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GEOG 581 - Spatial Data Science Ethics

This is a sample syllabus.

This sample syllabus is a representative example of the information and materials included in this course. Information about course assignments, materials, and dates listed here is subject to change at any time. Definitive course details and materials will be available in the official course syllabus, in Canvas, when the course begins.

Overview

GEOG 581 prepares current and aspiring professionals to recognize, analyze, and address legal and ethical issues in the GIS&T (geospatial) field.

GEOG 581 is for students who are concerned about the ethical implications and social impacts of geospatial technologies and methods. It traces the roots of Spatial Data Science Ethics in moral philosophy, professional ethics frameworks, and critical studies in the geospatial field. Students analyze non-trivial ethical case studies in which right and wrong actions are not clear-cut. They compare and critique relevant legal and policy issues in the U.S. and abroad. They evaluate the organizational ethics of firms and agencies (including current or potential employers) that provide spatial data science products and services, and they create and refine a proposed “ethics of digital care” for leading balanced digital lives. Finally, they develop a research Term Project to conceptualize and interrogate ethical issues related to their own research work. Course activities include readings, case study analyses, bi-weekly presentations, class discussions, and scholarly Term Project written reports.

Objectives

Students who successfully complete the course will be prepared to:

  • Practice academic integrity and ethical conduct of research;
  • Apply moral reasoning theories to ethical challenges encountered in research and professional practice; 
  • Compare and critique pertinent professional ethics codes, laws, and regulations; and
  • Create original, publishable written inquiries, critiques, and case study analyses that advance Spatial Data Science Ethics.

Required Materials

Typically, there are no required materials for this course. If this changes, students will find a definitive list in the course syllabus, in Canvas, when the course begins.

Prerequisites

Consent of the instructor or advisor is required for entry into this class.

Expectations

According to Penn State’s Faculty Senate, "For the typical student, a total of forty-five (45) hours of work planned and arranged by the University faculty is required to gain 1 credit." This three-credit course is designed to engage you in approximately 135 hours of purposeful activity leading to fulfillment of the educational objectives outlined below. You should therefore expect to devote 13-14 hours of effort per week to readings, writing assignments, presentations, and communications.

Major Assignments

Evaluation methods

To achieve the objectives proposed above, students will:

  1. Complete Penn State’s required graduate research training for human subjects research;
  2. Formally analyze ethics case studies chosen from the NSF-sponsored collection curated at gisethics.org, the Princeton Dialogues on AI and Ethics, and the Data Ethics Cases published by the Council for Big Data, Ethics, and Society;
  3. Reference and discuss pertinent ethics codes, laws, and regulations in case study analyses;
  4. Present and discuss case study analyses and related inquiries; and
  5. Prepare Term Projects consisting of original, publishable inquiries, critiques, and case studies.

Evaluation Grading

  1. Student Presentations (live and/or recorded) - 50% of total course grade
  2. Student Term Project Presentations – 17.5% of total course grade
  3. Class discussions - 15% of total course grade
  4. Instructor Presentations - 12.5% of total course grade
  5. Successful completion of CITI training in Human Subjects Research and other assignments  – 5% of total course grade

Course Schedule

The class schedule will be posted in Canvas at the beginning of the semester.