World Bank SDI Report - GIS and Spatial Data Infrastructures

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This article is a part of World Bank SDI Report.


Basic Concepts

Spatial Data/Geographic Information; Why Location is Important

Many decisions people make in their day-to-day lives are based on geographic information. People decide where they wish to go for their vacation; where in the city to live; which route to take when driving to a place. In all these situations, people use the geographic position together with information on the location and its immediate surroundings to make their decisions. Likewise, governments and commercial organisations need location-based data as an aid to defining strategies, carrying-out their operational roles and in monitoring the effectiveness of policies. The linking of location to other information about events, activities, people, features, natural phenomena etc. is the basis for Geographic Information Systems (GIS). Spatial data infrastructures (SDI) add value to GIS by providing the necessary environment for data discovery, ready access, harmonisation and sharing of geographic information and by providing the policy, licensing and charging framework within which location based data is managed[1].

Geographical information Systems (GIS)

We need geographic information to position, describe the physical extent and define the spatial relationships of natural and man-made phenomenon on the surface of the earth and their relationship to people and human activity. At a basic level, geographic data comprises location (where is it?), descriptive or attribute information (what is it?) and spatial relationships (how does it relate (spatially) to? Geospatial data will vary over time and therefore the time dimension is also an essential dimension in GIS. The term "spatio-temporal" is used to reflect the time dimension for example in geospatial modelling.

Knowledge of the location and the extent of features enable distances to be measured, directions to be given, areas to be calculated. It allows ownership to be associated with locations, allows the distribution and flows of people and materials to be better understood. It provides an understanding of the terrain and a basis for planning and managing a wide range of governmental and commercial activities from national security to optimal routing of communication routes to the planning of environmental policies. It allows maps to be made. In short, it is vital for sound decision making and economic development. Also, the knowledge of the location of an activity allows it to be linked to other activities or features that occur in the same or nearby locations which may provide insights on trends and relationships between activities. This modelling and analysis of geographic data within a geographic information system (GIS) has become a powerful tool in understanding, planning and managing the world we live in.

What then constitutes a GIS? A GIS is a hybrid concept incorporating elements from many disciplines including computer science, geography, cartography, and remote sensing. Today, many more fields of knowledge such as natural sciences, economics etc. have contributed to the technology making it an even more powerful tool for decision making. But what really is GIS?

According to ESRI, a leading company in GIS software solutions, a GIS integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. The US Geological Survey provides a similar definition but expands it by including the procedures, operating personnel, and spatial data that go into the system as part of a GIS.

While other database systems may offer similar functions of capturing, managing, analyzing data etc, one element that distinguishes GIS from such systems is that it is focused on spatial data. Attribute information such as demographic data must be geo-referenced (given a location connection) before it can be used in a GIS. That almost all information can be geo-referenced to improve understanding and analytical power was one of the key drivers towards the development of the GIS technology.

The power of GIS lies in its integration capabilities. GIS allows disparate data sets from various sources to be brought together in a single system thereby offering a consistent framework for modelling and analyzing geographical data. In this way it reveals relationships, connections, and patterns that are not necessarily obvious in any one data set and enhances the ability to predict how things will develop, enabling organizations to make better decisions.

Today, GIS is being used in virtually all sectors of development and is helping thousands of organizations and individuals answer the what, where, when, why or "what if" questions of their businesses[2].

Case Study example of application of GIS at the national level:

To illustrate the wide application of GI data and GIS, the example of GIS application in Korea can be considered. The text below is a summary of Annex A.

In Korea, GIS is widely adopted by both the Government (at national and local levels) and the private sector. Government areas of use include land use, agriculture, rural development, marine resources and security. In the private sector, innovative application areas include health, financial management, insurance, marketing and customer management. Moreover, mobile GIS applications for navigation and internet searching based on existing map data are common.

To avoid waste through duplicate investment, several of the more advanced application systems, such as for Underground Facilities Management, Land Information and 3D GIS, have been developed by the central government and made available for local governments to use and manage. This approach also encourages the wider use of GIS applications. More locally specific GIS applications e.g. for tourist activities have been developed by local governments. Tables 2.1 and 2.2 show the GIS applications that have been developed by Korean central and local government respectively.

