In this “Coffee & Learn” session, enjoy some coffee (or bring your beverage of choice from the coffee shop downstairs!) and join us for a 45-minute discussion on completing a data inventory.
Join us for a 1 hour crash course in data cleaning basics with Excel.
Through this workshop, participants will learn:
- Simple and advanced filtering
- Creating histograms through the Data Analysis Toolpak
- Splitting multi-valued cells and trimming whitespace
- Data validation and custom lists
* Disclaimer: This class is not a general Excel class, but rather a specialized application of Excel. Galter Health Sciences Library & Learning Center does not provide technical support for any Microsoft Products.
Join us for a 45-minute discussion on best practices for file organization.
Through this workshop, participants will:
- Learn best practices for file naming
- Learn best practices for digital folder organization
- Gain tips for adding searchable keywords and tags to files
An introduction to basic concepts in research data management including University retention requirements, data management plan requirements, data documentation, file naming conventions, metadata, and sharing research data.
Upon completion of this one-hour workshop, participants will:
- Understand and be able to apply best practices for file naming and documentation
- Be familiar with basic tidy data best practices
- Be familiar with metadata best practices
- Understand and be able to locate online Federal funder requirements for data sharing
- Be familiar with publication and data sharing tools available both at Northwestern and through the Web
An introductory class in OpenRefine, a free, open-source tool for cleaning data in spreadsheets. No coding knowledge is needed. Familiarity with concepts such as data records and values is helpful.
Upon completion of this 90-minute workshop, participants will:
- Understand how to facet and transform data values
- Understand how to write simple data transformations
- Understand how to retrieve data from APIs
- Understand how to reconcile data against controlled data sources