Introduction to Geospatial Data

GISC 1479 80369 DIL 003 (4-3-3) - Professor Sean Moran, GISP

Austin Community College - 2024 Summer Semester

Class Meets

This is a Distance Learning (DIL) asynchronous Competency-Based Education (CBE) online course. There are no mandatory class meetings, but the instructor will record Kick-Off Meeting videos at the beginning of the semester and before each competency for students to watch asynchronously.

There are four competencies (i.e. modules), each with three topics. Students should complete competency topics, test, and project by the assigned dates as listed in the Course Schedule and Outline at the end of this syllabus.

Contact Information

Sean Moran will be the instructor for Introduction to Geospatial Data.

Sean Moran is a Professor of GIS. Formerly the ACC GIS Department Chair; he has over 25 years of professional planning, Geographic Information Systems (GIS), and Global Positioning Systems (GPS) experience. His experience as an educator, manager, coordinator, supervisor, and analyst give him a comprehensive base of knowledge on which to draw. Prior to coming to Austin Community College (ACC) in 2009, Mr. Moran taught applied GIS to graduate-level planning students in the School of Architecture at the University of Texas. He has a BS in Urban Forestry from Texas A&M University and an MS in Urban Planning from the University of Texas. Mr. Moran’s contact information is listed below:

Sean Moran

GIS Professor

Austin Community College, Highland Campus

6101 Highland Campus Dr. Building 2000, ACC Inc

Austin, Texas 78752

email smoran@austincc.edu

office hours

Thursdays from 6:00 to 10:00 PM via video call appointments scheduled by clicking on this booking appointment and selecting a slot or slots. Optionally, students can contact me via email to schedule appointments outside office hours as needed.

Course Description

Geospatial data identify the geographic locations of features on Earth. This course introduces students to geospatial data types that can be used to create maps. Students will complete progressive exercises and projects that collect, assimilate, and analyze geospatial and related data stored in a text file, spreadsheet, database, and geodatabase. Topics include tabular data, data types, relational data, queries, schema, geospatial data, and geodatabases.

Transferability of workforce courses varies. Students interested in transferring courses to another college should speak with their Area of Study (AoS) advisor, Department Chair, and/or Program Director.

Course Rationale

Introduction to Geospatial Data is designed to provide students with an understanding of the methods and theories of geospatial data that will allow students to apply GIS knowledge and skills to everyday life and their chosen careers, to apply the course towards a certificate or an associate’s degree at Austin Community College, and to prepare them for success in upper division courses in GIS at other institutions.

Prerequisite

None.

Required Texts/Materials

Readings assigned will be available in electronic format for free via the course website and Internet. Most lectures include an assigned reading that should be completed before lecture. Students should come to lectures prepared to discuss the reading assignment.

All students will use ACC email, Google Workspace apps. and ArcGIS Pro 3.2 GIS software to complete demonstrations, exercises, projects, quizzes, and tests - see Installation Steps. Classroom students will have access to a workstation with ArcGIS Pro, high-speed Internet, and dedicated server storage space. Online students are required to have the following:

• A desktop or laptop computer capable of running ACC provided ArcGIS Pro - see System Requirements;
• A reliable Internet connection;
• An external USB flash or hard drive with at least 2GB of storage; and
• Web camera, microphone, and speakers.

If you do not have one or more of these, please contact the instructor to explore ACC resources for possibly acquiring any missing items.

Instructional Methodology

This course is taught asynchronously online with a combination of lecture slides, demonstrations, videos, quizzes, tests, and projects.  Students will complete the lab work using an ACC lab workstation or their own computer. Students should expect to spend an average of 6 hours per week attending lectures, working on labs, completing assignments and projects, and studying.

Course materials and communication are available on ACC’s Blackboard website (http://acconline.austincc.edu) In order to log into Blackboard, you will need your ACCeID.  Your ACCeID will consist of the first letter of your official first name followed by your 7-digit ID number and can be found on your ACC ID Card.

ArcGIS.com is to access maps, apps, and tools along with creating content and submitting work.  ArcGIS Online provides a common platform to find, share, and organize geographic content and to build GIS applications. It is a web resource hosted by ESRI, the company that makes ArcGIS software - the GIS software you will be using in this course and throughout your academic program at ACC. More information and details are available on the course website.

Students will use the Blackboard learning management system for assignment instructions, submitting assignments, and collaboration.