In the private sector, Korean portal vendors, provide a widening range of map services. Non-native Korean suppliers (e.g. Microsoft and Google) also provide services in Korea but are not as predominant in the Korean geospatial market as in say, European countries. Korean domestic vendors which have high resolution data based on aerial photography, supplemented by street view data, have data superiority. Due to the Korean data security policy, the full vector coverage of the whole country is not open to foreign vendors and this may be a reason that the Korean market remains less attractive to overseas investors. Competition in the GIS market is strong especially in Neighbourhood GIS applications such as searching for restaurants, hospitals and locations with many visitors. With the growth of location based services, location responsive customer relationship management and ubiquitous mobile services many more new and novel GIS applications are expected. See Table 2.1.

Domains National Government Agencies in the Public Sector Applications
Environment ME(Ministry of Environment) Environmental GIS[3]
Agriculture MIFAFF(Ministry for Food, Agriculture, Forestry and Fisheries), Rural Development Administration Agriculture GIS
Forest Korea Forest Service Forest GIS[4]
Marine MLTM (Ministry of Land, Transport and Maritime Affairs) Marine GIS
Utilities MLTM Underground Facilities GIS
Water MLTM Underground Water GIS
Cultures Cultural Heritage Administration of Korea Cultural Heritage GIS[5]
Statistics Statistics Korea SGIS[6]
Military MND(Ministry of National Defense) Military GIS
Education MEST(Ministry of Education, Science and Technology) Educational GIS

Table 2.1: Korean GIS Applications

(Source: MLTM, 2008, "The Study on Evaluation of NGIS Project and Action Plan,"p57)

Domain Local Government Application URL
Metropolitan city level
Daegu Bus information system
Neighbor GIS system
Address information system
  Seoul Urban Planning Information System  
  Busan Lifemap System
  Gwangju Bus information system
Neighbor GIS system
City, Gu/Gun
Gwacheon Address information system
  Gunsan Gunsan Neighbor GIS system
  Gunpo Water GIS system  
  Gangdong-gu Gangdong life map
  Gangnam-gu Gangnam-gu GIS

Table 2.2 Selected GIS Applications at the local level

Service name vendor URL
Wooricy Sundosoft Co.Ltd
CyberCT CyberCT
Empas map Empas
Superpagemap KTH
Cybermap world Cybermap world Co.Ltd
Wholsee Mandoma&Soft Co.Ltd.
Paran map KTH
Daum city map Daum communications Co.Ltd
Yahoomap (gugi) Yahoo Korea
Navermap NHN Co.Ltd
Congnamul Twinklelittlestar Co.Ltd

Table 2.3: Selected Korean Neighbourhood GIS Map services in the private sector

Spatial Data Infrastructures (SDI)

Given the potential benefits, investment in GIS systems and technology has grown rapidly. However, the nature of legacy surveying and mapping activity and organisation, which was focussed on the production of hard copy maps and charts and also the non-standardised nature of early GIS technology, has resulted in a lack of compatibility between systems. Data sets are frequently collected using different criteria; different classification methods are adopted and differing data models and formats used. Duplication in expensive data capture frequently occurs and the cost of harmonisation for any given project may be prohibitive even when access to the skilled personnel needed to achieve this harmonisation is available. This situation is exacerbated by the lack of common policies within governments for the publishing, release, distribution, licensing and charging of spatial data and the derived products. It is to address these issues and unlock the full potential of location based data and GIS that SDI programmes are needed.

The term "Spatial Data Infrastructure" (SDI) is used to describe the relevant base collection of technologies, policies and institutional arrangements that facilitate the discovery of and access to harmonised spatial data. The SDI provides a basis for data discovery, evaluation, and application for users and providers within all levels of government, the commercial sector, the non-profit sector, academia and citizens in general. From this definition the main emphasis of SDI is achieving interoperability of the various spatial data held by various stakeholders, facilitating access to this data and the provision of a harmonised environment in which resulting geographic information and intelligence may be applied to programmes and activities.

The GSDI Cookbook (Nebert, 2004[7]) describes the term Spatial Data Infrastructure (SDI) as "the relevant base collection of technologies, policies and institutional arrangements that facilitate the availability of, and access to, spatial data"[8]. Rajabifard (2002[9]) describes SDI as an enabling platform based on a dynamic, hierarchic concept with the aim of facilitating and coordinating the exchange and sharing of spatial information between different stakeholders. A definition used by the U.S. Federal Government includes the technologies, policies, standards, human resources, and related activities necessary to acquire, process, distribute, use, maintain, and preserve spatial data[10]. SDI includes applications, standards, technology and the institutional governance necessary for effective and efficient spatial data and services management within and across organizations. The concept of SDI is different within various contexts of political, social, administrative and technical environments; however, its ultimate objectives are to promote economic development, stimulate better government and foster environmental sustainability (Masser, 1998[11]).

