Data Science Programs
If you are faculty member, staff, or administrator looking for support on a research project, you have found the right place.
Depending on the state of your project you can consider different alternatives:
1) If you are a researcher who has not collected data yet, and need advice on how to design a project (e.g., how to work with research assistants, how to create a Qualtrics form, how to recruit participants), consider joining the Fall professional learning community “From Idea to Data.”
2) If you are a researcher who is interested in learning how to explore your own data and how to get it published (e.g., selecting a journal, creating figures, writing the results section) consider joining the Spring professional learning community “From Data to Publication.”
3) Finally, if you have collected data and you want the Data Science team to help you with it, you can request a consultation by completing this form.
A typical Data Science consultations entails the following steps:
Once you complete the form, the Data Science Coordinator will assign a team to your project.
The coordinator will create a folder in our Google Drive with the name of your project.
Once you are invited to the folder, you will need to upload the unidentified version of your dataset (notice that the initial consultation cannot take place until a dataset has been uploaded).
Once the dataset has been uploaded, you will meet with the Data Science team for the initial consultation (our standing weekly meetings are Thursdays at 9:30 am).
During the initial 30 minutes consultation you will work with the team (undergraduate students, graduate students, and faculty mentors) to develop a plan, including an appropriate timeline (note that in order to properly train students in data science all projects should take a minimum of one month and most projects should be semester-long projects).
The Data Science team will work on your data and the Data Science coordinator will follow up with you if there are questions.
During the final meeting (scheduled in the timeline) the Data Science team will present the results and everyone will have the opportunity to ask questions.
Once everyone agrees on the final output, the team will upload the final version of the data (.xlsx document), the final version of the code (R Notebook document), and any relevant figures (.png) to the project folder.
Types of Projects
Process: Students seeking help with their data (see form) will meet for a consultation with the Data Science Coordinator and two other team members assigned to that project. During the consultation, the Data Science team will help students brainstorm the best way to approach their data. Students are fully responsible for implementing all suggestions and completing all tasks to finish their project.
Timeframe: Each student consultation will take 30 minutes. Students can request as many consultations as necessary to complete their project.
Availability: The Data Science Team is committed to complete as many consultations as necessary to ensure all students working with data receive the necessary support.
Process: Faculty seeking help with their data will be asked to upload their dataset to a google drive folder before the initial consultation meeting with the Data Science team.
Timeframe: One semester. The initial consultation will take place at the beginning of the semester, the team will work on the project during the semester, and the final consultation will take place at the end of the semester.
Availability: The Data Science Team can accommodate up to five faculty projects every semester. To be considered for a specific term, faculty should submit their request (see form) at the beginning of each semester (August for Fall, January for Spring).
Priority: Faculty members who have completed the PLCs “From Idea to Data” and/or “From Data to Publication” will receive priority treatment.
Process: Administrators seeking help can start from an idea or a dataset. For those who start with an idea, the Data Science team can: operationalize constructs, select measures, validate measures, deploy measures, and collect data. For those who start with a dataset, the team can: clean data, visualize data, analyze data, and create a written and/or oral report.
Timeframe: One academic year. During the first semester data will be collected and during the second semester data will be analyzed.
Availability: The Data Science Team can initiate one university project every semester, for a total of two university projects taking place at any given time. Administrators should submit their request (see form) at the beginning of each semester (August for Fall, January for Spring).
Priority: Administrators working on projects likely to have the biggest positive impact on the EKU community will receive priority treatment.