Enterprise GIS is the implementation of GIS infrastructure, processes and tools at scale within the context of an organization, shaped by the prevailing information technology patterns of the day. It can be framed as an infrastructure enabling a set of capabilities, and a process for establishing and maintaining that infrastructure. Enterprise GIS facilitates the storage, sharing and dissemination of geospatial information products (data, maps, apps) within an organization and beyond. Enterprise GIS is integrated into, and shaped by the business processes, culture and context of an organization. Enterprise GIS implementations require general-purpose IT knowledge in the areas of performance tuning, information security, maintenance, interoperability, and data governance. The specific enabling technologies of Enterprise GIS will change with time, but currently the prevailing pattern is a multi-tiered services-oriented architecture supporting delivery of GIS capabilities on the web, democratizing access to and use of geospatial information products.
As GIS became a firmly established presence in geography and catalysed the emergence of GIScience, it became the target of a series of critiques regarding modes of knowledge production that were perceived as problematic. The first wave of critiques charged GIS with resuscitating logical positivism and its erroneous treatment of social phenomena as indistinguishable from natural/physical phenomena. The second wave of critiques objected to GIS on the basis that it was a representational technology. In the third wave of critiques, rather than objecting to GIS simply because it represented, scholars engaged with the ways in which GIS represents natural and social phenomena, pointing to the masculinist and heteronormative modes of knowledge production that are bound up in some, but not all, uses and applications of geographic information technologies. In response to these critiques, GIScience scholars and theorists positioned GIS as a critically realist technology by virtue of its commitment to the contingency of representation and its non-universal claims to knowledge production in geography. Contemporary engagements of GIS epistemologies emphasize the epistemological flexibility of geospatial technologies.
Epistemology is the lens through which we view reality. Different epistemologies interpret the earth and patterns on its surface differently. In effect, epistemology is a belief system about the nature of reality that, in turn, structures our interpretation of the world. Common epistemologies in GIScience include (but are not limited by) positivism and realism. However, many researchers are in effect pragmatists in that they choose the filter that best supports their work and a priori hypotheses. Different epistemologies – or ways of knowing and studying geography – result in different ontologies or classification systems. By understanding the role of epistemology, we can better understand different ways of representing the same phenomena.
Describe the characteristics of the Geography Markup Language (GML)
Explain the purpose, history, and status of the Spatial Data Transfer Standard (SDTS)
Identify different levels of information integration
Identify the level of integration at which the Geography Markup Language (GML) operates
Describe the geospatial elements of Earth science data exchange specifications, such as the Ecological Metadata Language (EML), Earth Science Markup Language (ESML), and Climate Science Modeling Language (CSML)
Import data packaged in a standard transfer format to a GIS software package
Export data from a GIS program to a standard exchange format
Explain why early attempts to store geographic data in standard relational tables failed
Evaluate the adequacy of contemporary proprietary database schemes to manage geospatial data
Describe standards efforts relating to relational extensions, such as SQL:1999 and SQL-MM
Evaluate the degree to which an available object-relational database management system approximates a true object-oriented paradigm
Describe extensions of the relational model designed to represent geospatial and other semistructured data, such as stored procedures, Binary Large Objects (BLOBs), nested tables, abstract data types, and spatial data types