organization between concerned institutions that is only achievable through a shared global vision on geospatial data governance. To this end, we suggest a few quick wins and several new mechanisms that would enhance the flow of SDI statistical information and improve data management structure in Africa.