GEOG 588
Analytical Approaches for Spatial Data Science

GEOG 588: Syllabus

GEOG 588: Analytical Approaches in Spatial Data Science (Spring 2 2024)

This syllabus is divided into several sections. It is essential that you read the entire document as well as the material covered in the Course Orientation. Together these serve as our course "contract."

Instructor

Marcela Suárez
Assistant Teaching Professor
College of Earth and Mineral Sciences
The Pennsylvania State University

Campus address
John A. Dutton e-Education Institute
2217 Earth and Engineering Sciences Building
College of Earth and Mineral Sciences, The Pennsylvania State University

  • E-mail: aks7396@psu.edu Please use the Canvas course e-mail system.
  • Office Hours: By appointment

NOTE: I will read and respond to e-mails and discussion forums at least once per day during the workweek (Monday through Friday). You may see me online occasionally on the weekends, but please don't count on it!


Course Overview

Geography 588 is a course in the Master of Geographic Information Systems and Master of Science in Spatial Data Science programs. This section is being offered to students around the globe through Penn State's World Campus. It is a "paced" course, which means that there are established start and end dates and that you will interact with other students throughout the course. The course is 10 weeks in length (plus a required "Orientation Week"). The course is organized around six lessons, which include short weekly projects (due in weeks 1, 2, 3, 4, and 6), a short presentation, and a more substantial term project pursued through all ten weeks of the course. Weekly lessons include associated readings and discussions.

This course focuses on theoretical discussions in spatial data science, as well as on applying a range of spatial data science skills and tools to solve real-world problems and model geographic phenomena. This includes reading, writing, and working with novel types of geographic data, and making static and interactive maps. Students will read, discuss, and synthesize research articles and develop coding solutions for data science tasks through a series of lab exercises. Discussion forums will provide a platform for students to discuss the readings and address coding challenges and problems in a collaborative framework. Exercises using the tools introduced in the course will provide students an opportunity to troubleshoot and debug their code while creating reproducible programming/coding workflows. Students will apply concepts presented in the readings to compare existing spatial data science methods in order to select the appropriate methods to complete their term project.

This is a paced course, meaning that there is an established start and end date, and that you will interact with other students throughout the course. The course is 10 weeks in length (plus an "Orientation Week" preceding the start of the course). Use of the course website is required.

Each lesson should require 12-15 hours to complete, depending on the speed at which you work. See the Course Schedule section of this syllabus, below, for a schedule of the lessons and course projects. If you find yourself taking longer or having trouble with the concepts, please ask for help either on the message boards (there is an excellent chance someone else has the same question - it might already have been asked & answered there) or via email.


Prerequisites

GEOG 588 requires GEOG 485 or GEOG 487 or equivalent experience as a prerequisite.

Students who do not meet these prerequisites may be disenrolled according to Administrative Policy C-5 if they do not have the proper prerequisite override. If you have not completed the listed prerequisites, then promptly consult with the instructor if you have not done so already. Students who add the course after being disenrolled, according to this policy, are in violation of the Student Code of Conduct.


Course Goals and Objectives

When you successfully complete this course, you will be prepared to:

  • Evaluate and justify the selection of the appropriate methods to complete Spatial Data Science tasks.

  • Develop key scientific programming skills that integrate state-of-the-art coding practices essential for spatial data science.

  • Synthesize, analyze, and visualize multiple types of spatial data for real-world problem-solving.

  • Create troubleshooting and debugging strategies (tools, mindsets, reproducible examples, resources) to address coding problems.


Course expectations

On average, most students spend ten to fifteen hours per week working on course assignments. Your workload may be more or less depending on your study habits.

I have worked hard to make this the most effective and convenient educational experience possible. The Internet may still be a novel learning environment for you, but in one sense it is no different from a traditional college class: how much and how well you learn is ultimately up to you. You will succeed if you are diligent about keeping up with the class schedule and if you take advantage of opportunities to communicate with me as well as with your fellow students.

Specific learning objectives for each lesson and project are detailed in each lesson. The class schedule is published below and in Canvas (the course management system used for this course).


Required Course Materials

Required textbooks

This course has no required textbooks.

Recommended textbooks

Supplemental material

Other textbooks that you might find helpful are:

Reserve materials and location
This course uses the library Electronic Reserves (E-Reserves). More information about how to access this content is available in the course orientation.

