Showing 61–72 of 92 results
Named Entity Recognition
Names are a common feature of interest when working with texts at scale. We can use a search function to locate names that we expect to find, but how do we go about searching for all names in the text – even those we do not know to look for?
The natural language processing technique of named entity recognition (NER) identifies words that may be names, places, or organizations within unstructured text. In this workshop, we will explore how NER works and apply it to a text corpus using a Python library named SpaCy.
Network Visualizations with Gephi
Learn to graph data and visualize networks at this workshop on Gephi. Viewers will explore how graph data can help express relationships between entities and visualize networks for Humanities scholars. This session uses a visualization tool intended for social network analysis to map and identify relationships within a dataset scraped from Twitter.
The shift towards ‘openness’ has been undeniable and accelerating within the academic landscape over the past decade. From open-source software, to open data, methods, and identifiers, to open access publishing and educational resources, more and more of the scholarly ecosystem can be discovered, reused, remixed, and connected in novel ways. Join us for this panel discussion, where we explain and connect the components of open scholarship while reflecting on the gaps, limitations, and disclaimers of an ‘open everything.’
Organize Research Projects with the Open Science Framework
OSF is a free, open platform to support research and enable collaboration. Join us to learn more about this great platform and how you can use it to organize your research projects, build a space for your research group to work together, collaborate on files and protocols, and publish your research openly!
Pre-Processing Digitized Texts
We underestimate our abilities to make sense of orthographic errors and alternative spellings like thcn or shew. Machines are less capable of making these inferences, meaning that OCR text output must often be corrected to render it legible to computational methods.
In this module, we’ll use several approaches to correcting errors in the OCR text output, introduce the concepts of initial data analysis (IDA) and data provenance, and explore how some techniques for correcting OCR errors can extend to pre-processing born-digital texts.
Predatory Publishing: Reducing the Odds of Falling Prey
Thinking about where to publish? Do you receive random invitations to submit your work for publications? Don’t get caught publishing in a questionable journal! This virtual workshop provides an overview of predatory journals and tips on how to avoid them and predatory conferences.
Qualitative Data: Practices for RDM Planning and Sharing
Qualitative methods let us share nuanced interpretations of multifaceted issues, understand lived experiences, see a research question from different standpoints, and highlight contexts. Qualitative research data can take the form of interview transcripts, oral histories, focus groups, field notes, audio, video, and more.
This workshop discusses considerations for managing and sharing quantitative data. We’ll start with practical skills and workflows, and then move on to a discussion about hesitations and urgencies. Qualitative research often grows out of relationships of trust, and information is deeply contextual, making data sharing sticky. However, communities are often approached by different researchers for similar information, and data sharing can also help alleviate research fatigue. Let’s learn and unpack together!
Research Beyond Academia
Mihaela Gruia, Director of Research Retold, delivers a two-part workshop series on knowledge mobilization. In order to make an impact with your research, it is important to know how to share research findings with broader, non-academic audiences. Gruia explains how to create a communications plan that will aid researchers in translating long, complex research reports into documents that spark conservation.
Research Data Management Guide
Research Data Management (RDM) is the active organization and maintenance of data throughout its lifecycle–from collection to interpretation, dissemination, long-term preservation, and reuse. Learn about McMaster resources on Data Management Plans, research data storage and backup, data documentation and metadata, data sharing, and more.
Science Communication and Digital Scholarship: A SCDS Graduate Resident Panel
How can scholars best communicate scientific analyses and results? How can we engage wider audiences in scientific research?
In this panel, three work-in-progress papers address these questions with a shared answer: digital tools. Through case studies of their own research, emerging scholars will explore the benefits of digital scholarship in science communication and discuss the importance of employing reflexive, inclusive, and interactive approaches.