International and national spatial data infrastructures (SDI) презентация

Theme 1. INTRODUCTION TO THE DISCIPLINE
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The goal of the academic discipline is to form students' requisite knowledge, skills and expertise on an application of methodological bases and technological-organizational approaches for development of international and national Spatial Data Infrastructures (SDI) as technologies, policies, standards, and human resources necessary to acquire, process, store, distribute, and improve utilization of spatial data.
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As a result of academic discipline study, students are obliged:
1) To know:
a) General principles and approaches to SDI development;
b) Technology of spatial data development for SDI;
c) Technology of metadata development for SDI;
d) Technology of Spatial Data Catalogues' development;
e) Technology of spatial data visualization for SDI;
f) Technology of open spatial access in SDI;
g) Technologies of different SDI services;
h) Approaches to outreach and capacity building of SDI;
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2) To be able to:
a) Define the factors for an effective SDI organization;
b) Set interoperable levels of SDI;
c) Implement necessary approaches for spatial data development concerning SDI;
d) Determine linkages between spatial data and metadata in SDI;
e) Specify the usage of Distributed Spatial Data Catalog Services;
f) Operate with Web Mapping Service (WMS) Interfaces;
g) Provide the open spatial access in SDI;
h) Use different SDI services;
i) Provide SDI outreach and capacity building taking into consideration international environmental cooperation.
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1.1. SDI development preconditions
1. At the United Nations Conference on Environment and Development in Rio de Janeiro in 1992, a major resolution was passed to focus on reversing the impacts caused by environmental deterioration.
2. The Agenda 21 resolution establishes measures to address deforestation, pollution, depletion of fish stocks, toxic wastes etc.
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3. The importance of geographic information to support decision-making and management of these growing national, regional, and global issues was cited as critical:
– At the 1992 Rio Summit;
– By a special session of the United Nations General Assembly assembled in 1997 to appraise the implementation of the Agenda 21.
4. A landmark effort was made to illustrate the capabilities, benefits, and possibilities of using online digital geographic information for sustainable development:
– at the World Summit on Sustainable Development in Johannesburg, South Africa in 2003.
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Notes.
1. Geographic information – facts that are obtained and/or can be obtained as a result of spatial data operating.
2. Spatial data (syn. geospatial data, geographic data, georeferenced data, geodata) – data concerning spatial features, which are a combination of such data two components:
– position(al) data;
– attributive (nonpositional) data;
– both of which, including conjointly, has a time dimension also.
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3. Spatial features – spatial components of real world, which are presented in computerized (digital) form in order to display geographic objects, processes and phenomenon and are divided into four principal initial types:
1) Point features (points);
2) Line features (lines);
3) Polygon (area) features (polygons);
4) Volumetric features (surfaces).
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5. Geographic information is vital to making sound decisions at the local, regional, and global levels.
6. Crime management, business development, flood mitigation, environmental restoration, community land use assessments and disaster recovery are just a few examples of areas in which decision-makers are benefiting:
– From geographic information;
– Together with the associated infrastructures (i.e. Spatial Data Infrastructure or SDI) that support:
a) Information discovery;
b) Information access;
c) Use of this information in the decision-making process.
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7. However:
1) Information is an expensive resource;
2) For this reason appropriate information and the resources to fully utilize this information may not always be readily available, particularly in the developing world.
8. Many national, regional, and international programs and projects are working to:
– Improve access to available spatial data:
– Promote its reuse;
– Ensure that additional investment in spatial information collection and management results in an ever-growing, readily available and useable pool of spatial information.
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9. This is true of many initiatives even if they are not actually labeled as “SDI initiatives”:
– An example of this is the Environment Information System Program in sub-Saharan Africa (EIS-SSA);
– An emphasis on harmonizing standards for spatial data capture and exchange, the coordination of data collection and maintenance activities and the use of common data sets by different agencies may also feature in such initiatives, although these activities by themselves do not constitute a formal SDI.
10. In regions characterized by an availability of geographic information, in combination with the power of GIS, decision support tools, data bases, and the World Wide Web and their associated interoperability, the way of solving for critical social, environmental, and economic problems is changing rapidly.
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Note. Interoperability:
1) (in the informatization scope) a capability to communicate, execute programs, or transfer data among various functional units of information systems in a manner that requires the user to have little or no knowledge of the unique characteristics of those units;
2) (in general) a property referring to the ability of diverse systems and organizations to work together (inter-operate).
