Visitors to Esri often pause for pictures beside an ivy-covered wall emblazoned with the word GEOGRAPHY in raised metal letters. The inscription speaks to an ingrained belief that geography offers a unique framework for organizing the world’s knowledge in a way that fosters better decision-making and a more sustainable future. Consistent with this belief, the education outreach team I lead at Esri does what we can to nurture geographic thinking and methods across the spectrum of academic disciplines.
That’s a big job. Disciplines have proliferated since the advent of the modern university in the 19th and 20th centuries. Consider this concept map of contemporary academic disciplines. Few disciplines depicted explicitly recognize geography, let alone GIS, as an integral way of understanding the world. Given the longstanding claim that a science of geographic information undergirds GIS (Goodchild 1992), you might suppose that Information Science is one of the disciplines that’s likely to appreciate the special properties of spatial data. If so, you’d be surprised to find that there’s precious little “G” is IS.
One of my team’s outreach activities this year was an engagement with the Americas Conference on Information Systems (AMCIS). AMCIS is an activity of the Association for Information Systems (AIS), a leading professional society of more than 4,000 members engaged in the study of information systems. During the event I was fortunate to participate in a session on the joint ACM/AIS “MSIS 2016” curriculum framework. In Fall 2014, the Association for Computing Machinery and AIS empaneled a working group to develop curriculum guidelines for Masters of Science degree programs in Information Systems. It is the fifth in a series of curriculum guidelines since 1972. This project is a further expression of the initiative begun in the 1960s by ACM to establish a body of knowledge and core curricula specifications for the computing disciplines. The GIS&T Body of Knowledge project initiated in the 1990s by the University Consortium for Geographic Information Science emulated those efforts intentionally.
Now available as a public discussion draft, MSIS 2016 represents a significant advance over earlier related efforts. In contrast to content-centered specifications (like the GIS&T BoK) that are organized as hierarchical “Knowledge Areas,” “Knowledge Units,” and “Topics,” MSIS 2016 consists of “Competency Areas” and “Categories,” “Individual Foundational Competencies,” and “Domain Competencies.” Its greater emphasis on what students are able to do with knowledge, rather than on knowledge for its own sake, likens MSIS 2016 the U.S. Department of Labor’s Geospatial Technology Competency Model.
The architecture of MSIS 2016 is illustrated above. The nine Core Competency Areas for Computing and IS Management subsume 88 Competency Categories. For instance, in the version of MSIS 2016 dated 8-18-2016, “Competencies in the area of Data, Information, and Content Management” includes the following “Pre-Masters” and “Masters” level competency categories:
Pre-masters level
- Explaining key data and information concepts and the data and information management lifecycle
- Capturing and structuring data and information requirements using appropriate conceptual modeling techniques
- Developing a logical level representation of data based on a conceptual model
- Implementing a database solution to serve systems consisting of multiple applications
- Using a contemporary data manipulation and retrieval language effectively
Master’s level
- Selecting appropriate data management technologies based on the needs of the domain
- Securing domain data and protecting user privacy and organizational intellectual property using appropriate technical solutions
- Designing and implementing a data warehouse using a contemporary architectural solution
- Creating a scalable infrastructure for large amounts of data using parallel and distributed technologies
- Developing and implementing organizational information management policies and processes
- Creating an information architecture for an organization
- Integrating and preparing data captured from various sources for analytical use
- Selecting and using appropriate analytics methods
- Analyzing data using advanced contemporary methods
- Designing and implementing architectures for organizational content management systems
Each Competency Category is illustrated with a set of examples. Example competencies associated with the category “Selecting and using appropriate analytics methods,” for instance, are:
- Select and apply advanced computational approaches to identify meaningful patterns and trends
- Build predictive models to support decision making activities
- Create visualizations of large complex data sets to understand meaningful patterns and trends
In the version of MSIS 2016 presented at the AMCIS conference (dated 7-15-2016), none of the Competency Categories or Examples included the terms “spatial,” or “location,” or even the suffix “geo.” I expressed concern about this omission during the working group’s briefing at the conference. The group kindly invited me to submit comments on their draft, which I did (and which they published at the MSIS 2016 website). Their open-mindedness is evident in the fact that they added the example “make explicit the spatial and temporal dimensions of information” to the Competency Category “Creating an information architecture for an organization” in the version of MSIS 2016 issued after AMCIS – the one dated 8-18-2016.
Why was “spatial” omitted from earlier versions of MSIS 2016, and why does it have only a token presence in the latest version? It’s not that the Working Group deferred to GIS curricula to cover the topic. On the contrary, the omission implicitly refutes the claim that the distinctive properties of spatial data warrant a separate but related Geographic Information Science. Spatial is hardly mentioned because it is considered “just another data type.”
The MSIS 2016 Working Group’s nod to spatial is a collegial gesture. But there are other hopeful signs that there may be a place for “G” in IS. One sign is the five young faculty members and graduate students who participated in the focus group I conducted at AMCIS, and who volunteered to serve as GIS ambassadors within their academic units. Another is the example of GI Scientist Brian Tomaszewski, who is successfully embedded in the IST Department faculty at Rochester Institute of Technology. If you’re aware of other examples, let us know. Chances are they already have access to Esri technology through their university site license. We’d like to help them make the most of it.
Goodchild, Michael (1992). Geographical information science. International Journal of Geographical Information Systems 6 (1): 31–45.
Joint ACM/AIS MSIS 2016 Task Force (2016). MSIS 2016: Global Competency Model for Graduate Degree Programs in Information Systems