spatial Data Infrastructure (SDI)

Abstract Over the past few years, several technology trends, notably big data analytics, volunteered geographic information, cloud computing, free and open source software, internet of things, and linked data, have emerged. This study reviews the contribution of some of these trends to Spatial Data Infrastructure (SDI) development, particularly in Africa. A geospatial application based on Google Container Engine, an Infrastructure as a Service cloud, has been developed. Data was sourced from the 2015 Kenya Certificate of Primary Education, the Kenya school mapping project of 2007 from the Ministry of Education, Science and Technology, and Kenya’s administrative boundary layers from the Independent and Electoral Boundaries Commission. By using the cloud, several operations and analyses typically common in SDIs were carried out. In addition, a cost estimate of a cloud-based Kenya National Spatial Data Infrastructure deployment is presented. Although the new technologies may not necessarily lead to wider SDI adoption, the study shows that the trends can increase the chances of SDI development and adoption, by permitting highly scalable geoservices, and facilitating cost-effective free and open source software.

It has been nearly twenty years since the National Survey Authority of Oman first initiated the idea in 1995 to adopt the development of a National Geographic Data Infrastructure (NGDI). While many countries in the world have successfully or partially successful in developing their national spatial data infrastructure within this time period, Oman does not make much progress and it is yet to see the development of the national SDI to materialise. Therefore, this study is important as it seeks to identify the factors which may contribute to Oman's failure and is significant to provide recommendation(s) to rectify the situation and to pave the way forward to a successful implementation of the NSDI.

Based on Australia’s experience in building the foundations of a marine spatial data infrastructure and an extensive literature review, a generic, idealised Governance Framework is postulated in this paper to support a bottom-up, SOA-based, SDI development. This Framework addresses how to incentivise, control, monitor, and supervise the building of an SDI using governance principles and motivational models inherently found in successful open source development projects. The Framework is under-pinned by assumptions consistent with observed mainstream information infrastructure design principles (Hanseth & Lyytinen, 2006). Developed with hindsight, the Framework draws on the author’s practical experience over the last three years, playing a number of roles within the Australian marine SDI community, including marine SDI project sponsor, project manager, community developer, data contributor and end-user. Many conclusions are made through observing approaches which did not work successfully during implementation, as much as they are based on observations of successful actions or governance. This paper is organised as follows. Section 2 presents the basic tenets of the SOA paradigm and the types of technology standards involved, as they are applied to SDIs and which are exemplified by reference to building Australia’s marine spatial data infrastructure. Section 3 outlines complex governance issues that arise from the SOA paradigm, primarily those surrounding service: design; integration; standards compliance; typing; versioning; quality and performance monitoring. These rather abstract issues are explored by using the Australian case study to provide concrete examples with which the reader can identify. This section also examines how open source communities could be productively used to increase the installed base in SOA-based developments and how a volunteer community can defray costs associated with SDI development. This open approach is then suggested as a potential model for motivating and governing a distributed, community-based SDI work-force.

We must therefore consider available resources for collecting, managing, sharing and using geospatial data as a basis for sustainable development, hence the concept of Spatial Data Infrastructure (SDI) that puts an emphasis on partnership and coordination to deliver geographic information to decision-makers and public at large in an easy-to-use format. This kind of application is increasingly necessary especially an inter-organi- zational environment which requires a high level of regional collaboration and in which all spatial data stake- holders (both users and producers) have to cooperate and utilize information and technologies in a cost-effec- tive way. However those infrastructures are currently underutilized especially in Africa due to a number of factors: poor awareness of decision makers, unavailability of spatial datasets and insufficient human and tech- nical resources. In this contribution, the aim is to design and set up a spatial data infrastructure for the ROSELT/ OSS (Long Term Ecological Monitoring in the Circum-Sahara of the Sahara and Sahel Observatory-OSS) in order to overcome inconsistencies in geographic data collection, lack of documentation, incompatibility of spatial datasets and to help centralize the management of the informational resources related to the program. This SDI is developed using a range of free and open source technologies and based on widely used open stan- dards.

The study highlights on the perception of geographic information system (GIS) and spatial data infrastructure (SDI) in the developing societies, which are societies that have developed less in the area of geographic information science and spatial data infrastructure. Analysis of the developments and achievements of the early and present GIS and SDI was carried out based on reviewing texts obtained from web services and published texts. Three geospatial community regions were analyzed which revealed a gap between the developed and developing GIS and SDIs. These gaps were noticed in the area of the terminologies used in the description of GIS and SDI. Standard components of SDI were also found lacking in the areas of access network, policy and technical standards, the issue of available experts were played down. These gaps exist as a result of so many factors, prominent among which are the issues of faulty approach to geographic information science, coupled with SDI models that could not fit into developing societies’ realistic needs. It also indicated that SDI is seen in most developing societies as an extension of GIS introduced into school curricula. A suggested model was developed for possible application in developing societies, which calls for studies in geographic information science as a step towards achieving an understanding of all inclusive GIS and SDI. Developing societies’ models should be specific to the peculiar problem at hand, standards should also be monitored and serve as a requirement for recognition by the regional SDI under the GSDI regulations.

