The ACM/AIS MSIS 2016 Global Competency Model has now been approved by both the ACM Education Board and Council and AIS Council. The approved version of the document is available as a CAIS article here .
The purpose of this site is to provide general information about the MSIS 2016 revision process and to solicit feedback from Information Systems and general computing communities regarding the deliverables of the joint ACM/AIS MSIS 2016 task force and the project in general.
The purpose of this revision process is to carefully review the MSIS 2006 curriculum recommendation and revise it so that it can provide up-to-date guidance to schools, departments, and individual faculty members designing master’s level curricula and courses in Information Systems.
The MSIS 2016 revision process was formally launched in December 2014 / January 2015 after a preliminary review task force had recommended this action to ACM and AIS in August 2013, both organizations had decided to include it in their budgets for the 2014-2017 fiscal years, and the task force had been named in 2014 through an open call to the IS community. The task force released its first public deliverable in June 2015, the second one in March 2016, and a comprehensive MSIS 2016 draft in July 2016. After the final round of revisions, the model was approved by ACM Education Board and Council in November 2016 and by AIS Council in December 2016.
MSIS 2016 Revision Process 
Congratulations to the ACM/AIS MSIS 2016 Task Force for the comprehensive draft curriculum recommendation that you presented for comments at the AMCIS 2016 conference in San Diego. The competency-oriented framework you propose is a significant step forward in the development of curriculum guidelines in this and related fields, including geographic information science.
I’m grateful for the opportunity to suggest how the addition of a few explicit references to geolocation (a.k.a. spatial) data and analysis may strengthen the document by increasing its relevance to the more than 350,000 organizations worldwide whose IS staffs are responsible for managing and operating geographic information systems technologies. The significance of the suggested additions is the recognition of the distinctive properties of spatial data, and the implications of those properties on data acquisition, management, processing, analysis, and presentation.
First l suggest a few specific additions, then follow with a general justification below.
Competency Areas
p. 29: As we discussed in your panel discussion on Friday August 12, the three high-level competencies listed under Competencies in the Area of Data, Information and Content Management effectively subsume geolocation data. I understand that you intend competency areas to be most stable and adaptable to rapidly evolving technologies and professional practices, so it makes sense not to call out a particular data type here.
Competency Categories
At this level, I suggest that it is appropriate to call out the distinction between spatial and non-spatial data. For example, on p. 34-35 Competency Categories under the Data, Information and Content Management area, Competency 21 could state:
– Integrating and preparing *spatial and non-spatial data* captured from various sources for analytical use
This fundamental distinction is sure to persist into the foreseeable future, and therefore does not undermine the stability of the category. Moreover, it clarifies the point the competencies associated with “integrating and preparing spatial and non-spatial data” are substantively different.
Competencies 22 and 22a (Selecting and using appropriate analytics method, and Analyzing data using advanced contemporary methods) could also call out distinctions between analytical methods for spatial and non-spatial data, but I’m satisfied that that point will be implied if the previous suggested addition is included.
In regard to the competency category Ethics, Impacts and Sustainability (p. 35), I believe that the challenges associated with *geolocation privacy* are so serious and complex (particularly but not exclusively in the healthcare domain) that it deserves to be called out explicitly. In addition, I suggest that one competency refer specifically to a professional ethics code, such as the ACM Code of Ethics and Professional Conduct (https://www.acm.org/about-acm/acm-code-of-ethics-and-professional-conduct).
Individual Foundational Competencies
Mathematical and statistical competencies should be expanded to include *spatial analysis* competencies. Specialized analytical methods such as buffers, overlay, point pattern analysis, network analysis and many others are commonly performed on geolocation data, but are not commonly included in mathematical or statistical curricula. Omitting them from MSIS 2016 would suggest erroneously that they are irrelevant to IS professionals.
Domain Competencies
Location analytics (a.k.a. spatial analysis) are distinctive competencies that are highly relevant to at least two roles, yet are absent from the current draft.
12.3.1 Business competency #4: “Analyzing and presenting *both spatial and non-spatial data* to provide support for effective analysis….” This seemingly minor addition clarifies that competencies associated with analysis and presentation of spatial (geolocation) data are fundamentally distinct from those employed for non-spatial data.
12.3.2 Health care competencies: Here MSIS 2016 refers to competencies cultivated by the Master of Health Informatics program University of Wollongong. While *location analytics and spatial epidemiology* are important aspects of contemporary health analytics, neither is called out explicitly.
Justification
In 1992, Michael Goodchild head of the NSF-funded National Center for Geographic Information Analysis at the University of California Santa Barbara, published a seminal paper that called “Geographical Information Science” (http://dx.doi.org/10.1080/02693799208901893). In it, he made a compelling case that the distinctive properties of geographic (or spatial or location) data warrant a scientific enterprise that is distinct from, but closely related to, Information Science. By 1995, a University Consortium for Geographic Information Science had formed. UCGIS published a Geographic Information Science and Technology Body of Knowledge in 2006 (https://blogs.esri.com/esri/gisedcom/2012/10/08/bok/), which emulated the ACM BoK. A visualization of the “GIS&T domain” on p. 6 of UCGIS BoK depicts the close relationship between GIScience and IS. My hope in these suggestions is that a symmetrical relationship may be suggested within the MSIS 2016, and that that relationship may be strengthened to society’s benefit in years to come.
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