SDI

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Spatial Data Infrastructure (SDI) is an information infrastructure providing access and enabling interoperability among spatial information based on standards, policies, regulations and coordination mechanisms (Groot R, 1997). The methods for creating SDI undergone radical changes in the recent years like the shift from the product-led model or data-producer-led model to process-led model or data-user model, etc. However, there are some limitations challenging the SDI growth like the lack of standards to handle linked geospatial data, etc.
The goal of this essay is to detail the concepts for the creation of an improved SDI in the year 2019. The intended SDI integrates the existing developments in the field to the relevant emerging trends and incorporates additional functionalities and technological advancements like cloud computing infrastructure. The essay also highlights the policy, standards and organizational requirements for overcoming the challenges of the current scenario.
The future SDI has all of its components moved to cloud environment which helps in scalability. The future SDI has the following key features categorized according to the components of a SDI:
• Databases, Metadata & Sources:
The geographic information is converted into linked geospatial data, for exposing, sharing and connecting resources in the web. For example, a geographical feature described in the data has a URI with links pointing to other geographical features based on their geospatial relation. The knowledge model and catalogue model of the datasets (metadata) is changed according to the developments in the field of semantic web to accommodate details that are necessary for pattern recognition and subsequent linking .The SDI should use open data...

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The future SDI increases the transparency in acquiring data and access to information which allows saving time, money and creates a platform to sustain increased efficiency and avoid duplication of efforts. This definitely impacts the society, especially involves more people during the spatial decision making process. For example, an analysis of a person can be challenged with more facts and in the similar way supported. With the increases of problems related to environment, SDIs like these can help more people to involve in the research and analysis. It might help solve some of those problems by identifying some things which went un-noticed, etc.
I believe, the future SDI described in this essay has the potential to cater the needs of 2019, except in an unlikely event of technologies mentioned here becomes outdated by that time, for example cloud environment.

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