Go to the Members Only area to download this latest version.In the current release of the PODS Pipeline Data Model (PODS 6.0, May, 2013) the PODS model has been broken down into 31 modular components which may be implemented independently with certain dependencies.
Dimensional modeling (DM) is part of the Business Dimensional Lifecycle methodology developed by Ralph Kimball which includes a set of methods, techniques and concepts for use in data warehouse design.
Dimensional modeling always uses the concepts of facts (measures), and dimensions (context).
The PODS Pipeline Data Model houses the asset information, inspection, integrity management, regulatory compliance, risk analysis, history, and operational data that pipeline companies have deemed mission-critical to the successful management of natural gas and hazardous liquids pipelines.
Typical information stored in a PODS database includes (partial list): The PODS Relational Model is implemented on either an Oracle or SQL Server RDBMS, and is therefore GIS-neutral.
The PODS Pipeline Data Model provides the database architecture pipeline operators use to store critical information, analyze data about their pipeline systems, and manage this data geospatially in a linear-referenced database which can then be visualized in any GIS platform.
The PODS Pipeline Data Model houses the attribute, asset information, construction, inspection, integrity management, regulatory compliance, risk analysis, history, and operational data that pipeline companies have deemed mission-critical to the successful management of natural gas and hazardous liquids pipelines.Similarly for a point feature, such as a valve, the begin station and end station are the same value (i.e., 500 m).In a similar manner, the same linear referencing system is used to locate, and effectively overlay, inspection reports, events, activities, or features, which occur on or near the pipeline.Facts are typically (but not always) numeric values that can be aggregated, and dimensions are groups of hierarchies and descriptors that define the facts.For example, sales amount is a fact; timestamp, product, register#, store#, etc. Dimensional models are built by business process area, e.g. Because the different business process areas share some but not all dimensions, efficiency in design, operation, and consistency, is achieved using conformed dimensions, i.e.The PODS Spatial Implementation is essentially identical in content to the PODS Relational Pipeline Data Model, but was specifically developed as a geodatabase for implementation on the ESRI platform.