With the remarkable array of digital tools available, it can be difficult to determine which ones you’ll really need, particularly when you're in the research stage. Perhaps you only vaguely …
Are you interested in using a map to tell your research story? to explore your data? to illustrate your argument? This workshop will offer an approachable introduction to Geographic Information Systems (GIS), and its uses: storage, capture, edition, analysis and visualization of data. In the first part of the workshop we will look at the …
Does your research involve sound? Would you like to learn more about digital tools for capturing, editing and managing audio files, as well as qualitative coding and transcribing their content? This workshop will review some hardware, software, techniques and concepts that are useful to scholars working with sound – be it music, voices, soundscapes or …
Data cleaning is an important step in any data-driven research project. Often data is harvested from diverse sources such as the web, databases, spreadsheets, text files, and countless other places. These sources can employ different encodings, formats, and follow different conventions all of which must be normalized before analysis can take place. Exactly what steps …
Topics to be discussed and demonstrated include deciding who to follow and for what reasons, strategies for using tagging and hastags, harnessing the power of media stats on blogs and articles, creating Twitter lists, live tweeting, frequency of tweets, social media aggregators and notifications to streamline workflow, and balancing personal and professional content. RSVP here.
Matplotlib is the most widely used visualization library in Python. There are two entry points into the library: the pyplot API which mimics MATLAB (widely used in engineering disciplines) and …
While academic work can certainly be a solitary affair, much of our work is collaborative in nature. Sane solutions to collaborating on computers do exist. You might have already used …
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