Online lesson content
All (other) materials needed for this course are presented online through Canvas. In order to access the online materials, you need to have an active Penn State Access Account user ID and password (used to access the online course resources). If you have any questions about obtaining or activating your Penn State Access Account, please contact  Penn State IT Service Desk for World Campus students or Penn State IT Get Support (for students at all other campus locations).

Software
R Studio and R the free statistical analysis software package.
GitHub an Internet hosting service for software development. [Optional]


Assignments and Grading

Students earn grades that reflect the extent to which they achieve the learning objectives, listed above. Grades will be based on percentages assigned to each of several components of the course, and opportunities to demonstrate learning include the following:

  • 1 Personal Introduction Video (25 points)
  • 7 Reading Discussions: (6 worth 30 points each + 1 worth 20 points = 200 points)
    You will be expected to participate in weekly discussions, where you will demonstrate your understanding of the lesson content and readings.
  • 6 Technical Discussions: (25 points each (Drop lowest) = 125 points)
    You will be expected to participate in technical discussions, where you will demonstrate your understanding of the lab assignments.
  • 5 Lab Assignments: (1 lab worth 25 points + 4 labs worth 50 points each = 225 points)
    You will submit lab assignments where you will demonstrate your coding skills.
  • 2 Reflective Practices: (25 points each = 50 points)
    You will complete two written reflections on particular questions related to the course content and activities.
  • 1 Lightning Talk: (150 points)
    You will present a talk on a topic of your choice.
  • 1 Final Project: (225 points)
    You will complete a final project on a topic of your choice.
    • Topic Selection and Discussion (20 pts), Term-Project Proposal (20 pts), Peer Review (25 pts), Rough Draft (40 pts), Final Draft (120 pts)

Citation and Reference Style
The final project should use APA-style citations. The following page provides links to guides for a variety of styles Academic Integrity and Citation Style Guide.

It is important that your work is submitted in the proper format to the appropriate Canvas Assignment or Discussion Forum and by the designated due date. I strongly advise that you not wait until the last minute to complete these assignments—give yourself time to ask questions, think things over, and chat with others. You'll learn more, do better...and be happier!

Due dates for all assignments are posted on the syllabus and course calendar in Canvas.

    Breakdown of each assignment's value as a percentage of the total course grade.
    Assignment Percent of Grade
    Personal Introduction 2.5%    
    Reading Discussions 20.0%    
    Technical Discussions 12.5%    
    Lab Assignments 22.5%    
    Reflective Practice  5.0%    
    Lightning Talk 15.0%    
    Final Project 22.5%    

    I will use the Canvas grade book to keep track of your grades. You can see your grades in the grade book, too. Overall course grades will be determined as follows. Percentages refer to the proportion of all possible points earned.

    Make-up Examination Policy

    This course does not have any exams.

    Curve

    Grades will not be curved in this course.

    Grading Policy

    Grading Scale

    Letter Grade and Corresponding Percentage
    Letter Grade Percentages
    A 93 - 100 %
    A- 90 - 92.9 %
    B+ 87 - 89.9 %
    B 83 - 86.9 %
    B- 80 - 82.9%
    C+ 77 - 79.9 %
    C 70 - 76.9 %
    D 60 - 69.9 %
    F < 60 %
    X Unsatisfactory (student did not participate)
     

      Late Policy

      You are expected to submit all of your work on time, as scheduled; however, late completions are possible if arranged beforehand in the case of documented illness or emergency. If you find yourself falling behind, talk to the instructor *before* you miss a deadline, not after. Instructors are people too, and we understand that life happens. Late submissions must be submitted within 7 days of original due date unless approved by the instructor. All late submissions will incur a 5% per day penalty.


      Course Schedule

      imagePrintable Schedule

      Below you will find a summary of the primary learning activities for this course and the associated time frames. This course is ten weeks in length, with an orientation week preceding the official start of the course. The course is organized around six lessons. See our Syllabus/Calendar in Canvas for specific lesson time frames and assignment due dates.

      Weekly schedule: Lessons open on Wednesday, close on Tuesday, most discussions and assignments are due on Tuesday. Please see our Syllabus/Calendar in Canvas for specific due dates.