Groundwater is a vital resource for sustaining socio-economic and ecological systems, especially at times of surface water scarcity [57]. In morocco, groundwater data need to be shared and to be made interoperable. In this context, a prototype of SDI has been developed for efficient management of groundwater data using OGC standards and open source technologies. It provides a platform for collecting, storing, and sharing monitoring groundwater data. The developed platform constitutes the linchpin of an ambitious project aiming at the design of a Spatial Data infrastructure SDI in Morocco dedicated to groundwater management. This application is pri- marily based on international standards (OGC and ISO). Data issue is from different databases (Postgre SQL, Badre 21, etc.). The application is connected to those data sources either by JDBC technology, or via WMS/ WFS. All document formats used are XML applications, in accordance with OGC standards (Get Capabilities, Get Map, etc.) as well as the W3C standards.

Nowadays, there is no doubt that spatial information plays a crucial role in the sustainable development of countries. It is one of the backbones of the e- government concept. Similarly, it is widely agreed that the most adequate framework to handle these spatial information on a national, regional or international level is the SDI concept. The term Spatial Data Infrastructure (SDI) has numerous definitions across countries, regions and disciplines. These definitions differ as considerably as do the stated objectives of the more than 120 SDI initiatives now underway across the globe, with varying degrees of success (Longhorn, 2004). This concept has been around for almost three decades and some 150 countries are at some stage of its implementations. However it seems that all of these experiences have known failure in some aspects. More information related to SDI is discussed in the literature review of Chapter 2.

Abstract. The expected global sea level rise by the year 2100 will determine adaptation of the whole coastal system and the land retreat of the shoreline. Future scenarios coupled with the improvement of mining technolo- gies will favour increased exploitation of sand deposits for nourishment, especially for urban beaches and sandy coasts with lowlands behind them. The objective of the work is to provide useful tools to support planning in the management of sand deposits located on the continental shelf of Western Sardinia (western Mediterranean Sea). The work has been realised through the integration of data and information collected during several projects. Available data consist of morpho-bathymetric data (multibeam) associated with morphoacoustic (backscatter) data, collected in the depth range − 25 to − 700 m. Extensive coverage of high-resolution seismic profiles (Chirp 3.5 kHz) has been acquired along the continental shelf. Also, surface sediment samples (Van Veen grab and box corer) and vibrocorers have been collected. These data allow mapping of the submerged sand deposits with the determination of their thickness and volume and their sedimentological characteristics. Furthermore, it is possi- ble to map the seabed geomorphological features of the continental shelf of Western Sardinia. All the available data (https://doi.org/10.1594/PANGAEA.895430) have been integrated and organised in a geodatabase imple- mented through a GIS and the software suite Geoinformation Enabling ToolkIT StarterKit ® (GET-IT), developed by researchers of the Italian National Research Council for RITMARE project. GET-IT facilitates the creation of distributed nodes of an interoperable spatial data infrastructure (SDI) and enables unskilled researchers from var- ious scientific domains to create their own Open Geospatial Consortium (OGC) standard services for distributing geospatial data, observations and metadata of sensors and data sets.

In Nepal, the digital cadastral data forms the basis for development of a land information system and local spatial data infrastructure. In Kathmandu Valley, the cadastral maps are geo- referenced with national geodetic framework. The Nepalese Government has initiated the computerisation of land records since 1993. In 2000, the Council of Ministers decided to establish a new department called the Department of Land Information and Archiving (DoLIA). The district wise development of land information system has begun. In resurveying, the informal settlement areas are mapped as a block parcel. Within that block some community members have prepared separate maps showing the occupancy of informal settlers though these maps remain in the informal domain. This information could be utilised to build a SDI for pro-poor management.

