This concept refers to association with the exchange, interchange or transfer of data between two or more users, organisations or computer systems

Requires national information policy and national information infrastructure

The process of spatial data sharing often involves; conversion and transformation

Computing environment

Systems architecture

Procedure

Purposes and applications

Infrastructure - based on the concept of a spatial data infrastructure (SDI)

Enterprise

Domain

Functional

Connected

Ad hoc or peer-to-peer connection

1. Promotes best practice in data management
2. Reduce the cost of using spatial information
3. Reduce the cost of data maintenance
4. Increase the quality of spatial data
5. Reduce software costs
6. Expedite application development and deployment
7. Reduce the risk of vendor lock-in and stranded technologies
8. Easy integration of spatial data with other forms of business data

Inherent complex and diverse characteristics of spatial data e.g., scale, geographical referencing, spatial and temporal resolution

Non-uniformity in terminology resulting from non-deterministic nature of human cognition and language

Differences in data management policies, user access protocols, systems security measures etc.

Technical incompatibilities and systems dependencies

Lack of data model and format standardardisation

Restricted availability of data

Unwillingness of organisations to share data

Poor data sharing policies

Object Linking and Embedding (OLE)

Open Database Connectivity (ODBC)

Java Database Connectivity (JDBC)

Common Object Request Broker Architecture (CORBA)

Common Object Model (COM)

Web-based services protocols

Web services are software components that can be accessed over the Internet through standards-based protocols or a standardised way of integrating Web-based applications using open standards

Data warehouse

Database federation

A collection of subject-oriented data in a well-defined and tightly structured repository

Approaches to implementing a data warehouse

• Central data repository e.g., Survey of Kenya
• Enterprise data warehouse - data is derived from operational data sources within an organisation
• Data marts - a subject-specific data warehouse. It is smaller, scaled-down and more manageable data warehouse

Subject-oriented - organised around major applications of an organisation

Integrated - integrate data from multiple heterogeneous data sources

Time variant - sourced at different times

Non-volatile - is a separate physical construct from the data sources and accessed mostly by read-only applications

Architecture of a Data Warehouse

A configuration of geographically distributed, autonomous and heterogeneous data sources and services, communicating using a standard protocol over a network either through schema integration or information mediation

The objective of database federation is to create a database architecture that provides uniform and simultaneous access to several heterogeneous data sources

Tight Database Federation - use a unified schema

Loose Database Federation - use a uniform query language

Mediated Database Federation - data sources are federated by connecting together into a unified system

Architecture of a Federated Database System

Queries about this Lesson, please send them to: jmwaura@jkuat.ac.ke

*References*

• Database Systems: Design, Implementation, and Project Management, Springer. Albert K W Yeung & G. Brent Hall
• Database Systems: Design, Implementation, and Management, 12th ed. Carlos Coronel & Steven Morris
• Database Modeling and Design; Logical Design, 5th ed. Taby Teorey et.al
• Fundamentals of database systems, 6th ed. Ramez Elmasri & Shamkant B. Navathe