      NOTES:

      • See the Canvas Syllabus or Calendar for a full semester calendar of events.
      • Students who register for the course will have access to the online articles in Canvas.
      Lesson 1: Introduction to Spatial Data Science (1 week)
      Week 1 Lesson 1: Introduction to Spatial Data Science
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Submit your Personal introduction video
      • Participate in the Lesson 1 Reading Discussion forum
      • Submit Lab #1 - An Introduction to R assignment
      • Participate in the Lab #1 Technical Discussion forum
      • Begin the three parts of the Term Project Topic selection and Discussion (Due week 2)
      Lesson 2: Good Habits and Practices in Spatial Data Computing (1 week)
      Week 2: Lesson 2: Good Habits and Practices in Spatial Data Computing
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Participate in the Lesson 2 Part 1 Reading Discussion forum
      • Submit Lab #2 - Intro to Rmarkdown and Data wrangling assignment
      • Participate in the Lab #2 Technical Discussion forum
      • Complete the three parts of the Term Project Topic selection and Discussion
      Lesson 3: Data Visualization (1 week)
      Week 3: Lesson 3: Data Visualization
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Participate in the Lesson 3 Reading Discussion forum
      • Submit Lab #3 - Data Visualization assignment
      • Participate in the Lab #3 Technical Discussion forum
      Lesson 4. Working with Geographic Data (1 week)
      Week 4: Lesson 4: Working with Geographic Data
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Participate in the Lesson 4 Reading Discussion forum
      • Submit the Term-Project Proposal
      • Begin Lab #4 - Web Mapping assignment (Due week 5)
      • Begin the Lab #4 Technical Discussion forum (Due week 5)
      Lesson 5. Spatial Data Science Applications (1 week)
      Week 5: Lesson 5: Spatial Data Science Applications
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Submit Lab #4 - Web Mapping assignment
      • Participate in the Lab #4 Technical Discussion forum
      • Participate in the Lesson 5 Reading Discussion forum
      • Begin Lab #5 - Analyzing US Census Data assignment (Due week 6)
      • Begin the Reflective Practice 1 assignment (Due week 6)
      • Begin the Term Project Peer Review (Due week 6)
      Lesson 6. Working with US Census Data (1 week)
      Week 6: Lesson 6: Working with US Census Data
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Submit Lab #5 - Analyzing US Census Data assignment
      • Participate in the Lab #5 Technical Discussion
      • Participate in the Lesson 6 Reading Discussion forum
      • Submit the Reflective Practice 1 assignment
      • Submit the Term Project Peer Review
      Lesson 7. Common Methods in Spatial Data Science (2 weeks)
      Week 7: Lesson 7 (Part 1): Common Methods in Spatial Data Science
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Participate in the Lesson 7 Part 1 Reading (or Videos) Discussion forum
      • Submit the Term Project Rough Draft
      Week 8: Lesson 7 (Part 2): Common Methods in Spatial Data Science
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Begin the Lightning Talk assignment (Due week 9)
      Final Project (2 weeks)
      Week 9: Final Project (Part 1)
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Submit the Lightning Talk assignment
      • Participate in a discussion on your classmates' lightning talks.
      Week 10: Final Project (Part 2)
      Tasks:
      • Read the online lecture notes and the other online articles as indicated in the lesson
      • Participate in the Term Project Technical Discussion
      • Submit the Term Project Final Draft
      • Share your Term Project in the Discussion
      • Submit the Reflective Practice 2 assignment
      Graphic showing the information provided in the weekly tables above.
      GEOG 588 Graphic Calendar
      © Penn State University is licensed under CC BY-NC-SA 4.0

      Class Support Services

      Penn State Online offers online tutoring to World Campus students in math, writing, and some business classes. Tutoring and guided study groups for residential students are available through Penn State Learning.


      Course Policies

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      Academic Integrity

      This course follows the procedures for academic integrity of Penn State's College of Earth and Mineral Sciences. Penn State defines academic integrity as "the pursuit of scholarly activity in an open, honest and responsible manner." Academic integrity includes "a commitment not to engage in or tolerate acts of falsification, misrepresentation, or deception." In particular, the University defines plagiarism as "the fabrication of information and citations; submitting others' work from professional journals, books, articles, and papers; submission of other students' papers, lab results or project reports and representing the work as one's own." Penalties for violations of academic integrity may include course failure. To learn more, see Penn State's Academic Integrity Training for Students

      Course Copyright

      All course materials students receive or to which students have online access are protected by copyright laws. Students may use course materials and make copies for their own use as needed, but unauthorized distribution and/or uploading of materials without the instructor’s express permission is strictly prohibited. University Policy AD 40, the University Policy Recording of Classroom Activities and Note Taking Services addresses this issue. Students who engage in the unauthorized distribution of copyrighted materials may be held in violation of the University’s Code of Conduct, and/or liable under Federal and State laws.