Distance Education

ACC distance education courses are every bit as academically challenging as on-campus courses, but many students discover that there are also unique challenges to online education. Common challenges that distance students encounter include lack of self-motivation, inability to focus, trouble maintaining accountability, being disorganized, inability to effectively communicate, poor time management, and failure to balance your educational and personal commitments.

You must be able to manage your time effectively and prioritize to meet deadlines and stay on track with your coursework. Successful distance students are self-starters who understand the commitment and discipline required to thrive in an online environment. You must be an active learner who asks questions when you do not understand something. Your instructor cannot see you, so you need to “speak up” if you have problems by contacting your instructor right away; otherwise, there is no way for your instructor to know that something is wrong.

Student Learning Outcomes

Students will learn how to compile, analyze, and present geospatial data while emphasizing the value of visual communication. Students will learn these basic geospatial concepts using industry standard GIS technology.

WECM Student Learning Outcomes

The Workforce Education Course Manual (WECM) is a web-based inventory of current workforce education courses and outcomes published by the Texas Higher Education Coordinating Board  for Texas public two-year colleges. WECM courses are created and maintained by teams of instructional specialists from Texas college with expertise in the subject areas. By the end of this course, the student will be able to:

• Explain basic concepts of using GIS in mapping the earth in spatial terms and populating the GIS's system to access data
• Create and access data in the GIS's system using an appropriate software package
• Develop and print maps with industry standard legends
• Operate industry standard GIS packages on a personal computer
• Capture positional and attribute information with correct and accurate geographic referencing
• Convert geographic information among several coordinate systems
• Acquire GIS's system information from databases, existing maps, and the Internet
• Annotate output for finished maps, documents, and reports.

GTCM Student Learning Outcomes

The Geospatial Technology Competency Model (GTCM) is an industry model framework published by the US Department of Labor Employment and Training Administration (ETA) to identify industry-specific technical competencies. By the end of this course, the student will be able to:

• Develop conceptual, logical, and physical geospatial data models in response to user requirements and within the life cycle of a GIS project or work-flow of a GIS program.
• Select, evaluate, and document primary and secondary data according to original scale, coordinate system, precision, accuracy, completeness, currency, source, and fitness for use.
• Edit, query, convert, rectify, georeference, project, transform, geoprocess, validate, import, export, backup, and archive data while utilizing file and data standards and assuring quality.
• Interpret user requirements to select, install, maintain, and license desktop GIS and GIS-related software.
• Interpret user needs to generate GIS products with a defined purpose, target audience, and appropriate medium.
• Create data, maps, and reports with GIS-industry recognized data standards, cartographic conventions, and reporting methods.
• View, locate, query, geoprocess, and analyze spatial data utilizing GIS software.

SCANS Competencies

The Secretary Commission on Achieving Necessary Skills (SCANS) is a commission appointed in 1990 by the Secretary of the US Department of Labor Lynn Martin to develop a list of skills "that high-performance workplaces require and that high-performance schools should produce." By the end of this course, the student will demonstrate the following workplace competencies and foundation skills:

1. Workplace Competencies - Effective workers can productively use:
   1. Resources – They know how to allocate (C1) time, (C2) money, (C3), materials, and (C4) staff
   2. Information – They can (C5) acquire and evaluate data, (C6) organize and maintain files, (C7) interpret and communicate, and (C8) use computers to process information.
   3. Interpersonal skills – They can (C9) work on teams, (C10) teach others, (C11) serve customers, (C12) lead, (C13) negotiate, and (C14) work well with people from culturally diverse backgrounds,
   4. Systems – They (C15) understand social, organizational, and technological systems, (C16) they can monitor and correct performance; and (C17) they can design or improve systems.
   5. Technology – They can (C18) select equipment and tools, (C19) apply technology to specific tasks and (C20) maintain and troubleshoot equipment.
2. Foundation Skills - Competent workers in the high-performance workplace need:
   1. Basic Skills – (F1) reading, (F2) writing, (F3) arithmetic and (F4) mathematics, (F5) listening and (F6) speaking.
   2. Thinking skills – (F7) to think creatively, (F8) to make decisions, (F9) to solve problems, (F10) to visualize, (F11) the ability to learn, and (F12) to reason.
   3. Personal Qualities – (F13) individual responsibility, (F14) self-esteem, (F15) sociability, (F16) self-management, and (F17) integrity.

Course Evaluation/Grading System

Grading components are based on the successful and timely completion of quizzes, tests, and projects.