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11. However:
1) Even in the new era of networked computers, the social habits of the past continue to prohibit users from finding and using critical geographic information;
2) This can lead to:
– Either the abandoning of a proposed project;
– Or to unnecessary (and expensive) recapture of existing geographic information;
– In many agencies there is still the lost opportunity to reuse incidental digital geographic information collected for other purposes.
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12. There is a clear need, at all scales, to be able to access, integrate and use spatial data from disparate sources in guiding decision making.
13. Our ability then, to make sound decisions collectively at the local, regional, and global levels, is dependent on the implementation of SDI that provides for compatibility across jurisdictions that promotes data access and use.
14. Only through common conventions and technical agreements will it be easily possible for local communities, nations and regional decision-makers to discover, acquire, exploit and share geographic information vital to the decision process.
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15. The use of common conventions and technical agreements also makes sound economic sense by:
– Limiting the cost involved in the integration of information from various sources;
– Eliminating the need for parallel and costly development of tools for discovering, exchanging and exploiting spatial data.
16. The greater is the limitation on available resources for SDI development, the greater is the incentive for achieving alignment between initiatives to build SDI.
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1.2. The term 'Spatial Data Infrastructure' (SDI):
1) Is often used to denote the relevant base collection of technologies, policies and institutional arrangements that facilitate the availability of and access to spatial data;
2) Provides a basis for spatial data discovery, evaluation, and application for users and providers within all levels of government, the commercial sector, the non-profit sector, academia and by citizens in general.
So, Spatial Data Infrastructure – the technology, policies, standards, and human resources necessary to acquire, process, store, distribute, and improve utilization of spatial data.
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1.3. Requirements to SDI:
1) SDI must be more than a single data set or database;
2) SDI hosts:
a) Position data and attributes;
b) Sufficient documentation (metadata);
c) A means to discover, visualize, and evaluate the data (catalogues and Web mapping);
d) Some methods to provide access to the geographic data;
e) Additional services or software to support applications of the data;
f) The organizational agreements needed to coordinate and administer data on a local, national, regional and or trans-national scale.
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1.4. SDI levels
1. As to spatial data domain, we can distinguish in general:
1) Global SDI;
2) Regional (including continental, trans-national etc.) SDI;
3) National (state) SDI;
4) Local (inter-state) SDI.
2. First two of such 'data domain' SDI can be named in general "International SDI", other two – 'National SDI'.
3. As to context and functions of SDI, for example:
1) Regional, national and local 'data domain' SDI can be the part of Global SDI and will be qualified as 'international SDI';
2) Term 'corporate SDI' also exists and such SDI can be international or/and national concerning domain and functions etc.
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1.5. The ultimate goal of SDI is to create a situation where spatial data is available and used throughout society and so:
1) It is so easy and inexpensive to use spatial data that you don’t realize you’re using it at all;
2) The use of spatial data becomes part of your daily activities;
3) Everybody in society benefits from being able to use spatial data;
4) The Information Society has been created;
5) Things that were once impossible or very difficult become possible/easier.
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1.6. Lead agency of SDI development:
1) Is the prime mover of SDI:
a) Facilitates administrative functioning of the SDI;
b) Manages resources;
c) Provides office space and related facilities for its operation;
d) Often is a government ministry, state organization or an empowered private company;
c) Often has a mandate related to spatial data management, links with other organizations;
2) Deals with “big picture” issues surrounding SDI:
a) Maintains linkages with the other SDI initiatives;
b) Frequently is networked with other, subsidiary agencies.
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1.7. Factors for an effective SDI organization:
1) Open data policy, accessible to users, few restrictions;
2) Standardization to enable transfer and exchange of spatial data;
3) Data/Information sharing and shared experience;
4) Networking for better access as well as better service;
5) Multi-disciplinary approach: scientists, engineers, technicians and administrators should cooperate;
6) Interoperable systems.
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1.8. Generalized SDI implementation stages:
1) Creating an awareness of need for SDI;
2) Identifying system, organization and network requirements;
3) The translation of organizational needs into functional requirements;
4) System evaluations;
5) Justifying the system acquisition;
6) The system acquisition and start up;
7) The operational phase.
