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Geographic Information Infrastructure
Applications | Technology | Right to Information The Essentiality of Geospatial Information Standardisation for Sustainable DevelopmentGeoportals contain metadata elements are designed to answer following questions (figure 1):
 fig.1 European Geoportal The United States Federal Geographic Data Committee (1994) defines The "National Geospatial Data Clearinghouse" as a distributed network of geospatial data producers, managers, and users linked electronically. A clearinghouse is commonly an application that is located on a network that is used by people who have access to the network to obtain copies of datasets that the datasets custodian has made available on the network. Essentially a clearinghouse allows a user to search a network to find out what data are located on it, and then to actually gain access to that data, subject to the constraints placed on it by the data’s custodian. Spatial Data Infrastructure Data that are collected for a particular project are, in most cases, useful for other projects. Thus there is a need for this type of data to be placed in databases and made accessible for others to use. Different kinds of geoprocessing systems – Geographic Information Systems (GIS) and systems for remote sensing, photogrammetry, automated mapping, CADD, and navigation - have not mixed well. Still, it remains difficult for a researcher or practitioner to efficiently access, retrieve and apply data of interest without considerable effort to search map storages or visiting multiple web sites or, conduct many different queries, download files, reconcile different vendor formats and bring all the data into the same Spatial Reference System so that the information can be used. Diverse collections of data relevant to sustainable development are stored at the local, national and international levels in different vendor formats, and are available via multiple web sites and portals. This is important, not only to the organisations looking for the data, but also for the organisations with the data. Due to the "commoditisation" of data, organisations can use the SDIs to attempt to recoup some of the production costs of the dataset by selling/trading/sharing it with other organisations. They also help to minimise the duplication and fragmentation of fundamental datasets that have already been captured at great expense (Mooney et al. 1997). In many areas data of useable quality does not exist and that even where data does exist its usefulness may be reduced by access restrictions or by lack of standardisation with other data sets. Many if not most, SDI initiatives around the globe, at national and regional level, recognise the importance of fundamental data in the implementation of the infrastructure. When a SDI is being developed, one of the biggest issues that has to be addressed is what to do with all the legacy data (data that are already in existence). Data should be in a form that is easily transferred from one proprietary data format to another. The second aspect of a SDI is to establish good communication channels between people/organisations concerned with spatial data (FGDC 1996).The third aspect of a SDI, which is brought about with the aid of good communication channels, is the introduction of common procedures and standards. By having standards for data storage etc. in SDIs, data can easily be shared amongst users and the best possible utilisation of the data can be achieved. Common standards within a SDI tend to solve many of the incompatibility problems for newly created data; however the legacy data will remain a problem.The goal is to create a framework of existing networks that leverage the important work that has already been accomplished by making it easier and quicker for a user to discover, combine and exploit existing data (Bacharach). Over time, many organisations and governments throughout the world have made major investments in collecting spatial data as a national resource that is fundamental to good decision-making. Managing this type of information, and maximising its use, has become a focus for both developed and undeveloped countries. Canada has developed the Canadian Geospatial Data Infrastructure, with funding of C$60 million over five years. (Canadian Geospatial Data Infrastructure 2006) This concept is established in Australia as ASDI to set up a distributed network of databases, managed by individual government and industry custodians (Australian Spatial Data Infrastructure 2006). The Permanent Committee on GIS Infrastructure for Asia and the Pacific (PCGIAP) has a vision for an Asia-Pacific Spatial Data Infrastructure (APSDI) that is a network of databases, located throughout the region to provide the fundamental data needed by the region. In United States the Federal Geographic Data Committee (FGDC 1996) defined a SDI as an umbrella of policies, standards, and procedures and delineated these major initiatives to develop a National Spatial Data Infrastructure (NSDI) which is accessible through the National Spatial Data Clearinghouse:
The NSDI has come to be seen as the technology, policies, criteria, standards and people to assemble geographic data nationwide to serve a variety of users in public and private sector applications of geospatial data in such areas as transportation, community development, agriculture, emergency response, environmental management and information technology. Ultimately this framework will illustrate the best practices promoted by the Global Spatial Data Infrastructure. The definition of the GSDI was adopted at the 2nd GSDI Conference in 1997.The purpose of the GSDI is to encourage the growth of compatible Spatial Data Infrastructures capable of supporting collaboration on regional and global issues of importance. In addition, it provides practical guidelines on how to establish spatial infrastructures. GSDI is also working closely with the United Nations Geographic Information Working Group (UNGIWG). This working group that was established for the needs of peacekeeping actions, sustainable development and the eradication of poverty, collaborate with ISO/TC 211 and use standards it has developed. The potential realisation of a GSDI has captured the imagination and attention of policy-makers, administrators, industry, and the professions. Although not widely known in the general community or commonly understood by its proponents the GSDI is seen by many as a central element in the global response to the challenge of sustainable development (Holland 1999). In 1992 the Japanese Ministry of Construction proposed Global Map product concept to deliver basic topographic and thematic data sets globally. The Spatial Data Transfer Standard The Spatial Data Transfer Standard (SDTS) is an intermediate transfer format for the transfer of spatial data. Figure 2 is a simple example of a spatial data transfer processors (SDTP) encoding spatial data from an Arc/Info format into an SDTS profile and then a separate SDTP decodes the spatial data in the profile into an INGRES format.  Fig.2. SDTS encoding and decoding Digital geographic data is an attempt to model and describe the real world for use in computer analysis and graphic display of information. Any description of reality is always an abstraction. There is seldom perfect, complete, and correct data. To ensure that data is not misused, the assumptions and limitations affecting the creation of data must be fully documented. The objective of International Standard is to provide a structure for describing digital geographic data. Though this International Standard is applicable to digital data, its principles can be extended to many other forms of geographic data such as maps, charts, and textual documents as well as non-geographic data. The geospatial standard defines the schema required for describing geographic information and services. It provides information about the identification, the extent, the quality, the spatial and temporal schema, spatial reference, and distribution of digital geographic data mandatory and conditional metadata sections, metadata entities, and metadata elements and a method for extending metadata to fit specialised needs. By focusing on the adoption of standards-based geographic information and technology offerings now, sustainable development researchers and practitioners in the field and at the national and international support levels will be better able to share information, interconnect applications, and minimise system integration issues as the range of product offerings increases and as access to the internet expands. A standard is a code of practice for procedures to create, store transfer or use data. This is to ensure that when information is generated in one system its quality is still the same when used in another system. The success of different data formats has largely been governed by the size of the user community using that standard and the ease with which the standard can actually be implemented. For example, the standards devised by the FGDC have been adopted both within the USA and by a wider global audience. This global influence can at least in part be attributed to the impact of the large US GIS companies. GI standards can have three different implementations: a Generic view, a Profile view, or a Product view (Fadaie et al. 2004).These standards may specify, for geographic information, methods, tools and services for data management (including definition and description), acquiring, processing, analysing, accessing, presenting and transferring such data in digital / electronic form between different users, systems and locations. It is evident that the potential of geographic information can be achieved only with clear and well-defined data definitions (Stiggelbout, 1999). There are two strands of thought present in the discussion of data standards. One is largely about the fact that many of the factors affecting data quality operate at the user end of the GIS system. Another strand of thought more closely associated with various national and international organizations to define specifications. Thus the quality can be best managed by standards to establish principles and ensure compatibility and users to implement them. Jingtong (2001) describes different points of view among experts and among organizations have to be hardly coordinated. If strategies were designed solely for and by specific users, then we would have, for instance, different data formats that would not help improve the implementation of quality controls. Compatibility and credibility require standards. The main beneficiaries of data standards are users. They need standards to:
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