Office of Research, Innovation and Collaboration (ORIC)

College of Education and Human Ecology

data visualization

Data Cleaning for Social Sciences Workshop 1: Introduction & Basic Data Cleaning Procedures

The QMC is hosting a free, virtual three-part workshop series on data cleaning for social sciences. The event will be held over Zoom, and cover basic, intermediate, and advanced data cleaning procedures.

The overall goals of this workshop series are to equip participants, particularly in the field of social sciences, with the essential skills and knowledge needed to effectively clean, prepare, and transform data for robust and accurate analysis in their research and studies.

The workshop series will be led by our Graduate Research Associate, Lizeng Huang.

Register for this event by clicking the link here, and visit our Spring 2024 Workshop Series page for more information about our upcoming events.

Introduction to the new NIH Data Management and Sharing Policy (Virtual Event)

Do you have an upcoming NIH proposal due? Join us to learn about the newly implemented NIH Data Management and Sharing (DMS) policy, including the requirement to submit a DMS plan with all new applications and renewals. Compliance with the submitted and accepted plan will be assessed, and non-compliance can impact future funding.

This informational session will provide an introduction to the policy, as well as the tools and resources provided by Ohio State to help you. The final 30 minutes will be reserved for questions.

Topics to be covered include:

  • How the DMPTool can help you address the required elements of a DMS plan
  • Tips for identifying a suitable repository
  • Guidance on how to budget for data-related costs
  • Who on campus can help with questions

This workshop is ideal for researchers who currently receive NIH funding or may apply in the future, as well as staff who support NIH-funded researchers.

Can’t make the workshop? Check out the NIH DMS Policy Guide for the latest updates, including the slides from this session.

For questions, or additional information, please contact us at datamanagement@osu.edu.

Missing Data Workshop

The QMC is hosting a 90-minute workshop on missing data, with a particular focus on addressing missing data in regression analysis. The overall goal of this workshop is to give attendees the tools to be able to assess the nature of missingness within datasets, and build attendees’ capacities to address missingness within their research. The workshop will use R, and directions can be found below to download R.

Menglin Xu, PhD

The workshop will be led by Dr. Menglin Xu. Menglin Xu is a Ph.D. graduate from the Quantitative Research, Evaluation, and Measurement (QREM) program of EHE, OSU. Menglin has teaching and research experience in multivariate statistics, psychometrics, causal inference, longitudinal data analysis, Bayesian statistics, meta-analysis, and Monte Carlo simulations, among others. Serving as a biostatistician at Medical Center of OSU, Menglin is using her expertise in experimental design and statistics to support professional works in diversified areas of health sciences, psychology, and education.

Register

Introduction to Data Visualization in R (Virtual Event)

This workshop will consist of a beginner friendly introduction to the R programming language for data visualization. We will explore the pros & cons of using R and showcase examples & resources. Those with or without programming experience are encouraged to attend! Join us to learn more about visualizing data using the R programming language, so that you can visualize yourself as a future R user!

Register

Introduction to Data Visualization (Virtual Event)

Join us for a virtual Introduction to Data Visualization workshop. Put on by the Research Commons, this workshop will break down what data visualization is and why it is important. Examples, tips, tools, and resources will be shared, with the aim of enabling the participants to realize data visualization in their own lives. Join us to broaden your outlook on what data viz is and what it can do for you!

Register

Data Entry and Program Management in REDCap (Webinar)

This level of training is appropriate for individuals who won’t have primary responsibility for designing forms, rather their role will be to enter and edit data. Also for project coordinators/ program managers who will oversee data collection.

Please click here to register. A calendar invite will be sent after registration. Slides will be distributed to all registered participants 12 hours before training time.

Introduction to Data Visualization in Python (Virtual Event)

This workshop will consist of a beginner friendly introduction to the Python programming language for data visualization. We will explore the pros & cons of using Python and showcase examples & resources. Those with or without programming experience are encouraged to attend! Join us to learn more about visualizing data using the Python programming language, so that you can visualize yourself as a future Python user!

Register

Introduction to Data Visualization in R (Virtual Event)

This workshop will consist of a beginner friendly introduction to the R programming language for data visualization. We will explore the pros & cons of using R and showcase examples & resources. Those with or without programming experience are encouraged to attend! Join us to learn more about visualizing data using the R programming language, so that you can visualize yourself as a future R user!

Register

Secondary Data Symposium 2023 (Online)

A symposium featuring faculty research supported by The Ohio State University Department of Biomedical Informatics, Center for Biostatistics, Secondary Data Core, curated for an audience of clinicians and researchers. Research professionals will present on their experience and overall expertise with using secondary data to answer important questions throughout multiple areas of study.

Register

What does feminist data science look like? (Virtual Event)

As data are increasingly mobilized in the service of governments and corporations, their unequal conditions of production, their asymmetrical methods of application, and their unequal effects on both individuals and groups have become increasingly difficult for data scientists–and others who rely on data in their work–to ignore. But it is precisely this power that makes it worth asking: “Data science by whom? Data science for whom? Data science with whose interests in mind? These are some of the questions that emerge from what we call data feminism, a way of thinking about data science and its communication that is informed by the past several decades of intersectional feminist activism and critical thought.

Register

Footer

CONTACT US

Office of Research, Innovation and Collaboration (ORIC)
153 Arps Hall
1945 N. High St.
Columbus, OH 43210

Meet Our Staff

OFFICE HOURS

8 a.m. to 5 p.m.
Monday–Friday

Phone: (614) 247-2412
Email: EHE-office_of_research@osu.edu