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Desktop to Enterprise


Bob Morris
President and CEO
Leica Geosystems Geospatial Imaging, USA


Large organizations worldwide, including government agencies and private enterprise, have spent years building data and applications for individuals, project teams, departments, offices and geopolitical regions.
With advances in geospatial technologies, they can preserve these past investments while moving into a comprehensive enterprise solution ultimately improving the decision-making process. Geospatial data and information products are derived from image sources such as aerial photography, commercial satellite imagery, military satellite imagery, etc. Consequently, enterprises maintain large repositories of image data. The challenge they face is finding cost-effective and efficient ways to manage spatial data stores (comprising imagery, vector data, maps, thematic and statistical information) and assemble these data sets into a manageable form (geospatially referenced) to integrate with other business systems, such as an ERP, CRM, or Permitting Solution.

Traditionally, these geospatial data were available only to technical personnel for engineering design, environmental analysis, land use planning, disaster planning, forest management, and other tasks. And there was some resistance to opening the geospatial vault to others—concern that data would be lost or misused.

However, as organizations retool for the future, they’ll recognize the value of providing data visualization and analysis capabilities to non-technical users, such as farmers, planners, real estate and insurance agents or policy makers. These users are proficient in their own fields but not necessarily ready to become remote sensing, photogrammetric or GIS experts.

The enterprise approach broadens the importance and use of geospatial data beyond traditional users and thrusts it into mainstream IT. Do it right, and reap the rewards. Do it poorly, and more time, money and resources will be consumed.

Meeting the Needs of Everyday Users
Our industry is moving to help non-technical users perform sophisticated information extraction tasks without being trained on the behind-the-scenes science that makes it possible. This process starts with a base commercial geospatial information product, but employs modules specific to an industry that can be further customized by the customer’s IT department with specific forms, processes and shortcuts.

A forester who wants to find the height of trees at a certain location could use the customized application to select the area and data by following logical workflow prompts. The data would be located wherever it resides in the enterprise and displayed. The forester would select from the data choices to create a thematic map. The application could even automatically select the best source data for the task (such as tree heights), simplifying the task even further.

In this scenario, data is managed and cataloged at the enterprise level and made available to users throughout a network (hardwired or wireless). Each user isn’t logging onto a general spatial application, but an industry and task-specific application. This shortcut to intelligent data and maps will change how organizations use spatial data, broadening the user base and amplifying return on investment.

Geospatial developers and service providers have done this type of customization for years for their customers. Now, we can deliver focused, commercial vertical-market applications that work inside an enterprise.

This holds tremendous promise of increased productivity and competitive advantage, making enterprise resources available to clients using (comprehensive applications), thin (web-browsers) or mobile clients (GPS, PDA). For example, a forester in Arizona and a forester in Georgia could use their web browser to link to USDA Forest Service data that could be stored anywhere in the agency network. As a result of cataloging all data holdings, an enterprise server would know where imagery resides and select and present it based on the user’s specific area of interest and criteria. The cataloging, storage and delivery process remains transparent to the end users since it’s all handled by the enterprise.

This approach more effectively manages the core issue of extracting meaningful data from imagery so it can be easily cataloged, stored and delivered.

Keeping Data Secure
Data sharing within an enterprise means having intelligent security features. Like an Enterprise Resource Planning System, the geospatial enterprise software must support layers of security. This feature lets the manager or IT professional assign viewing, data management, information extraction and data revision privileges.

A sophisticated (fine-grained) security model that subtly controls levels of access is a key element in deploying an enterprise system. Organizations want end users to have as much information as possible while protecting data from access and change by unauthorized users. At some government agencies requiring high levels of security, customized applications and specific data are loaded onto a computer when the user signs in. When the user signs off, they are wiped from the workstation. That same level of security is now demanded by many large organizations that need to provide full, but monitored, access to spatial data. This is a priority for geospatially focused companies like ours that are building security models with subtleties in how users can access and use enterprise data.

Data crawling and cataloging is important to enterprise users. Whether it’s a national mapping agency maintaining and producing a digital land base, state and local government agencies, utility companies or a large architectural/engineering/construction firm, data can be maintained at various locations thousands of miles apart. With advanced data crawling technologies, the user directs the software to intelligently discover and catalog geospatial data.

Data crawling describes the search capability to “crawl” an enterprise’s network to discover and present relevant information so users don’t have to manually search through directories and file names on the network to find the data needed for a specific geospatial application. Based on standards-compliant metadata, the technology seeks out strings of metadata or headers matching the search criteria (like an origin point), and immediately flags datasets or web services matching the criteria. The application could even automatically select the best source data for the task, such as a layer of tree heights to plan the harvest of a forest.

This eliminates the need for every user within the organization to discover data across the network every time a geospatial process needs to be performed on data. This makes it possible for users with little formal training in spatial software use to access and use spatial resources.

The next logical step is creating information from the data. Most GIS systems create data--shape files, coverages, raster images, and land cover datasets. But what users really need is information generated from that data (i.e. vectors, features, change detection, etc.), rather than the data itself. This requires integrating the GIS and spatial systems with other business systems, creating dynamic, on-demand reporting systems. In other words, marrying the worlds of GIS/geospatial with reporting, email, dissemination and enterprise delivery systems.

Traits of Modern Geospatial Software

• Enables better communication and collaboration among various entities in the enterprise
• Enhances workflow for greater efficiency in producing accurate information
• Reduces total cost of ownership of software deployed across the enterprise
• Increases ROI through single, focused applications (like Web applications) that scale to support multiple users
• Integrates geospatial technologies with other enterprise solutions to better manage resources and assets
• Defines security as a function of dat

Thus, the result is not data products but information that integrates GIS and business statistics. If the forester wants to know what the financial potential is for a tree stand at a specific time, he would select the area of interest (the tree stand) and select the information product (financial potential). The geospatial enterprise server application would discover the best datasets required to produce that information based on an intelligent rules-based engine and process the data to create the necessary output. The result could be delivered as a formatted report and even sent by email as a PDF with the geospatial information embedded with statistics and other non-spatial information. Embedded information could indicate, for example, the readiness of the data for use in the project. Raw data could be indicated with red dots while georeferenced data would have green. The user would prompt the system to determine ‘location conflict’ for that area of interest. The system would automatically seek the original data it needs to perform the task and present the results as a visual information product along with the associated statistics.

As a final step, the data is downloaded into a formatted report or other communication tool. These formats would be delivered to industry standards for modification by the customer’s IT department or users, to make them specific to a company or agency. Their use ensures reports will be written to standards, are easy to create and modify, and, most important, are enablers of efficient decision-making.

Our industry grew from the paper and digital map generation, to the 3D generation, to today’s email-FedEx-Instant Messenger-SMS world. In this competitive “I want it now” era, we have to be interoperable, open and work with other business systems and deliver TRUE enterprise solutions that address the decision-making needs of all users in an organization.