SDIs provide the framework for optimization of the creation, maintenance and distribution of geographic information at different organizational levels (e.g. regional, national, global) and involves both public and private institutions. SDI is fundamentally about the facilitation and coordination of the exchange and sharing of spatial data, services and other resources between stakeholders. From a technical perspective, in order to facilitate access to, and exploitation of, spatial data, SDIs must establish standards and enable services to be reused by their community of users in the construction of different applications and value-added services. Thus, SDI enables users to save resources, time and effort by avoiding duplication of efforts related to information collection, maintenance and integration (Chan et al., 2001[12]).

Components of SDI

The Global Spatial Data Infrastructure Association's (GSDI) 2006 newsletter proposed that SDIs would include all or a combination of the following elements:

  • Geographic data – the actual digital geographic data and information;
  • Metadata – the data describing the data (content, quality, condition, location, disclosure or confidentiality issues, etc.), which supports structured searches, comparison of data and inter-operability;
  • Framework – including mechanisms for identifying and sharing the data features, attributes, and attribute values, and mechanisms for updating the data without complete re-collection;
  • Services – to help discover and interact with the data;
  • Clearinghouse – to actually obtain the data in uniform, distributed searches through a single user interface;
  • Standards – created and accepted at local, national, or global levels;
  • Partnerships – relationships and agreements across relevant actors and organizations that reduce duplication and collection costs and leverage local, national and global technology and skills; and
  • Education and Communication – allowing individual citizens, scientists, administrators, private companies, government agencies, nongovernmental organizations, and academic institutions to communicate and learn from each other.

These elements are demonstrated more graphically in Figure 2.1.

Figure 2.1: NSDI Components (in the Korean context)Source: MLTM (2010)[13]

SDI Hierarchy

An SDI hierarchy is made up of inter-connected SDIs at corporate, local, state/provincial, national, regional (multi-national) and global levels (see Figure 2.2). Rajabifard et al. (2002[14]) state that an SDI hierarchy creates an environment in which decision-makers working at any level can draw on data from other levels. The themes, scales, currency and coverage of the data required depend on which level of the SDI hierarchy one is working.

In the SDI hierarchy, the SDI at a national level typically has a significant role, in building SDI at other levels. Figure 2.3 shows a South Korean SDI hierarchy which illustrates the different levels of SDI data, standards (for data and application), and other SDI components interconnected vertically and horizontally. An example of vertical interconnection is for spatial data e.g. the topological map, which is integrated across all levels. GIS Applications at a national level are also mapped with those at a local level. Horizontally, at any level each of the 6 SDI components is interrelated. In this model, both vertical and horizontal partnerships are essential aspects of the SDI hierarchy.

Figure 2.2: SDI hierarchy. Source: Rajabifard (2002)[15]
Figure 2.3: Korean SDI hierarchy. Source: MLTM (2009)[16]

Evolution of SDI

van Loenen et al. (2009) observed that the focus of SDIs has moved from a data orientation in the 1990s to a process orientation in the late 1990s-2005 towards the current service-oriented SDIs exemplified by the INSPIRE directive in Europe and the spatially enabling government initiative in Australia[17].

As summarized by Masser (2005[18]), current trends in SDI development are as follows:

  • From a product to a process model,
  • From formulation to implementation
  • From data producers to data users
  • From database creation to data sharing
  • From centralised to decentralised structures
  • From coordination to governance
  • From single to multilevel participation
  • From existing to new organisational structures

With developments in modern consumer technology a trend of user-created geospatial content (the terms crowd-sourced and Volunteered Geographic Information (VGI) are also used) is now emerging (Goodchild[19]). These technology developments include wider access to the Internet, positioning from GPS-enabled mobile phones and easy to use application programming interfaces (API's) for mapping software. These developments enable huge numbers of people to add geospatial content to on-line web services. Open Street Map is a good example of VGI[20].

User-created data as a complement to authoritative data represents a major opportunity. For example, the USGS National Map Corps[21] program uses VGI to guide official authoritative information collection (see also, Du et al 2011 for research on conflating authoritative and crowd-sourced data[22]). VGI fits the broader model of NSDI as a collection of individuals acting independently and responding to the needs of local communities can together generate useful data. With a server, software and tools to remove significant inconsistencies the various VGI contributions can be conflated and used for wider benefit. The accuracy and currency of each contribution may vary but still be useful to address local needs and guide wider area programmes[23]. As such, it can be a valuable source of "citizen-relevant" spatial data and offers potential for SDIs in developing countries[24].

