Data curation is the active and ongoing management of data throughout its lifecycle, in order to help us find, retrieve, understand, and use data, thus enhancing its value in our data-driven world. This course uses hands-on activities to teach strategies for active curation and management of data. We’ll cover a broad range of practical and theoretical issues in the emerging field of data curation, examining ideas related to research lifecycles, workflows, metadata, data preservation, and data ethics.
- Unit 1: Foundations of data
- Recognize how the data lifecycle relates to research and scholarly communication
- Understand the history and benefits of curating and sharing data
- Unit 2: Implementing data practices
- Develop the skills necessary to curate a dataset to support discovery, reuse, and preservation
- Unit 3: Data and society
- Critically analyze the legal, ethical, and privacy implications of data sharing and data reuse
The work of the course
This is a 3-credit course. According to the MSU Course Policy, a credit is the unit used in recording an amount of work and engaged effort represented in learning outcomes and verified by evidence of student achievement. Each credit hour represents a minimum of three class-oriented work hours (50 minutes of classroom instruction and an additional two hours of out-of-class engaged effort and work per student) each week during a 15-week (minimum) semester. One credit of achievement should approximate 45 hours of combined instruction and student work/engaged effort. At least an equivalent amount of work and engaged effort is required regardless of pedagogical format (lab, web-enhanced, on-line, condensed coursework, internships, studio, independent study, etc).
Required equipment for the course
This course requires access to a laptop, a text editor, and office software. Contact Jason or Sara if you don’t have access to a laptop.
Readings for the course
There is no textbook required for this course. Readings will be available in D2L under the week’s module.
|Unit 1: Foundations of data
|Defining data curation and the data lifecycle
|Week 1: January 14January 16
|Review syllabus and grade conditionsReview data lifecycle diagrams
|Why curate data?
January 21 and 23
|Internal and external sharing; value of data; FAIR principles for data sharing
January 28 and 30
|funding agency and journal data sharing policies Principles of scholarly communication, analysis of how data is reused
|Data in different disciplines
February 4 and 6
|How does the data change between disciplines? How do different disciplines curate and reuse data?
|Unit 2: Implementing data practices
|Metadata and data models
February 11 and 13
|Describing data; learning metadata standards and ontologies
|Data Stores (Relational, Flat-File, Graph)
February 18 and 20
|Creating data fields, key/value pairs; Linking data tables and entities
February 25 and 27
|Open data, restricted data, data citation
|Data Identifiers and Resolution techniques
March 3 and 5
|Understand the principles of addressing data (Protocols, Headers, URIs, etc.)
|Optimizing data for discovery
March 10 and 13
|Applying search engine optimization; Social media optimization, Semantic Web enhancements for data findability
|Spring break – no class
March 16 and 20
March 24 and 26
|File formats, preservation metadata, checksums, data backup
|Unit 3: Data and society
|Intellectual property, data licensing
March 31 and April 2
|Creative Commons, Open Data Commons
|Introduction to data ethics
April 7 and 9
|Big data, sensitive data, human subjects
|Research participant protections
April 14 and 16
|Consent procedures to facilitate data reuse. Data anonymization strategies.
|Open data as a public good
April 21 and 23
|Data refuge, data for the public good
|Wrap up and final project sharing
April 28 and 30
|Outreach and promotion for your dataset
Assignments and projects
Throughout the semester, you will complete both regular assignments and major projects. Full descriptions of assignments will be available in D2L.
Regular assignments include hands-on assignments and reflection papers.
Each major project will correspond to a learning unit. The projects will allow you to explore course topics more deeply, build momentum for your final project, and are designed to provide you with an opportunity to share your ideas and demonstrate your familiarity with the course concepts. The primary course project will be the creation of a data store and metadata for a dataset related to your discipline or a discipline of interest.
Project 1. Foundations of data
Identify a dataset (from a data repository, a dataset that you have collected, a dataset from a faculty member, etc.). Make a short (3-5 minute) video using Techsmith Relay that introduces your dataset to the class. (Full assignment instructions will be available in D2L)
Project 2. Implementing data practices
Describe, query, and preserve your dataset. We will be using a class-supported instance of the Datasette tool. Students will be asked to submit their dataset, add metadata, and run test queries on the data to ensure it is ready for reuse and applications. (Full assignment instructions will be available in D2L)
Final Project. Presenting your dataset
For our final project, you will demonstrate how you have prepared your data in Datasette for discovery, reuse, and preservation. Walk us through how your dataset meets the FAIR principles. What metadata did you include so that others can find and understand your data? How are you ensuring preservation into the future? Who might use the data in the future and how might they use it?