      For example, uploading completed labs, homework, or other assignments to any study site constitutes a violation of this policy.

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      In order to receive consideration for reasonable accommodations, you must contact the appropriate disability services office at the campus where you are officially enrolled. You will participate in an intake interview and provide documentation. See documentation guidelines at Applying for Services from Student Disability Resources. If the documentation supports your request for reasonable accommodations, your campus’s disability services office will provide you with an accommodation letter. Please share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. You must follow this process for every semester that you request accommodations.

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      In case of weather-related delays or other emergency campus disruptions or closures at the University, this online course will proceed as planned. Your instructor will inform you if there are any extenuating circumstances regarding content or activity due dates in the course due to these delays or closures. If you are affected by a weather-related emergency, please contact your instructor at the earliest possible time to make special arrangements.

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      Technical Requirements

      For this course, we recommend the minimum technical requirements outlined on the World Campus Technical Requirements page, including the requirements listed for same-time, synchronous communications. If you need technical assistance at any point during the course, please contact the IT Service Desk (for World Campus students) or Penn State's IT Help Portal (for students at all other campus locations).

      Internet Connection

      Access to a reliable Internet connection is required for this course. A problem with your Internet access may not be used as an excuse for late, missing, or incomplete coursework. If you experience problems with your Internet connection while working on this course, it is your responsibility to find an alternative Internet access point, such as a public library or Wi-Fi ® hotspot.

      Mixed Content

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      Equations

      This course must be viewed using the latest version of Firefox, Safari, Chrome, or Edge. Internet Explorer is not supported. If you use any other browser, or if you are not using the latest version of your browser, some pages containing equations may not render properly. In addition, javascript must be enabled for equations to render properly. If you have any issues with equations not rendering properly, please update your browser to the latest version or try using a different browser. If you need additional technical assistance at any point during the course, please contact the HelpDesk (for World Campus students) or the IT Service Desk (for students at all other campus locations).

      Deferred Grades

      If you are prevented from completing this course within the prescribed amount of time for reasons that are beyond your control, it is possible to have the grade deferred with the concurrence of the instructor, following Penn State Deferred Grade Policy 48-40. To seek a deferred grade, you must submit a written request (by e-mail or U.S. post) to the instructor describing the reason(s) for the request. Non-emergency permission for filing a deferred grade must be requested before the beginning of the final examination period.  It is up to the instructor to determine whether or not you will be permitted to receive a deferred grade. If permission is granted, you will work with the instructor to establish a communication plan and a clear schedule for completion within policy.  If, for any reason, the coursework for the deferred grade is not complete by the assigned time, a grade of "F" will be automatically entered on your transcript.

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      Penn State is “committed to creating an educational environment which is free from intolerance directed toward individuals or groups and strives to create and maintain an environment that fosters respect for others” as stated in Policy AD29 Statement on Intolerance. All members of this class are expected to contribute to a respectful, welcoming, and inclusive environment and to interact with civility.

      For additional information, see:

      Attendance

      This course will be conducted entirely online. There will be no set class meeting times, but you will be required to complete weekly assignments with specific due dates. Many of the assignments are open for multiple days, so it is your responsibility to complete the work early if you plan to travel or participate in national holidays, religious observances or University approved activities.

      If you need to request an exception due to a personal or medical emergency, contact the instructor directly as soon as you are able. Such requests will be considered on a case-by-case basis.

      Mandated Reporting Statement

      Penn State’s policies require me, as a faculty member, to share information about incidents of sex-based discrimination and harassment (discrimination, harassment, sexual harassment, sexual misconduct, dating violence, domestic violence, stalking, and retaliation) with Penn State’s Title IX coordinator or deputy coordinators, regardless of whether the incidents are stated to me in person or shared by students as part of their coursework. For more information regarding the University's policies and procedures for responding to reports of sexual or gender-based harassment or misconduct, please visit Penn State's Office of Sexual Misconduct Prevention & Response website.

      Additionally, I am required to make a report on any reasonable suspicion of child abuse in accordance with the Pennsylvania Child Protective Services Law.


      Disclaimer

      Please note that the specifics of this Course Syllabus can be changed at any time, and you will be responsible for abiding by any such changes. All changes will be communicated to you via e-mail, course announcement and/or course discussion forum.