Data Management and Life Cycle
(PA397C | INF385T | ECO395M)

Due dates are listed on Canvas. Late submissions are not accepted.

Assignment 1: Plagiarism test

The first assignment of this course is to pass the plagiarism test and obtain a certificate at the master and doctoral level. Plagiarism is a serious academic misconduct. You will receive zero grade on plagiarized work and there may be other consequences. We have been told not to do this maybe since primary school, and we are always assuming we know what plagiarism is. However, we may assume we know too much (e.g., Notable Cases of Plagiarism).

You do not need to take this test if you have comparable certification, but the validity of your certification needs to be approved by the instructor.

“All assignments in this course may be processed by TurnItIn, a tool that compares submitted material to an archived database of published work to check for potential plagiarism. Other methods may also be used to determine if a paper is the student’s original work. Regardless of the results of any TurnItIn submission, the faculty member will make the final determination as to whether or not a paper has been plagiarized” (Statement from the Faculty Writing Committee: Guidelines for Preventing Plagiarism).

For this assignment, please submit your certificate as a file.

Assignment 2: Annotation on weekly readings

You are required to read the reading materials before class, at least have one comment on each article, and respond to at least one comment from another classmate. This routine assignment uses online annotation platform, and is due before class day.

Log your annotations here for grading.

For this assignment, you only need to log your reading progress, no submission required.

Assignment 3: Customized learning

I have listed relevant DataCamp online modules after each week for your reference. You can also choose the chapters or modules of your interests. Each chapter is worth 3 points, you should complete at least 9 chapters.

This assignment has two sub-assignments:

  1. Planned chapters (3% points): Please submit a list of your planned chapters with expected due dates.
  2. Completion (27% points): Please submit all completion evidence in one single file (e.g., screenshots, certification file, etc.).

Assignment 4: Analysis of empirical studies

You are expected to present an analysis of 2-3 empirical studies published by the top journals in respective field using the knowledge learned from the reading materials. The empirical studies can be research reports, academic journal articles, or any other evidence-based and data-driven studies/projects. The materials of the empirical studies need to be uploaded to the online course folder at least a week before class, and slides (e.g., PowerPoint Slides) for presentation are required (no due date).

Example questions:

  • Research design questions: What is the research question? Where does the data come from? How does the author(s) operationalize the research question(s) using the data?
  • Workflow and replication questions: How does the author(s) organize the files? Is the study replicable? How can its reproducibility be improved?
  • Validation questions: How does the author(s) validate the data? Are the conclusions still valid if different datasets are used?
  • Critiques: How can the study be improved regarding its data selection, validation, and management? Are there any methodological flaws regarding its use of data? Are there any logical gaps between data and empirical analysis?

Rubric. Your presentation should clearly demonstrate the studies’:

  • Research question, research design (e.g., how abstract concepts are measured), and their relations with data (30%).
  • Data management, documentation, and reproducibility (30%).
  • Computational methods used, and how data is analyzed using these methods (overview is adequate; 30%).
  • Critiques (10%).
  • Keep your presentation within 30 minutes.

For this assignment, please submit your presentation slides as a file via Canvas.

Assignment 5: Client project

Your group are expected to work with a client to help them solve a data management problem. Over the past few years, we’ve successfully executed a multitude of data projects, enabling dozens of nonprofit organizations and government departments to meet their data management objectives. The presentations of some of these projects can be accessed here: 2019 Spring / 2020 Spring / 2021 Spring

Specific deliverables and milestones for this group project:

1. Project contract draft (5 points)

No required format for the contract. It should serve as a concrete plan and guideline for your team and an agreement between your team and client. It usually includes these components: project objective, deliverables, member responsibility, timeline, conditions of confidentiality, communication methods, signatures of team members and client representative, etc.

Submit the draft contract as a file via Canvas.

2. Project contract final (5 points)

Submit the final contract with all parties’ signatures via Canvas.

3. Final report and presentation (30 points)

Please submit your final report and presentation slides as files via Canvas.

  • Please limit your presentation to 30 minutes.
  • Your presentation will be evaluated by the class using this assessment scale.
  • The instructor will assess your presentation and final report using the same scale. The final grade for this assignment: students’ evaluation 30%, instructor’s evaluation 70%.
  • You will have a week to revise your final report and related files according the feedback received during presentation.
  • Please submit your presentation slides, a narrative final report, and any related files and appendix.
  • No required format for the final report. But it should detail all your work in a narrative format with relevant references cited. No required citation format as long as it is consistent. Font size 12, 1-inch margins, single-space, 10 pages maximum. You can add more content using an appendix. No required format and no page limit for the appendix.
  • If you have problems with uploading multiple files via Canvas, try to upload the files as a compressed file (e.g., .zip file). You can also send me your final files via email (not recommended, but okay). The general principle is to have multiple files in one place.

© Ji Ma