What makes up a Spatial Data Infrastructure?

Whilst definitions of SDI tend to vary in emphasis there is a strong consensus on what the major building blocks are. The text, below, describes in more detail each of these core SDI components.

Policy Framework and Legislation

The importance of developing a supportive policy and organizational environment for SDI is critical. Potential stakeholders will only become active participants if they see advantages for their organizations and if they do not feel threatened by the infrastructure. This policy/organization environment will vary from country to country and will need to be worked out closely with the stakeholders. The buy-in and commitment from senior management of all stakeholders is critical to the success of the infrastructure as a whole and to that of the access element in particular. The Canadian Geospatial Data Infrastructure[25] is an example of an infrastructure implementation that has developed an organization based on broad stakeholder participation.

Some of the issues that need to be considered in the development of the policy/organizational environment are:

  • Distributed/autonomous suppliers.
  • The management of the data should be done as close as possible to source. This helps ensure the accuracy and quality of the data.
  • Commercial and government stakeholders need to feel comfortable as active participants in the infrastructure. They should not feel threatened by infrastructure business models or policies.
  • The access component of the infrastructure must provide multiple levels of buy-in. This enables stakeholders to choose a level of participation that best meets their business and operational objectives. This is especially important in the early stages as many stakeholders will want to "try" it out and may not be prepared to expend much effort until they see how it works.
  • Sustainable long term business models.


Metadata is the term used to describe the summary information or characteristics of data, software or services. This definition includes a wide spectrum of possibilities ranging from human-generated textual description to machine-generated data that may be useful to software applications.

A map legend is one representation of metadata, containing information about the publisher of the map, the publication date, the type of map, a description of the map, spatial references, the map's scale and its accuracy, among other things. Such metadata is equally important as descriptive information applied to a digital geospatial file or a software application.

Metadata should give an indication of whether the data is relevant, comprehensive, timely, and accurate. Metadata - "data about data" - can be compared to an old library card catalogue that describes key information about the books on the shelves such as where to find them, title, subject, author among others.

Whilst the value of geospatial data is recognised by both government and society, its effective use is inhibited by poor knowledge of the existence of data, poorly documented information about the data sets, and data inconsistencies. Once created, geospatial data has the potential to be used by multiple software systems and for multiple purposes. Metadata is therefore an essential requirement for locating and evaluating available data. It can also benefit the primary creator of the data by maintaining the relevancy of the data and assuring its continued use over time. Today's geospatial data will be relevant well in to the future to study climate change, ecosystems, and other natural processes. Metadata standards will increase the value of such data by facilitating data sharing through time and space. Investing a small amount of time and resources at the beginning of a project can pay significant dividends in the future.

Metadata, therefore, helps us locate, extract, evaluate and combine available data sets. It improves the use and interoperability of data sets, contributes to efficient planning and execution of new data capture and reduces future costs.

Organising and making metadata available is a very cost-effective measure to start the process of building a Spatial Data Infrastructure.

Good practise therefore demands that geospatial data producers should provide metadata for each dataset and dataset update that they produce. The metadata provided should conform to national and international standards (see ISO Metadata standard 19115). The metadata content should include the following minimum information:

  • Data quality (positional accuracy, attribute accuracy, temporal accuracy, lineage, completeness and logical consistency)
  • Geospatial data organization
  • Spatial reference (coordinate system, datum, map projection)
  • Identification information (name of data, geographic coverage)
  • Entity/attribute information (formats, type, measurement units)
  • Distribution information (distributor, format, access protocol, procedure)
  • Collection (and update) date
  • Name of data custodian
  • Brief text description of the data
  • Key words regarding content/type.

Network Services and Technology

<<text still needed>>


A Clearinghouse is a repository structure, physical or virtual, that collects, stores, and disseminates information, metadata, and data. A Clearinghouse provides widespread access to information and is generally thought of as reaching or existing outside organizational boundaries. It incorporates the data discovery and distribution components of a spatial data infrastructure (see Figure 2.1 for reference). The Clearinghouse will ensure; maximum benefits of data sharing, minimum duplication of effort in data acquisition and provide 'one-stop' access for geospatial data information.