Abstract— Indonesia is a country with high disaster risk, entitled to ring of fire as one of the countries, which are surrounded by tectonic plates. The country has been exposed to natural hazards for decades. However, every time the natural hazard hits, the number of casualties remains huge. There is a serious question on how disaster management is going on in Indonesia and what knowledge could help to minimize or even prevent such huge casualties in any disaster occurrences. Big data can be a new approach towards natural disaster management mainly because it has the ability to visualize, analyze, and predict natural disasters. In the openly big data era, it is rather easy to process data with open-source software for managing the post-disaster as well as pre-disaster effect. The question remaining is how well the data is, which will be processed. This paper aims to appraise the quality of Indonesia's spatial data infrastructure using the R programming language in order to address natural disaster management and eventually lower the impact of the disaster. Some of the assessment criteria used in this paper are metadata of the data, positional accuracy, and completeness. The article concludes that Indonesia, as a country with high level of exposure to natural hazards, still lacks in NSDI quality, especially in providing disaster data. The most damaged buildings in Palu, with 2,416 damaged buildings affected. The sub- district of Nunu has the lowest number, with only 1 building damaged. The number of sub-districts with damaged buildings in Palu is 14 of the total 43 sub-districts.

With the increasing massive amounts of data available in different organization producing various types of data and the need to use and work with them by various users and consequently dealing with complex search mechanisms to achieve desired results, the need to design and create context-aware user interfaces proportional to working conditions and user environment is more tangible. In fact, the contextual conditions of user have a close relation with his information needs, and how servicing system to him is controlled based on contextual in- formation. Generally, in relation to search and optimum accessibility of users to the appropriate data in the geo- portal user interface of spatial data infrastructure many effective contexts also can be considered. The effective contexts help the user in providing the best results in the framework of spatial services of Geoportals.

Beyond the obligation to comply with technical guidance or organisational rules there must also be a will to extensively share (in a manner that is as versatile as possible) scientific outputs. This is a crucial point, as research scientists must wholeheartedly accept the handing of the results of their efforts to others with no guarantee of proper acknowledgement (it is expected that a wider diffusion increases the chances for improper use or citation: though scientists are accustomed to good practices this may not hold for the general public), nor a certitude that their output will be used the expected way. This conception of the scientific process is still being debated but gradually gains proponents as several works have shown the comparative advantages (Uhlir and Schröder, 2007, and Willinsky, 2005, amongst others) of unrestricted cooperation. It has come into an OECD (2007) recommendation to make the global scientific process more effective. Effectiveness must also encompass numerous alternative ways to process, display, explore and extract knowledge. A lot remains to be done in various domains: spatial representation, time-series exploration, analysis, modelling. A special attention should be drawn to UI for those (scientists, and whenever possible, the wider public) less conversant with technology or with a different background. These ideas are applied to environmental science with proof-of-concept implementations of and around the SDI GéoSAS. We are not considering the fields of linked data and the semantic web, though our approach must eventually converge with, and complement, them. In addition, our proposals only address the case of data, processes, models and services with spatial components, inputs, or outputs, which make up most of our production.

This paper describes a framework for 3D geospatial data infrastructure based on Open Geospatial Consortium (OGC) Standards in Iran, especially Tabriz, as one of the oldest cities with more than 3000 years of history. The external code lists based on local culture, vegetation and heritage landmarks were proposed for indexing 3D city structures, buildings, statues and city furniture of Tabriz. These code lists can be used between different governmental agencies as a communication tool and utilized for indexing in the 3D spatial Database (DB). There are some predefined code lists from Germany as the founder of City Geography Markup Language (CityGML), which can be utilized for Iranian context, along with some defined codes based on local cultures and structures. These code lists can be defined for all street furniture, sculptures, and facade textures in some applications such as city planning, built environment, disaster management, and so forth. The code lists can also be used for the components of the buildings, for instance, the facade of the building in different layers as an entity or multi-patch feature class or implicit geometry such as windows, doors, and backgrounds. In addition, the code list can be used to index city elements and enhance the use of 3D SDI for a variety of privileges from end-users to professionals in the near future for different organizations and management levels. The framework for web-based CityServer3D application has been discussed in this research paper. CityGML, as a standard data exchange format, has been utilized for developing 3D SDI for Iran, and implicit geometry representation has been used to avoid lagging while rendering the 3D models during navigation in the 3D virtual environment. The Implicit Geometry Representation (IGR) has been defined in CityGML as prototypic geometry which can be parameterized for multiple usages (Löwner et al., 2016) .

The second component of the research used an on-line questionnaire to investigate the motivations, capacity and effectiveness of local-state government data sharing partnerships from a local government perspective. The design of the questionnaire was constructed around an SDI framework to assess local government capacities and their appreciation of policies, data holdings, people, access arrangements and standards/technology. In addition to the SDI framework, the questionnaire also investigated the organisational setting, partnerships and collaborations and the participant’s perspectives on the existing partnership arrangements. A total of 110 responses were received including seven responses which were rejected as either incomplete or invalid. The remaining 103 valid returns represented a response rate for the survey of 56%. The data from the questionnaires was automatically collected into an excel spreadsheet via the web server. This process was extremely effective as it eliminated coding and transcription errors and facilitated direct transfer to the analysis software.

