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5.0 ORGANIZATIONAL DATA MINING
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The richness of LIDAR data coupled with collection effort creates the opportunity for broader deployment across the organization (Figure 3). The advantages of adopting LIDAR information broadly across the organization are multifold:

Fig3_DOTorganization

Figure 3: Centralized data storage for typical divisions within a transportation agency (after Singh, 2008).

5.1 Single repository

Figure 3 shows schematically the concept of how typical divisions within a transportation agency may use and update centralized datasets.  Ideally, data is centrally located and updated by each organization during all phases of the infrastructure life cycle (Singh, 2008) so that it is current and accessible to all within an organization. A single repository provides many benefits to an organization:

  • As the information is shared and continually updated, it becomes more robust and trusted because each additional use directly or indirectly provides a quality check.
  • Multiple users working with a common data set are less likely to experience uncertainty or confusion that arises when dealing with overlapping but slightly different versions of a data set.

5.2 Historical

Historical records of very high detail can be maintained indefinitely in digital form.  This information can be mined after-the-fact.  For example, evaluating deflection in a structure over time or investigating the causes of failure are facilitated with accurate, 3D information.  As a second example, having baseline information could prove invaluable in case of an earthquake or other hazard, when damage assessments are needed quickly and prior to opening bridges for traffic flow.

5.3 Faster decisions

Planning, maintenance and safety groups can use LIDAR data to quickly visualize key areas for better collaboration and decision-making.  With proper software, users not skilled in survey or engineering can utilize dense 3D data efficiently.

5.4 Costs

Costs of data collection will continue to fall as systems become faster and more commonly used. Transitioning the cost of collection from per-project engineering to include routine maintenance, operations or other potential uses of the data will increase the return on investment.  Data collection may also be coordinated with other interested agencies that will share the costs.

5.5 Redundancy

Centralizing data also avoids redundancy and eliminates duplicate efforts.  Multiple regional offices, for instance, may need data in common or overlapping areas and not be aware of the other’s needs. Duplication of effort and data can often be avoided if the collection is coordinated through a main office.

At present, software that leverages LIDAR data across the enterprise is in its infancy, but one should anticipate rapid progress over the next decade.  Advances in cloud computing and software-as-a-service (SaaS) will likely significantly reduce the agency’s IT burden for management of MLS data and make real-time access to information available to a much broader audience than at present.

Recommendation: Follow developments in agency-wide collection and deployment of data, but at present adhere to the provisions of your sunset plan (Section 4.5.5).

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