The final grade is based on a total of 100 points and the following grade scale:

Exercises

Exercises are designed to apply the concepts and techniques discussed and demonstrated in lecture. The instructor will be available to assist students with the exercises and discuss their practical application. Although not a formal grading component, completing the exercises will improve your skills and make you more proficient in completing the quizzes, tests, and projects.

Quizzes

Each week’s topic includes a supporting quiz with 10 questions - 5 conceptual and 5 practical and can be retaken as many times as desired prior to the test. The Quizzes Grading Component is calculated by averaging the top 10 of 12 total quizzes. Quizzes are structured to measure comprehension of the weekly lecture and exercises. Successfully completing and studying the quizzes will improve your test scores.

Tests

There are three subject matter tests and one cumulative test that will be administered during class time or office hours. Tests are NOT open book or notes. Each subject matter test will consist of 20 questions - 10 conceptual and 10 practical. The cumulative test will consist of 40 questions - 20 conceptual and 20 practical. Each question is worth 0.5 points. Tests are structured to measure and reinforce overall comprehension. 

Projects

There will be four projects assigned during the semester. Each project will include a work breakdown structure (i.e. list of tasks) and description of the final deliverable that builds on the material covered in lectures, demonstrations, and exercises. The first two projects will include a list of tasks supported by step-by-step instructions. The third and fourth projects will include a list of tasks supported by more general instructions. Each project is worth 10 points. The projects are designed to build the skills and confidence required to complete real-world applications using GIS.

Course Policies

Please see the following course policies regarding attendance/participation, withdrawals, missed or late work, and incompletes.

Attendance/Participation

While not a formal grading component, accessing Blackboard and completing curriculum according to the Course Schedule and Outline will have a strong influence on your final grade. I will monitor due dates and Blackboard activity in case there are any questions about your final grade and commitment to this course. You are responsible for reading and responding to any announcements made on Blackboard. 

Withdrawals

The last day to withdraw from this course for the Summer 2024 session is Monday, July 22, 2024. It is the responsibility of each student to ensure that his or her name is removed from the roll should they decide to withdraw from the class. The instructor does, however, reserve the right to drop a student should they feel it is necessary.  If a student decides to withdraw, they should also verify that the withdrawal is submitted before the Final Withdrawal Date. Students are also strongly encouraged to retain a copy of the withdrawal form for their records.

Students who enroll for the third or subsequent time in a course taken since Fall 2002, may be charged a higher tuition rate for that course.

State law permits students to withdraw from no more than six courses during their entire undergraduate career at Texas public colleges or universities without penalty.  With certain exceptions, all course withdrawals automatically count toward this limit.  Details regarding this policy can be found in the ACC college catalog. 

Missed or Late Work

Any missing or late work cannot receive a grade higher than the lowest grade awarded to a student who turned in the same assignment or project on-time. For example, if the lowest grade for all projects submitted on-time is 80%; then a student who submits a perfect project after the due date would receive an 80%.

Incomplete

The instructor may award a grade of “I” (Incomplete) if a student is unable to complete all of the requirements for a course.  An incomplete grade cannot be carried beyond the established date in the following semester. The completion date is determined by the instructor but may not be later than the final deadline for withdrawal in the subsequent semester.

College Policies

Please see the ACC website for college policies regarding academic integrity, ACC email, campus carry, counseling, coronavirus, discrimination, privacy, safety, student complaints, students rights and responsibilities, student support services, testing services, and more.

Course Schedule

While the instructor reserves the right to change the course schedule as required during the semester; any changes will be discussed with students and announced in Blackboard. Students should complete competency topics, test, and project by the assigned dates.

* Denotes test and project deliverable due dates.

Course Outline

1. Competency - Collect, transform, and visualize tabular data using best practices.
   1. Topic: What is Data? - Explain how data is collected, stored in the tabular model, and analyzed to create information and knowledge.

Performance Criteria

1. Explain the relationship between data, information, and knowledge
2. Define data.
3. Differentiate between primary and secondary data.
4. Explain nominal, ordered, interval, and ratio data types.
5. Describe how tables are structured.

1. Topic: Transforming Data - Use spreadsheet functions to transform text, numeric, and geospatial data.

Performance Criteria

1. Describe how data functions are used to transform data.
2. Differentiate between concatenate and parse text functions.
3. Describe the order of operations for mathematical functions.
4. Explain how logical functions can test value expressions.
5. Use spreadsheets to transform data.