In analogy to seadikes, river dams are critical infrastructure and require continuous monitoring with various observations. Although safety monitoring systems are available at these structures, there remains a residual risk of failure. Potential damages associated with dams usually stem from the failure of the structure due to overtopping, seepage water flow, and deformation. A critical dam failure may claim lives and cause massive material damage. To further minimize the residual risk, measures from different sources must be combined and analysed to extract maximum information. In the research project TaMIS an already existing set of core SDI components has been complemented with additional spatial time series and analysis components to form a dam information system [48]. One of the core requirements and complementing modules of such a system is an eventing module that detects low level events, e.g. threshold violations or sensor failure and communicates detected events to a responsible person.

Chapters five and six detailed location quality analysis, semantic location extraction, credibility and relevance analysis of CSD. The purpose of this chapter is to discuss the findings of the research, in particular, the opportunities to integrate the research out- comes with authoritative data and to identify possible system automation methods. The CSD quality indicators, assessment and improvement methods were explored in pre- vious chapters. However, an automated mechanism for CSD quality management may also be required to make the data useful for stakeholders such as disaster first respond- ers. Therefore, in this chapter a framework is presented to automate the CSD quality management and to enable the information to be effectively integrated with authorita- tive data. SDIs are also rapidly evolving with the technological changes happening in this fast-moving world. These developments include changes in the technical, archi- tectural, policy and other dimensions of SDIs which are critical for maintaining the highest data quality, improved access and the smooth functioning of SDIs. Due to this dynamic environment, SDI-CSD coupling will be challenging. This chapter explores the opportunities, challenges and issues pertaining to authoritative data and CSD inte- gration.

The solution has already been used in massive GIS data creation and processing. The data created by this solution is being used for NOFN project of Govt. of India for connecting 2, 50,000 Gram Panchayat (GP) of rural India. Many e-services will be configured and used over the broadband network laid using the data created by our solution. Being a centralized approach based on our customized algorithms inspired by algorithms mentioned in [6], this solution is not only saving time but accuracy also has been increased to many fold. Since GIS is immerging field in India, many challenges with respect to accuracy of data are being faced by us, using this approach and solution minimizes rework. It is a “create once used many times” approach that is saving a lot of time and resources.

manages real-time sensor data and provides critical spatial analytics atop expert domain knowledge 121. provided in the system.[r]

Spatial Data Infrastructures (SDI) are a key component in the development of a Nation. There is a lot of economic potential that is locked away in Spatial Data holdings and this potential is realised by making the data widely available through a SDI (UNECA, 2001). Spatial Data Infrastructures help facilitate access to and effective use of geospatial data for decision making applications. By April 2005, 83 countries worldwide had established National Spatial Data Infrastructure (NSDI) Clearinghouses on the internet [4]. This development indicates the large extent to which nations are prioritizing and formalising NSDI initiatives. In Africa, SDI are being implemented, although in some instances they are given a different name [13]. Evidently there is a lagging behind of formal NSDI activity in Africa, although there is a lot of informal activity that will contribute to the formal NSDI once governments are fully willing to participate in and take ownership of NSDI initiatives. Examples of organisations that informally contribute to NSDI development in Africa are the Food Aid Organisation’s Somalia Water and Land Information Management (FAO SWALIM) [18] and Southern African Development Community (SADC) Regional Remote Sensing Unit [9]. The clearinghouses for these organisations can be viewed at the following URLs:

The first research specialist meeting on VGI was organised under the auspices of NCGIA, Los Alamos National Laboratory, the Army Research Office and The Vespucci Initiative and brought researchers from around the globe to discuss the potential of VGI for spatial information management. Coleman (2010) took a close look at how the concept of VGI fits within spatial data infrastructure (SDI). The utilisation of VGI for spatial information collection and updating is now widely used by OpenStreetMap, TeleAtlas, NAVTEQ and Google Maps. Government organisations have now also realised the power of VGI and crowd sourcing and are interested in utilising this technology for spatial data infrastructure development. U.S. Geological Survey was an early examiner of this technology. State governments in Victoria (Australia), and North-Rhine Westphalia (Germany) are two good examples of employing volunteered input to their mapping programs in the government sector (Coleman 2010). The Department of Sustainability and Environment (DSE) in Victoria employ notification and editing services (NES) to improve processes for notifying and updating changes to Victoria’s authoritative spatial datasets accommodating internal contributions of volunteered geographic information. The NES is available to state and local government organisations that already participate in data sharing and data maintenance programs within the DSE. With their volunteer inputs they can amend or update Victoria’s authoritative spatial datasets (Department of Sustainability and Environment Victoria 2012).