Text still needed – to cover the OGC and ISO TC211

Organisational and Institutional Arrangements

The organizational approach focuses on the positions/actors involved in the creation, publication and discovery and use of spatial information. It defines roles and responsibilities and states the essential functions. At the general level stakeholders will typically include:

  • National mapping and charting agencies (NMCA's): NMCA's play a key role in ensuring availability of accurate and maintained geospatial framework data. Such data are, for example, key to the promotion of sustainable economic development, improvement of environmental quality, resource management, upgrading public health and safety, modernization of governments, and the responses to natural and other disasters.
  • Industry: Industry provides technology, data and services in support of SDI activities as well as being a user of SDI and their engagement with NSDI strategy is therefore critical. In particular, industry plays a key role in ensuring that effective information technologies (consistent with standards and specifications being developed) exist and that these technologies support the NSDI requirements.
  • Other Government Ministries, agencies, organizations and institutions: There are many other parts of central and local government, agencies, organizations and institutions that collect and use geospatial data that, together with NMCA's and industry, have an important role in SDI activities. It is important that ways be sought to encourage cooperation, collaboration and communication among as many SDI stakeholders as possible.
  • International, Quasi-governmental and Non-Governmental Organisations: Such organisations will frequently play a role in research and the provision of services as well as collecting relevant spatially referenced data. As such they will be both important contributors to and uses of an NSDI.
  • Citizens: Citizens have often been seen as the passive recipients of NSDI generated programmes and services but with the development of VGI programmes and Public Participatory GIS services enabled through Web2 technologies and modern mobile communications and Internet the citizen should now be seen as a potential contributor to SDI as well as an engaged recipient of the services that SDI facilitate.



An SDI needs a marketing and promotion plan to build up the level of awareness and participation and to develop momentum. It is important to get a critical mass of participants/users so that the benefits of supporting the NSDI are clear.

Access Issues

Together organizations spend billions of dollars each year producing and using geographic data Nebert (2004[26]) but there is still a paucity of data for many critical applications. There are several aspects to this problem as discussed below:

  • Most organizations need more data than they can afford.
  • Some organizations cannot afford to collect base information at all.
  • Organizations often need data outside their jurisdictions or operational areas. They do not collect these data themselves, but other organizations do.
  • Frequently, large amounts of money are spent on basic geographic data, leaving little for applications data and development
  • Data collected by different organizations are often incompatible due to differences in scale and coordinate systems. The data may cover the same geographic area but use different geographic bases and standards. Information needed to solve cross-jurisdictional problems is often unavailable.
  • Many of the resources organizations spend on geographic information systems (GIS) go toward duplicating other organizations' data collection efforts. The same geographic data themes for an area are collected again and again, at great expense.

Framework initiatives will greatly improve this situation by leveraging individual geographic data efforts so data can be exchanged at reasonable cost by government, commercial, and nongovernmental contributors. It provides basic geographic data in a common encoding and makes them discoverable through a catalogue in which anyone can participate. Using Web mapping and advanced, distributed GIS technology in the future, users can perform cross-jurisdictional and cross-organizational analyses and operations, and organizations can funnel their resources into applications, rather than duplicating data production efforts.

Resource Needs and Funding


Benefits of a Spatial Data Infrastructure


Development Challenges

Cost / Benefit Studies

Policy Making

Policy Implementation and 'day to day' Services Delivery

Monitoring and Review

Resource Allocation and Use

Organisational/Institutional Integration (joined-up government)

Private Sector and Civil Society

Consequences of a lack of SDI

Some Practical Examples

Spatial Data Infrastructure and Millennium Development Goals (MDG): What is the Link?

The Role of GIS and SDI in Monitoring Development Outcomes

Meeting the objectives of the MDG and reducing global poverty is a multidimensional challenge. Poverty is reflected in low income, low food consumption, ill health, reduced life expectancy, poor education, lack of assets, limited access to natural resources, low social status, lack of political voice. Tackling these issues and monitoring and evaluating progress requires a multidisciplinary response (Durand-Lasserve, 2006; Akinyemi, 2008[27]). Given that all of the eight Goals have a spatial dimension in one form or another, the use of GIS within an SDI is needed to assist in addressing the issues targeted by the MDGs and working to achieve them.

Measurement is at the core of the monitoring and evaluation component of the results-based management methodology. The eight goals encompass twenty-one quantifiable targets which define the desired outcome. Progress towards those targets and, by extension, the goals themselves, is measured through 60 indicators[28]. Geospatial data in its myriad forms figures centrally in the measurement of these indicators.