1. Topic: Visualizing Data - Visualize data in tables, charts, maps, and dashboards using best practices.

Performance Criteria

1. Apply Ed Tufte’s Guidelines for Visualizing Data.
2. List best practices in creating tables.
3. List best practices in creating charts.
4. List best practices in creating maps.
5. List best practices in creating dashboards.
6. Create and publish a dashboard with tables, charts, and maps.

1. Competency - Assimilate normalized data into an entity-relationship modeled RDBMS using ETL tools.
   1. Topic: Data Models - Model tabular and geospatial data using conceptual, logical, and physical entity-relationship diagrams.

Performance Criteria

1. Describe the components of the Entity-Relationship Model.
2. Label the symbology used in an Entity-Relationship Diagram.
3. Explain conceptual, logical, and physical data models.
4. List the three basic geospatial data models.
5. Use an Entity-Relationship Diagram to model a database.

1. Topic: Databases - Create database schema and relate tables in a Relational Database Management System (RDBMS).

Performance Criteria

1. Compare and contrast spreadsheets vs. databases.
2. Explain what database schema is.
3. Differentiate flat-file tables from relational tables.
4. Identify the three cardinal relationships in an RDBMS.
5. List and differentiate the three types of geodatabases.
6. Create table joins and relates in GIS.

1. Topic: Data Assimilation - Use Extract, Transform, Load (ETL) tools to assimilate vector, raster, and triangulated data in a geodatabase with subtypes and attribute domains.

Performance Criteria

1. Explain how ETL is used to assimilate data.
2. Describe how vector data is modeled in GIS.
3. Describe how raster data is modeled in GIS.
4. Describe how triangulated data is modeled in GIS.
5. Create geodatabase subtypes and attribute domains in GIS.
6. Use ETL tools to assimilate data in GIS.

1. Competency - Create, edit, and document geospatial data using point, line, and polygon construction tools, snapping, topology and metadata.
   1. Topic: Data Creation - Create and edit geospatial data using basic point, line, and polygon construction tools.

Performance Criteria

1. Explain what manual heads-up digitization is.
2. Explain what automated classification digitization is.
3. Describe how vector points, lines, and polygons are structured.
4. Describe how raster grids are structured.
5. Explain the role of editing environment in creating and modifying vector and raster data.
6. Create and modify vector data using GIS.

1. Topic: Data Editing - Create and edit geospatial data using advanced point, line, and polygon construction tools.

Performance Criteria

1. Provide examples of common raster and vector editing tools
2. Explain how geodetic features differ from planar features
3. Explain how Z and M coordinates enhance vector feature geometry
4. Create geodatabase contingent values in GIS
5. Use COGO to create geospatial data
6. Use advanced point, line, and polygon construction tools to create and edit geospatial data

1. Topic: Topology - Explain how network, geodatabase, and map topology are used in GIS.

Performance Criteria

1. Describe what topology is and how it’s used in GIS
2. List the topological elements that model connections between geospatial features
3. Differentiate between a directed and undirected network
4. Differentiate between geodatabase and map topology
5. Explain what metadata is
6. Create geodatabase and map topology in GIS

1. Competency - Use the field data collection workflow to acquire, assimilate, and produce geospatial and attribute data deliverables.
   1. Topic: Location Data - Explain how GPS and DGPS create location data.

Performance Criteria

1. Differentiate between triangulation and trilateration.
2. Describe the space, control, and user segments of GPS.
3. List types of GPS error that degrade your positional accuracy.
4. Explain how differential GPS works.
5. Differentiate between image data and a mosaic dataset.
6. Configure GIS data for collecting GPS field data.

1. Topic: Field Data - Collect GPS field data using the field data collection workflow to minimize errors.

Performance Criteria

1. Describe the field data collection workflow.
2. Explain how to plan and configure a mission.
3. List types of feature-level metadata collected with GPS.
4. Explain how to validate, assimilate, and backup field data.
5. Collect spatial features and attribute values in the field.

1. Topic: Data Automation - Describe and demonstrate the benefits of using data automation in GIS.

Performance Criteria

1. List the benefits of automating work.
2. Describe the types of data processes that can be automated.
3. Differentiate desktop, enterprise, and cloud-based automation.
4. Describe different GIS data automation processes.
5. Automate a data process using GIS.

See Course Requirements for Readings, Course Subjects, and Learning Outcomes.

See Course Requirements for Readings, Course Subjects, and Learning Outcomes.

See Course Requirements for Readings, Course Subjects, and Learning Outcomes.