Evaluating GIS Vendor Templates

Introduction
This paper will focus on the process of performing GAP analysis on standard templates packaged with GIS software for distribution utilities (Sue – I do not see where an evaluation is being discussed in this paper. If you think the author is right, omit my edit). (Sue – I do not see where an actual ESRI/Intergraph template is being referenced) The scope of this review covers both relational and object oriented vendor offerings.

The GIS Software Selection Process
Many utilities are incorporating an evaluation of vendor supplied templates as a part of the software selection process. To properly evaluate the usefulness of a template, some level of understanding is required about the information the GIS will manage and how it will be stored.

Types of Data Modeling
What is a GIS data model? A GIS data model can be thought of in the same context as a traditional information system data model, which can simply be defined as “a specification of the data structures and business rules needed to support a business area”. A true data model should be more than just a structural diagram, and should convey complete information about how entities are managed by the information system. Data models should start at a low level of detail and then expand the detail as they reach completion.

The Logical Data Model (LDM) is a representation of the system at the abstract level, and contains none of the constraints of the actual physical implementation. The Physical Data Model (PDM) is the expression of the logical design into a working application architecture.

Entity-Relationship Data Models
Entity Relationship (ER) data models have been used for many years to assist with the implementation of relational database systems. The current accepted standard for ER modeling is called IDEF1X, and is supported by most modeling software vendors.

Special terminology is associated with data modeling and some of the commonly used terms are defined below:

An entity is a thing of significance to the business, whether real or conceptual, which holds information for the business or system being modeled. Each defined entity must have more than one occurrence and each occurrence must be uniquely identifiable. For example, a transformer is an entity in an electrical distribution system. Transformers can have many types or occurrences and each type or occurrence can be uniquely identified. An entity relationship diagram not only shows data entities but also their relationships with others.

Data entities are represented using the following notation:

Data Entity
An attribute is an individual piece of descriptive data about an entity. Attributes of an entity are identical for all the specific instances of the entity. Attributes for a super-entity are applied to all of its sub-entities.
A relationship is the nature of the interaction between two entities. Sample entity relationships are shown below.

An optional relationship description can also be shown using text in the ER diagram.
A primary key is an entity attribute that uniquely identifies each instance of an entity from other instances. It is the primary key that provides the relationship between two entities.
A domain is a common database format and set of discrete values that can be used repeatedly for similar attributes. All attributes must either have a domain or their own unique definition.