GeoWorld

P ersistent legacy applications and workflows often are difficult for organizations to spatially enable, especially when the data source is complex and lengthy. Increasingly, key decision makers find themselves needing data that can be analyzed in context with location and associated business data to support timely business solutions. So how does an organization leverage existing data while increasing analysis capabilities by upgrading from a rigid mainframe application to an enterprise GIS? As an effective example, the New Mexico State Land Office (SLO) offers how to "do it right" by geoenabling its right-of-way (ROW) data that support, among other things, lease-management business processes. SLO was created in 1899 to manage New Mexico's trust lands for the benefit of public schools and other public institutions. As stewards of these trust lands, SLO oversees and manages activities such as generating revenue while protecting and conserving the lands for future generations. Revenue is collected principally from leasing activities, which includes subsurface (e.g., oil and gas, and minerals leases) and surface leases (e.g., ROWs, agricultural and commercial leases). Perpetual and long-term easements are significant and extensive features of the trust landscape and work processes. But most easements never have been adequately mapped, leaving SLO officials with a need for accurate spatial ROW data to make better-informed landmanagement decisions. data capture to date (Figure 2 shows an example of the existing spatial information). Increasing business demand for timely and accurate lease-location information created the need to improve lease-location data access, analysis and maintenance capabilities, but there's a technological disconnect between database information and spatial data. Further, there are several limitations within ONGARD: bution, limiting the types of analysis that can be performed. upgraded for versatility. exist, they can't be found and corrected. In this age of digital data, SLO found itself lagging in providing critical infrastructure information to help decision makers. The Solution The New Mexico SLO required a solution that could bring ROW data into a spatial format and capture all the critical information. Timmons Group was engaged to define the business requirements, evaluate the technology solutions, develop the work processes and complete a pilot conversion project. The solution The Problem ROW lease data currently are stored and managed in the Oil and Natural Gas Administration and Revenue Database (ONGARD), a mainframe DB2 application that captures nonspatial information from lease applications and survey plats (e.g., type of structure, use of land and Public Land Survey System (PLSS) description of the ROW). ONGARD originally was designed to capture oil and natural gas lease financial information, but it has been modified to also capture surface-leasing information. Figure 1 shows the ONGARD system user interface. Rudimentary lease-location data, including quasispatial PLSS data, are captured in Surface Tract Books. These include hand-drawn ROW representations per the legal description as well as the ROW's history. This has been the extent of lease-location Figure 1. The ONGARD system displays the "spatial" location of ROWs by nominal quarter section. A U G U S T 2 O 1 3 / W W W . G E O P L A C E . C O M 27

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