In this introductory workshop, learn about research data management best practices and how investing a small amount of time in organizing your data now can save you a lot of time and prevent future headaches. We will go over best practices for data planning, storage, organization, preservation, and sharing.
McMaster’s Research Data Management (RDM) Community of Practice is back! We meet the last Thursday of every month to learn together as researchers and research support staff across all levels of RDM expertise. Data Management Plans (DMPs) are growing as a requirement for grants, from the Tri-Agencies, to NIH, and others. They can also be a helpful document to guide best practices—either as a process document for your research group or as an individual researcher. Join our RDM Community of Practice to discuss DMP development!
Universities are not immune from data breaches and cyber attacks. Learn to protect your research data at this webinar with McMaster experts in IT Security and Cybersecurity. After introducing Information Security (a field dedicated to protecting sensitive digital information and data from unauthorized access, alteration, and/or destruction), the session will examine InfoSec problems specific to researchers. This webinar will also include a case study: If we take a hypothetical research workplace (such as a lab or office), what are its potential Information Security weak spots and how might we fix them?
The Library is the heart of DH at the University of Ottawa. Our colleagues in the Library have supported DH research and teaching since the very beginning. Come to the second session to meet the librarians that support and engage in DH research and teaching. They will highlight services, tools, and resources available through the Library and the Archives and Special Collections, showcasing projects on which our university Librarians and Archivists have collaborated.
This beginner-level workshop will focus on basic concepts of R programming using RStudio. Various Data Types and Data Structures will be discussed, as well as basic data analysis in R. No prior knowledge of R programming is required.
Planning ahead for research helps you prepare for data questions and problems before they happen. Submitting a Data Management Plan (DMP) is increasingly a requirement for funding applications with Tri-Agencies and the NIH. But DMPs can also be very helpful “living documents”: research tools that identify strengths and gaps which are updated through your research process. In this session, we’ll start with best practices of data management planning and go through a demo of DMP Assistant, a web-based tool for developing and collaborating on Data Management Plans in the Canadian research context. We’ll end with a sandbox session.
Are you building your own web site using JavaScript and frameworks? In this second workshop of the Building JavaScript Websites series, learn to design your web site to work for desktop and mobile sized screens. Starting from a simple prepared single-page application, we will walk you through how to scale your web site to work with the small screens on mobile devices without any loss of functionality. Each workshop in this series can be taken independently of the other workshops in the series.
Led by Dr. Shawn Graham
This series of workshops introduces humanities scholars to coding in the humanities. The suite of workshops covers the following topics: Each of these workshops introduces a core topic for those interested in computational methods for the humanities and provides opportunities to apply the ideas and techniques discussed. Attending all sessions is essential as the workshops are […]
This introductory workshop offers best practices for data organization in spreadsheets for humanities, social sciences and librarians.
Led by Jinny Yu and Celina Jeffery (from uOttawa) and Ming Tiampo (from Carleton U)
This beginner-level workshop will introduce you to the basics of SPSS statistical software, how it works, and some basic descriptive statistics, statistical procedures and chart building features. No prior knowledge of SPSS is required.
