Social Media and Authoritative Citizen Data
Crowdsourced data, initially met with skepticism and concern by the geospatial community, is now going mainstream. GIS practitioners have long been the keepers of “authoritative” data, and are now beginning to take crowdsourced data very seriously. This is in large part due to the tremendous utility of crowdsourced data we’ve seen during responses to recent disasters. Crowdsourced data enriches GIS, and Esri is constantly looking at how our users can use, manage, interpret, and incorporate it into their work.
With the advent of cloud computing as a new platform, geospatial applications in the cloud are driving a powerful new modality for GIS. With it, there is an opportunity to reinvent the way the GIS application is built and consumed, as well as influence the discovery and availability of spatial data and geospatial analyses.
Cloud computing provides the potential for access to and publication of dynamic data. This includes the consumption of real-time information for analyses and modeling, which can then be leveraged in applications that serve multiple purposes and audiences. Esri is seeing this more with disaster response operations that are standing up mission-critical geospatial applications hosted in the cloud. With access to seemingly unlimited compute capacity using cloud infrastructures, analytical calculations can be performed in a fraction of the time as traditional processes, which may potentially offer more economic viability as a result of the economies of scale that the cloud affords.
This may seem only attractive to small- to medium-sized businesses, educational institutions, non-profits, and startups. But as cloud computing moves increasingly into mainstream operations for business, the potential for cloud-hosted content and cloud-delivered content is becoming a significant reality for organizations, regardless of size. For a geospatial technologist, cloud GIS can ideally mean that data is always available, always accessible. For the mobile worker, the cloud offers an expansive field to speed workflow productivity and collaboration. Shared data and applications in the cloud can be immediately accessed to discover, view, edit, save changes and invoke geoprocessing functions for on-demand results.
Esri recognizes the opportunities that cloud computing can afford the geospatial professional and technologist. As such, we intend to continue to invest significantly in research and development of cloud-based solutions and services across multiple vendors to satisfy the requests by the geospatial community, and to foster growth of GIS into industries and within communities that may have not been cultivated as yet.
It is important to underscore that our current attention to the cloud does not forego interest and investment in on-premises desktops, servers and mobile applications. Rather, the cloud is another enabling platform to help complement and augment an organization’s sales, marketing, and technology portfolio capabilities.
Business Intelligence and Analytics
Commercial/business applications of GIS have long lagged behind more traditional GIS applications such as planning, government, and environment. But we are starting to see GIS reach much deeper into the business arena due to the focus on integration of GIS with enterprise resource planning (ERP), business intelligence (BI), data warehousing, and enterprise content management (ECM) applications. The majority of these integrated applications let end users work either in their business application environment or the GIS environment, so they are not disruptive to existing enterprise workflows.
Esri’s approach in this arena has been to partner with companies who have deep expertise in their respective BI, ERP, and ECM environments. We also recently acquired SpotOn Systems, a company that brings interactive mapping to IBM Cognos business intelligence applications. By making it easier to unite Esri’s spatial analytics, data, and maps with IBM Cognos BI, we think that this acquisition provides business users of GIS with the analytic element that has long been missing.