The conceptual GIS planning process outlined by Tomlinson (2005) and the technical process of System Architecture Design advanced by Peters (2012) were not formed in a vacuum; efforts to formalize this kind of intentional, thoughtful approach to system design exist elsewhere in the IT industry. The discipline of Software Engineering is keenly focused on the process layer within which a particular technology solution is deployed (it is our source for process nomenclature such as “waterfall” and “agile” models)
Furthermore, in the broader IT field, the emerging discipline of Enterprise Architecture has formalized the conceptual notions of business process modeling, data design, application architecture and technology architecture into a series of interrelated process steps resulting in a strategic, yet operational vision to enable an organization to achieve its goals (Woodard, 2017). The TOGAF Standard for Enterprise Architecture advances an “Architecture Development Method” that meticulously breaks down the process of identifying business processes (Business Architecture), developing data models (Data Architecture), identifying the applications needed to support the business needs (Application Architecture) and then developing the technical implementation plan to realize the applications (Technology Architecture) (The Open Group, 2018). As an Enterprise GIS can be improved through a more intentional alignment with an organization’s strategic objectives, and more consideration given to change and risk management (both value-adding points of Enterprise Architecture per Woodard, 2017), Enterprise GIS-as-process stands to benefit from a mapping of the classical Tomlinson process steps to an emerging consensus of best practice in the more generalized field of Enterprise Architecture.
While most of the material up until this point is written at a sufficient level of technical abstraction to remain relevant over time, a proper understanding of Enterprise GIS necessarily includes a discussion of its concrete realization as enabled by contemporary Information Technology tools and patterns. As was stated at the outset, the state of the art in Enterprise GIS advances with waves of technological innovation in IT generally.
Modern Enterprise GIS (at the time of writing, Q3 2018) is most commonly implemented using a multi-tiered, database driven, services-oriented architecture (SOA) in which maps, data, and tools are exposed as REST or SOAP endpoints over HTTP(S), and then further wrapped in customized applications. Both commercial and open-source software tends to follow this general pattern of data persisting in a relational, spatially enabled database; cartography can be done using both full-featured GIS clients and increasingly through lightweight web mapping portals; maps and functionality can be delivered on the web as services directly to other applications, or as applications targeted to the end user user cases, which often can be developed from templates with little or no programming.
Increasingly, cloud-centric patterns (Software-as-a-Service and Platform-as-a-Service) are being incorporated into Enterprise GIS implementations. In PaaS implementations, organizations run GIS software in virtual machines that they provision from the elastic, scalable compute, storage and networking capacity on public cloud providers’ infrastructure (an example of this would be Amazon Web Services or Microsoft Azure). In this pattern, the organization is still responsible for operating and maintaining all the software components of its Enterprise GIS. In a SaaS implementation, GIS functionality is delivered to an organization without said organization having any awareness of, or responsibility for, the underlying infrastructure and software components. Many, if not most enterprise GIS implementations are hybrids, incorporating, as appropriate for their particular context, on-premises infrastructure, PaaS, and SaaS cloud resources, frequently integrated with one another into a cohesive system of systems that has been architected to further that organization’s objectives.