Spatial Data Infrastructure

 

SDI concepts and its current trend

Spatial Data Infrastructure

- SDI is defined as the collection of technologies, policies and institutional arrangements that facilitates the availability and access to spatial data.
- It provides basis for spatial data discovery, evaluation and application for users and providers.
- It encompasses resources, systems, network linkage, standards and institutional issues involved from many different sources in delivering the geo-spatial information to the potential users.
- The main aim of SDI can be expressed as follows:
1. To link existing and upcoming databases of the respective level. (Represented by product based model)
2. To define a framework to facilitate the management of information assets. (Represented by process based model)

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SDI Hierarchy

- The SDI hierarchy consists of following levels:
1. Organizational SDI
2. Local SDI
3. State SDI
4. National SDI
5. Regional SDI
6. Global SDI

- Organizational, local and state SDI are the operational levels of the SDI.
- National SDI is the functional level of SDI.
- Regional and Global SDI are the strategy management level of the SDI.

- Each lower level provides the building block for upper levels.
- Each upper level transfers strategy and policy to lower levels.

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National Spatial Data Infrastructure (NSDI)

- It is the functional level of Spatial Data Infrastructure that encourages collection, processing, archiving, integration and sharing of the geographic spatial data and information using common standards and inter-operable system and techniques.
- It assures that the spatial data from multiple sources are widely available and integrated to enhance knowledge and understanding of the geographic phenomena of the world.

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Components of SDI

- The basic components of SDI are as follows:
1. Standards
2. Framework
3. Geo-data
4. Metadata
5. Clearing House

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Characteristics of SDI

1. It is a set of base capabilities.
2. It is a general comprehensive system.
3. It has multiple effective aspects in ICT utilization.
4. It includes stable and dynamic physical components.
5. It provides fundamental, important and irreplaceable services

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The concept of metadata and clearing house

Clearing House

- A clearing house is a distributed network of spatial data producers, managers and users that are linked together electronically.
- It consists of a system of software and institutions that facilitates discovery, evolution and transfer of the spatial data.
- The main aim of the clearing house is to minimize unnecessary duplication of the effort for data capture and to maximize the benefit of geographic information sharing.
- It acts as a service that supports for links to the spatial data and browsing capabilities.
- From institutional point of view, it is the people and infrastructure that facilitates discovery of which geographic information is possessed by whom.
- From technical point of view, it is the information service that provides access to the geographic information for the potential users.

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Working of Data Clearing House

- The data providers are allowed to register their geographic data sets, quality of data and methods to access these data.
- The data providers also provides additional information about the data sets.

- Client consults server registry to get the geographic data access.
- The registry pass the distributed query to all the data servers.
- The data servers provide response in the form of headlines.
- Client request metadata entry.
- Metadata or data are downloaded or a connection to the data is made.

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Metadata

- Metadata is the additional information about the data sets, which describes content, quality, condition and other characteristics of the data.
- It provides a way to inform the potential users about the data sets, their purpose and scope.
- It is used internally by the data provider to monitor the status of the data sets.
- It is used externally to advertise to the potential users through a national clearing house.

- A standard is defined for the design of the metadata.
- Metadata must be managed properly to keep it up-to-date.

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Role of Metadata

1. Availability (information needed to determine the data sets that exists for a geographic locations)
2. Fitness for use (information needed to determine whether a data set meets a specified need)
3. Access (information needed to acquire and access the data set)
4. Transfer (information needed to process and use the data sets)

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Critical factors around SDIs

1. Data Standards

- It refers to the agreed way of representing data in a system in terms of content, type and format.
- The same data standard should be maintained by the databases so as to successfully exchange data between them.
- So, a common data standard should be formulated supporting common data architecture to provide efficient base for data transfer.

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2. Heterogeneity

- Spatial data are heterogeneous in nature. It means the data differ in kind, quality and character.
- Such heterogeneous data are maintained by a variety of database system.
- This creates inconsistency among data sets and creates problems during data sharing.

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3. Communication Problem

- Spatial data is huge in size.
- The problem in communication technology is to select the appropriate technology to transfer such huge data with security and reliability.
- The communication medium must guarantee efficiency in search and delivery of the spatial data.

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4. Institutional and Economic Problems

- It arises due to the absence of policy for pricing, copyright, privacy, liability, quality and so on.
- For the proper data sharing, such problems should be resolved.

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