As the international donor community has increasingly embraced results-based management approaches to development aid, the monitoring and evaluation of development outcomes has come to the fore most notably in the form of the MDGs. SDIs are an enabler of results-based management, both towards the design of interventions and towards tracking change and progress resulting from on-the-ground programs. Not only is the infrastructure of GI and GIS more rigorously leveraged for targeting interventions but SDIs also figure centrally in the continuous monitoring and evaluation of the efficacy of development programs. SDIs enable and underpin both operational tools in the design and fielding of development projects and the more strategic monitoring and evaluation tools to measure social and economic progress (or "development aid ROI") stemming from those interventions.

Concluding Comments

The implementation of SDIs brings many benefits. Among the salient ones are:

  • The provision of timely access to reliable, consistent and harmonised geospatial data to support sound decision making by local, regional and national governments.
  •  The minimization of the waste of resources on duplicate activity through institutions collaborating on policy issues and sharing spatial data.
  • The maximization of dataset integration due to use of common standards.
  • The improvement of the quality of information and services offered by government agencies and private sector due to the collective participation of many stakeholders


  7. Nebert, D. D., Ed. (2004). Developing Spatial Data Infrastructures: The SDI Cookbook, GSDI-Technical Working Group. Available at
  9. Rajabifard, A., M. E. F. Feeney and I. P. Williamson, 2002, ‘Directions for the Future of SDI Development’, International Journal of Applied Earth Observation and Geoinformation, 4, 11-22
  11. Masser, I. (1998). The first generation of national geographic information strategies Selected Conference Papers of the Third Global Spatial Data Infrastructure Conference, Canberra, Australia.
  12. Chan, T. O., M. E. F. Feeney, et al. (2001). "The Dynamic Nature of Spatial Data Infrastructures: A Method of Descriptive Classification." Geomatica Journal 55(1): 65-72.
  13. MLTM, (2010), The 4th-phase National GIS Comprehensive implementation plan (2010-2015)
  14. Rajabifard, A., M. E. F. Feeney and I. P. Williamson, 2002, ‘Directions for the Future of SDI Development’, International Journal of Applied Earth Observation and Geoinformation, 4, 11-22
  15. Ibid.
  16. Unwin, T., Ed. (2009). ICT4D: Information and Communication Technology for Development, . Cambridge, Cambridge University Press.
  17. B. van Loenen, (ed), “SDI Convergence; Research, Emerging Trends, and Critical Assessment”, 2009
  18. Masser, I. (2005). GIS Worlds: Creating Spatial Data Infrastructures. Redlands, ESRI Press.
  19. Michael F. Goodchild, “Citizens as sensors: the world of volunteered geography”, 2007, NCGIA VGI Workshop
  20. As the free wiki world map, OpenStreetMap creates and provides free geographic data such as street maps to anyone who wants them.
  21. The National Map Corps' Web-based data collection procedure presents an opportunity for private citizens to contribute specific geographic knowledge to the USGS's mapping program. By completing a simple registration procedure, volunteers can immediately collect data and provide the location and name of important map-worthy features in their community.
  22. Du, H., Jiang, W., Anand, S., Morley, J., Hart, G., Leibovici, D. and Jackson, M. J. (2011). “An Ontology Based Approach for Geospatial Data Integration of Authoritative and Crowd Sourced Datasets”, Proc. 25th International Cartographic Association, 3-8 July, 2011, Paris, France.
  23. Michael F. Goodchild (2007)
  24. In South Korea, during the completion of the 3rd phase of the NGIS project, most of trends mentioned were founded. For example, in the 1st phase of NGIS, more concerns were on data creation and production of datasets such as digital topological maps and various thematic maps, later in the 2nd and 3rd phases more efforts on data sharing were made. For future SDI evolution toward the knowledge/information society, Korean NSDI policies and programmes will be transformed as suggested in “The 4th-phase National GIS Comprehensive implementation plan (2010-2015).
  27. Durand-Lasserve, A. (2006). "Informal settlements and the Millennium Development Goals: global policy debates on property ownership and security of tenure " Global Urban Development 2(1): 1-15.
    , Akinyemi, F. O. (2008). "In support the of the Millennium Development Goals: GIS use for poverty reduction tasks." International Archives of the Photgrammetry, Remote Sensing and Spatial Information Sciences 37(B7): 1331-1335.
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