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Fig.1.1 – SDI institutional framework (1.9)
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1.10. Advantages of SDI development:
1) Spatial data are standardized and better maintained:
a) Revision and updating are easier;
b) Easier to search for, analyze and represent data;
c) Data products are more valuable;
d) Data can be shared and exchanged more freely;
e) Productivity of the staff is improved;
f) Time and money are saved;
g) Better decisions can be made;
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1.10. Advantages of SDI development:
2) Spatial data operations are faster:
a) Faster data acquisition and pre-processing;
b) Faster database management and retrieval;
c) Faster spatial measurement and analysis;
d) Faster graphic output and visualization.
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1.11. SDI possible benefits for the society:
1) Social infrastructure...better society;
2) Environmental infrastructure....better management;
3) Urban infrastructure.....better life;
4) Economic infrastructure.......better business;
5) Educational infrastructure......better knowledge.
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1.12. SDI funding:
1) Funding for SDI development is derived from public sources (e.g. taxes or export/import revenue) and private sources (e.g. business profits);
2) Public funding requires justification for the socio-economic value of SDI development;
3) Such justifications include:
a) Greater efficiency in storage, analysis and acquisition of geospatial data and information;
b) Faster application of this information to real world problems;
c) Financial savings resulting from these advantages;
d) SDI was applicable to the key socio-environmental and land based problems;
e) The technology allowed more interaction between developing and developed countries.
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1.13. Recovery of costs on SDI development:
1) Cost recovery models are based on the financial benefits, which offset the costs from a cost benefit perspective;
2) SDI involves both high costs and strong potential benefits;
3) The higher the applicability, accessibility and availability of the techniques and information, the greater the cost recovery;
4) Effective human management increases the returns and hence increases the benefits.
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1.14. SDI tax funding:
1) Benefits provide the justification for tax support for SDI development;
2) SDI, in producing value added products, provides the potential of financial revenue to support the contribution of taxes. This encourages:
a) The cooperation of private and public organizations;
b) The increased application of SDI, as an economic development, rather than a costly liability.
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1.15. Examples of SDI economic benefits:
1) Great Britain:
a) £79-136 billion created by SDI activities in 1996;
b) ~ £200 million direct return from sale of spatial data and services;
2) The United States:
a) $3.5 trillion return from 12 core agencies;
b) Benefit costs $4 – 15 billion per year, depending on estimate, plus indirect returns;
3) Australia;
a) Cost of spatial data is 1/6 of what it would be without SDI;
b) Saved $5 billion over 5 years.
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1.16. Types of SDI legislation assistance:
1) Pre-existing laws covering information access, including copyright and patent laws;
2) Privacy laws, applied both to information access, and the use of remote sensing methods;
3) Laws governing contacts between:
a) Central and local government;
b) Local public sector bodies;
c) Private companies and individuals;
4) Laws establishing the capacity of SDI;
5) Laws that repeal impediments to the smooth functioning of an expanding SDI.
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1.17. SDI peculiarities
1. SDI provides the ideal environment to connect applications to data:
– Influencing both data collection and applications construction through minimal appropriate standards and policies.
2. The creation of specific organizations or programs for developing or overseeing the development of SDI can be seen as the logical extension of the long practice of coordinating the building of other infrastructures necessary for ongoing development, such as transportation or telecommunication networks.
3. Just as SDI programs of necessity involve the alignment of scarce resources for achieving success, so too it is necessary to ensure that the SDI initiatives develop in harmony with each other in order to maximize the impact of these programs.
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4. In reality, many initiatives are working in isolation, not necessarily developing in harmony with others and consequently unable to reap the benefits of working together.
5. Anyone:
– Who is involved in a project of which spatial information forms an integral part;
– Who intends leaving a legacy of spatial data or tools to exploit the data that lasts beyond the period of funding for the project;
– Is, by definition, participating in some of the fundamental elements required by an SDI.
6. As coordination between organizations expands, these projects very often lay the foundations on which initiatives formally dedicated to the establishment of SDI can then build.
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1.18. The most prominent examples of formal SDI programs are on a national scale:
1) Most of these are driven by the national or federal government, e.g.:
a) The NSDI in the USA;
b) The SNIG in Portugal;
c) Australia’s ASDI;
d) Malaysia’s NaLIS;
e) South Africa’s NSIF;
f) Colombia;
g) The multi-national INSPIRE Initiative in Europe etc.;
2) There are exceptions, which have largely been driven by the private sector, such as:
a) The Uruguay Clearinghouse;
b) NGDF in the United Kingdom.
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