- Create a final deliverable that presents your curated dataset and answers the above questions. Deliverables could be: a poster or infographic; a video or live presentation; a zine, comic strip, or comic book.
(Full assignment instructions will be available in D2L)
At the middle of the semester, you will write a midterm self-evaluation that reflects on your work and contributions throughout the course. You will complete a similar self-evaluation at the end of the term. The self-evaluations are intended to serve as helpful reflective exercises in which you document your process and overall progress. The self-evaluations will not only inform our own evaluation of you, but will inform how we adjust the course itself as we progress together.
Instructions: Create a document that responds to the following questions. You are welcome to approach this self-evaluation either as a series of answers to each of these questions or as a less formal letter to us about the course and your work. Be honest and carefully consider your work thus far in the class.
1. Evaluate your participation during in-class discussions and exercises. How would you characterize your involvement in our discussions so far? What are your strengths and weaknesses in this regard? Have you read and thought through the readings? What could have used more work? How has your thinking evolved from one week to the next?
2. Have you completed all assigned work for the course?
3. What letter grade would you give yourself for the first half of this course and why? Consider preparedness, the strength of your written work, your participation in discussion, and your goals for the semester.
4. Having been a part of the course for a few weeks now, where do you see your personal learning going? What goals do you have for the second half of the course?
5. What questions do you have for us at this point? About the subjects of the class? About your work/progress this semester? Are there any aspects of your work that you would particularly like feedback on?
Instructions: Create a document with answers to each of the following questions. The questions here are less prescriptive than on the midterm self-evaluation, in order to give you the opportunity to reflect on the course in a way that feels appropriate to you.
1. Write a short evaluation of your performance in this class (up to 250 words), addressing the following sorts of questions: Were you prepared for each class week? Did you do all of the required readings and projects? How would you characterize your overall effort, interest, and commitment to the class? Did your engagement increase or decrease as the semester went along? How did you meet the goals for the course?
2. Write a brief description of the skills and concepts that you gained or built upon as a result of this class (up to 250 words). Are there skills or ideas that you still want to gain or discuss beyond what the class provided?
3. Tell us about your experience discussing ideas and sharing your projects with your peers. What went well? What methods helped with this dialogue? Did you encounter challenges?
4. What letter grade would you give yourself for the semester and why? Consider preparedness for class, the strength of your papers and projects, and your participation in discussions and class activities.
For this class, you will ultimately make a recommendation to us for your final grade based on your completion of “Grade Conditions” that are outlined below. While we will assign final grades (as officially required), you will evaluate your own work throughout the course through self-evaluations that will inform our evaluation of you. We have included grade conditions for A, B, and C (with lower grades at our discretion) that you can use as a reference in evaluating your own work.
Throughout the course we will not be assigning letter or number grades on individual assignments. We will give an overview signal ( ✔- , ✔, or ✔+ ) and include questions and comments that engage with your work. You will also be reflecting carefully on your own work and engaging thoughtfully with the work of your peers. The intention here is to create a more open and organic learning experience rather than a prescriptive grade-driven experience. If this process causes more anxiety than it alleviates, contact us at any point to talk about your performance in the course. If you are worried about your grade, your best approach will be to join the discussions, do the exercises and reading, and complete the projects with sincere interest. You should consider this course a “busy-work-free zone.” If an assignment does not feel productive, we can find ways to modify, remix, or reimagine the instructions.
|What an “A” grade looks like
|What a “B” grade looks like
|What a “C” grade looks like
|Projects and reflection papers
Your projects and reflection papers show:
Advanced understanding of the course topics, including regularly making connections between the readings, information learned in previous class sessions, and your own experiences.
Your assignments show strong effort and attention.
Your projects and reflection papers show:
Foundational understanding of course topics, including sometimes making connections between the readings, information learned in previous class sessions, and your own experiences.
Your assignments show a fair amount of effort and attention.
Your projects and reflection papers show:
General understanding of course topics.
Your assignments show a low level of effort and attention.
|You participate with good faith and generosity in all class activities and you show leadership and strong cooperation with your classmates.
|You participate with good faith and generosity in all class activities.
|Your participation is uneven in class activities.
|You complete the midterm and final self-evaluation with sincere self-reflection and you show thorough familiarity with the content of the course.
|You complete the midterm and final self-evaluation with sincere self-reflection.
|You complete the midterm and final self-evaluation.
Feedback for us
Periodically, we will provide time in class for you to provide anonymous 5-minute feedback about any aspect of the course. We value your input, and when possible, we will adjust the course in response to your feedback.
We wish to make this class accessible to all. If you have a disability for which you are or may be requesting an accommodation, please contact us or the Office of Disability Services.
University conduct policies
This course will adhere to the MSU Conduct Guidelines.