The quality of your GIS data model is essential to get the most out of your ArcGIS software. Esri offers lots of options for setting up your data structure both fully customised and based on predefined data models. This page contains frequently asked questions about ArcGIS data models.

ArcGIS data models: an introduction

What is a GIS data model?

A GIS data model is a structured representation of geographic data used to store, organise and analyse spatial information. The data model acts as a blueprint for how geographic data is stored and managed, allowing the system to process and analyse it efficiently.

There are different types of GIS data models, including raster- and vector-based models. Grid models divide geographic space into a grid of cells, with each cell having a value representing a specific feature (e.g. elevation, temperature). Vector-based models represent geographical features using points, lines and polygons to accurately represent their shape and location.

In addition to these basic types, there are other more advanced GIS data models, such as the geodata base model and the network data model. The geodatabase model is a storage and management system for geographical data in a relational or object-relational database. This model can contain complex relationships between different data layers and supports advanced analysis functions. The network data model is used to model geographical networks, such as transport networks or utilities, and enables users to perform complex network analysis.

What is the geodatabase model in ArcGIS?

The geodata model in ArcGIS is a structured and standardised way to organise, manage and store geographic data in a geodatabase. A geodatabase is a container for storing GIS data, such as vector and raster datasets, tables, topology, networks and terrain models.

A geodatabase is a container for storing GIS data, such as vector and raster datasets, tables, topology, networks and terrain models.

Some of the important aspects of geodatabase models in ArcGIS are:

  1. Geodata models provide a structured format for organising data, such as defining fields, domains and subtypes.
  2. Use a geodata model to establish relationships between different datasets and objects, such as topological relationships, network connectivity and hierarchical relationships.
  3. Monitoring data uniformity becomes easier with the help of a good geodata model. By setting rules and constraints, manual errors can be avoided.

ArcGIS also offers the possibility of using predefined data models designed specifically for a particular industry. You can read more about this in the next question answer section.

Predefined data models in ArcGIS

For which industries do predefined data models exist in ArcGIS?

ArcGIS offers a wide range of predefined data models designed specifically for a particular industry. We list some common examples:

  • Water management;
  • City planning;
  • Public safety;
  • Infrastructure;
  • Environmental management;
  • Utilities;
Which extension do I need to use predefined data models in ArcGIS?

You will need additional extensions for ArcGIS Pro, Enterprise or Online software to use the predefined data models. 

You will need additional extensions for ArcGIS Pro, Enterprise or Online software to use the predefined data models. You need a specific extension for most of the industry-specific data models. For example, to use the predefined data model for utilities, you need the Utility Network Management extension.
How can I use predefined data models in ArcGIS?

Follow the following steps to use defined data models in ArcGIS, after finding the data model suitable for your industry:

  1. Download the predefined data model. Some data models can only be found on the vendor's website, some data models can be found on the Esri website. Some data models are available as templates, while others are provided as documentation with design patterns.
  2. Create a new geodatabase in ArcGIS and implement the predefined data model by following the instructions from the documentation or by importing the template.
  3. If necessary, modify the defined data model according to your personal requirements. For example, it is possible to add, remove or change attributes, domains, subtypes, relationships and other elements from the data model.
  4. Import your current data into the predefined data model. Check that the data complies with the structure and validation rules of the data model.

After completing the above steps, you can start analysing and visualising your dataset!

Creating your own data models in ArcGIS

How do I create a data model in ArcGIS?

Is there no predefined data model suitable for your project or your industry? Then you can create your own data model in ArcGIS Pro. To do so, follow these steps:

  1. Determine the goals and requirements of the dataset. This first step is necessary to find the right way to structure and organise your data.
  2. Create a new geodatabase in ArcGIS Pro. This will be the container for all your data and thus form the basis of your data model.
  3. Create the necessary feature classes and tables for your data model.
  4. Use feature datasets to group related feature classes. Feature datasets can also include topologies, networks and terrain models to support advanced analysis and operations.
  5. Optional: define domains and subtypes. Domains define valid values or ranges for fields in your data model. By setting domains, you can avoid many manual errors when using the data model. Subtypes, in turn, can modify the behaviour of features within a feature class based on their type.
  6. Create relationship classes to capture relationships between objects in your data model. Relationships can be one-to-many, many-to-many or one-to-one and can be used to monitor data quality and enable complex analysis.
  7. Using indexes, compression and other optimisation techniques can improve the performance of your data model.
  8. Write good documentation on your data model. Include the structure, goals and methods used, so that other users use the data model correctly in the future.

Feature classes and feature datasets

What is a feature class?

A feature class is a collection of entities with the same geometry type (points, lines or polygons) and the same attributes. In ArcGIS, feature classes are stored in a geodatabase and form the basis for gis analyses and visualisations. They represent objects or events from the real world, such as buildings, rivers or roads.

Feature classes can have different attributes and relationships related to the entities they represent. They can also relate to geospatial operations such as buffering, overlay analysis and network analysis. Feature classes are essential for organising, managing and analysing geospatial data in ArcGIS and play an important role in designing and implementing data models.

What is a feature dataset?

A feature dataset is a collection of related feature classes in a geodatabase that together have a common theme or purpose. Feature datasets are used to organize and manage gis data that share a topological or network relationship or have the same spatial reference. By using feature datasets, you can logically structure data and perform operations that apply to a group of feature classes.

To create a feature dataset in ArcGIS Pro, you can use the 'Create Feature Dataset' tool, which is available in the Data Management toolbox. This allows you to create a new feature dataset in an existing geodatabase and define the spatial reference and other properties for the dataset.

When should I use a feature class?

The use of a feature class or a feature dataset depends on the structure and requirements of your geospatial data and analyses. We list some guidelines to determine when to use a feature class or a feature dataset:

  • You want to store and manage data for a single geographical feature, such as roads, buildings or rivers.
  • You want to store data without topological or network relationships with other data.
  • You want to perform simple data operations and analysis without dependencies between different data sets.
When should I use a feature dataset?

Use a feature dataset when:

  • You want to group multiple related feature classes that share a common theme, purpose or geographical area.
  • Your data have topological or network relationships that need to be defined and managed.
  • You want to perform advanced GIS analyses that take into account the relationships between different feature classes.