While in the past, systems and applications focused on solving a single problem using custom data models, and specialized databases, enterprises are moving away from these isolated systems to reduce duplication of effort, reduce costs through better utilization of resources, and improve quality of service.
Oracle sees a number of significant trends affecting the breadth and depth of usage of location information.
- From few, or specialist, users to broader services utilized across multiple job functions or departments.
- From single application to application infrastructure enablement.
- Consolidating organizations and workflows.
- Unification of operational systems with common information platforms.
o From BI to business processes
- Cheap quick data collection/aggregation/dissemination.
o Satellite and aerial imagery
o Sensor networks
o 3D data for city, terrain, and geophysical models
- Low cost, widely available visualization tools.
- Ubiquitous service-oriented architectures.
- Increased availability of a GRID of hot-pluggable information infrastructure.
o Petabytes of cheap storageOracle has, for many years, invested in providing an integrated content store, a robust and standards based application development and deployment platform, and an integrated suite of applications designed for implementing flexible business flows and access to valuable information when and where its needed.
o Grid enabled databases and application servers
o Cheap memory
o Low cost servers
o Resource virtualization and dynamic provisioning tools
o Vendor supported standards
Such infrastructure makes it easier for domain experts to solve business problems. Spatially enabled applications can utilize infrastructure services to the maximum.This allows solution providers to focus on the business problem, not the technology issues.This is a more efficient, collaborative use of skills and resources.Platform vendors handle infrastructure issues, while application developers and solutions providers focus on domain-specific tools, for example, spatial analysis, workflows, and rules.
For such applications to be most easily developed and deployed, typically spatial data management should reside in the IT infrastructure, and not be locked away in a separate, isolated system with proprietary data access.These applications then gain the robustness, security, and scalability of the infrastructure.
The development of lower cost, and widely deployed, automated data creation and collection methods such as RFID, automated meter reading, digital imaging cameras, airborne or terrestrial LIDAR, and remote sensing satellites is leading to an exponential explosion of data that must be managed.The availability of such data, coupled with advances in visualization and geometric modeling technology have made it possible for desktop or browser based applications to incorporate sophisticated techniques such 3-D, terrain, engineering, or scientific analysis and visualization.
Many organizations currently use such technology very effectively in their operational and decision support systems.For examples, insurance companies routinely utilize very large collections of gridded datasets (e.g.likely exposure to risk due to hurricanes, fire, earthquake, crime) in risk assessment and portfolio analysis.Wireless communications companies use realistic 3-D city models to determine placement of antennae.Homeland security or emergency response organizations use similar models to determine access points for buildings, or locations of utilities (e.g.gas lines).While these applications effectively address a specific purpose the emergence of services such as Microsoft Virtual Earth (or Live local), Google Earth, and NASA's Visible Earth is resulting in wider acceptance and greater expectations of such technology.As a consequence, we expect to see asset management, transportation, logistics, service, and other enterprise applications either adding such modeling and display capability, or interfacing with services or software that provide it. Oracle already supports efficient storage and retrieval of vector, raster, and gridded datasets.Hence it is likely that future releases will support representation and management of surface models (e.g. TINs, DEMs), 3-D, and Lidar imagery or point-cloud data.
There is a fast growing trend towards service oriented architectures and integration with real time or near time sensors for operational and decision support systems.Many organizations are developing business strategies based on the concept of real time sense and respond.Raw business events are collected from sensors or conventional business applications and then processed into higher-level "complex events" and acted upon using rules based business process, or activity, monitoring systems.Sensors can be used to monitor a real-time process (traffic, transactions, utility consumption) that then trigger another process.In addition, the use of radio-frequency (RFID) tags is increasingly used for inventory control of industrial equipment, shipping, and vehicle identification, and indoor asset tracking.Many of these applications will require a location element.This and the fact that location-determination technology (GPS, cellular networks, RFID, WLAN) is becoming ubiquitous underscore the need for a location ready SOA platform.
Oracle, Amazon, Google, Yahoo, Salesforce.com and others have spearheaded another trend.That is, enterprise grid computing using low cost hardware and software that enables virtualization and dynamic provisioning of resources.Google, for example, has shown that this infrastructure is excellent for building scalable, and highly available, geospatial services that provide a rich user experience. Oracle's product strategy is led by the vision of where we believe grid computing could lead in the future.Infrastructure resources managed in a grid will progress to the point that computing and storage capacity are delivered on demand like a utility.Applications in a grid will advance so that business and application logic are as massively connected and referenced as static web pages are on the Internet today, enabling frictionless, automated, global business between trading partners.Eventually, a global information grid will impart to every bit of digitally represented information anywhere the same values we take for granted with relational databases as if all information resides in a single virtual database.All inherent relationships between information will be revealed, and anyone with appropriate authorization will have instantaneous access to all relevant information regardless of representation, location, or access method.
Oracle's information platform will continue to drive trends and address requirements as they arise.Hence future releases of the Oracle database will likely support storage, indexing, and efficient retrieval of 3-D data, and surfaces, for city and terrain modeling, cadastre, homeland security, and other applications.The adoption of SOA and proliferation of sensor networks mean the database and application servers' existing SOA and sensor based computing infrastructure will support geospatial services.Oracle's business intelligence tools (Discoverer, BI Beans) already support spatial querying, analysis, and presentation as part of their exploratory data analysis and dashboard functionality.Future releases of these tools will likely see a much more seamless integration of spatial information handling in the BI product suite.The dashboard will have linked views of information presented on maps, graphs, crosstabs, or tabular reports.All query build or report generation wizards will support spatial analysis and map visualization.Data preparation, or ETL tools, will support linking of spatial data with other data sources, and invoking spatial functions during the transformation stage.In summary the Oracle platform, database, fusion middleware, and applications suite will continually enhance their support for spatial information management thereby delivering further value to organizations.
Spatial information management is no longer a specialized application, but has broad relevance to general business applications and IT. Integration of spatial information with the IT infrastructure makes intelligence about location accessible to more business applications "" resulting in better information, and agile decision making.It also allows domain experts to focus on solving the business problems.Spatial information management will evolve as IT platforms evolve.Thus, as IT platform evolves to grid computing, SOA-enabled, resilient platform, these benefits will accrue to spatial applications.
Silos of proprietary spatial data are being replaced by master content stores, i.e.logically consolidated, consistent, open, very large data hubs.Consolidation of spatial with IT data management infrastructure eliminates duplication of effort and reduces costs of deployment and data maintenance; spatial data is stored once and maintained centrally in an enterprise data store, and used many times by several applications.