A.1 Inventory, Condition, and Performance Data Standards

A.1 – Inventory, Condition, and Performance Data Standards
Required, Recommended, and Optional Data Attributes

Establish clear data requirements by documenting comprehensive inventory, condition, and performance data models. Gather input from key stakeholders to ensure models meet business needs and are practical to collect and maintain. Clearly identify required, recommended, and optional data attributes. Required and recommend fields should be feasible to collect and maintain; optional fields may only be collected under specific circumstances. Data that cannot be reliably collected or maintained should be excluded from the data model.

Figure 3-3. Examples of Required, Recommended, and Optional Asset Inventory, Condition, or Performance Data Attributes

Minimum Data Coverage

Examine asset and performance management decision-making needs to establish clear requirements for where, when and how often asset inventory, condition, and/or performance data will be collected. In some cases, complete network-wide collection may not be needed or may not be practical given resource constraints. In these situations, collection can be limited to what can be collected and maintained in a timely, cost-effective manner – and targeted to what is most valuable to decision-makers.

Important Terminology

The following terms are used within this Section.

Asset Breakdown Structure:

A hierarchical model of the agency’s assets, with high level categories (such as “traffic assets” and sub-categories (such as “traffic signals”).

Asset Information Model:

As defined by Building Information Modeling (BIM) standards (ISO 19650), a model that compiles the data and information related to or required for the operation of an asset.

Component Breakdown:

Models that divide complex assets into individual parts of the larger whole, such as dividing a bridge into the deck, superstructure, and substructure.

Data Attribute:

A specific piece of the data model, describing a data entity. A data element contains a specific fact important to the business (e.g. Bridge ID, Sign Type, Pavement Roughness, or Install Date).

Location Referencing System:

A set of data and procedures for managing locations of geographic objects using one or more methods for specifying location. For TAM this often includes a linear referencing system that specifies location as the distance along the roadway from a reference point (such as a county boundary or intersection).

Conceptual Examples
Targeted Data Coverage based on Asset Life-Cycle Considerations
Streamlining Pavement Marking Performance Data Collection

Certain pavement marking materials have a service life of less than 1 year. An annual retro-reflectivity performance data collection adds little value where these markings are used, therefore these can be excluded from collection.

Network-Level Data Collection Requirements
Focusing Network-Level Collection

Maintaining network-level data collection to meet detailed project-level design requirements is not generally cost-effective – data do not stay accurate due to changing field conditions as well as maintenance and project work. Focus statewide collection on meeting requirements for network-level use cases (such as performance management, needs analysis, investment prioritization).