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|---------------------------------|:----------:| | Engagement with Materials | 30% | | Class Participation | 15% | | Presentations | 10% | | Programming, Data and Tool Interaction Assignments | 15% | | Final Project Paper | 30% | | Total | 100% |
Throughout the course, you will be actively engaging with a wide range of assigned materials, including academic articles, book chapters, project websites, podcasts, videos, essays, and datasets. This engagement involves a two-step process: firstly, by commenting on Perusall, and secondly, by reflecting on your insights on Slack. Additionally, you'll dive into a dataset by creating a Data Biography.
1. Commenting on Perusall (10%)
Engage with the assigned materials on the collaborative annotation platform Perusall (access code to be shared in class). Make sure to read, watch, or listen to the materials thoroughly. Perusall allows you to highlight passages, make comments, and respond to your peers' comments and questions. Please be courteous and constructive during these interactions, adhering to the same etiquette guidelines as our class interactions.
- Frequency of Engagement: Unless otherwise noted, you should complete a minimum of three annotations per assigned material (i.e. per article, chapter, video, etc.) by 11:59PM on the day before our class.
- Nature of Comments: Your comment can be an agreement, disagreement, expression of confusion, question, or any other relevant observation. There are no right or wrong comments. The interaction serves as an exercise in critical thinking, collaborative learning, and engagement with scientific debates.
2. Reflecting on Slack (10%)
After your interaction on Perusall, post an overall reflection in the #reflections channel on Slack. Reflect on the entirety of your engagement with the materials. Some possibly helpful questions to guide you:
- What connections do you identify across the assigned materials?
- If specific arguments or points are being raised, do they overlap or contrast with each other?
- Are there elements that particularly inspired or frustrated you? Which ones and why?
- What parts of the assigned materials were confusing or challenging to understand?
- Are there specific topics you are now interested in exploring further?
A paragraph of 200-300 words is sufficient for your reflection. You are welcome to write more, but please keep in mind that the goal is to reflect on the materials, not to summarize them. If you are unsure about the length of your reflection, please feel free to ask me. Your grade will be determined by the depth and quality of your reflections, focusing on your critical engagement with the readings rather than agreement with their content.
Deadline: Please ensure both your annotations (min. 3 per assigned material) on Perusall and your reflection on Slack are submitted by 11:59PM on the day before our class.
3. Data Biography (10%)
In this assignment, you will create a Data Biography for a humanities dataset. Begin by exploring Heather Krause's concept of a Data Biography through her article "Data Biographies: Getting to Know Your Data" (Global Investigative Journalism Network, March 27, 2017), or watch her excellent Data Storytelling Module on YouTube. This will help you to get a better sense for what a Data Biography is and why it is important.
In short, a Data Biography is a narrative about a dataset's lifecycle. It covers its creation, usage, and any milestones associated with it. For this assignment, choose a dataset either from the resources that I've listed here or one you find independently. If you opt for a dataset of your own choice, make sure it aligns with humanities data as outlined by Miriam Posner in her blog post.
Please post the name and link to your chosen dataset in the #data-bio Slack channel. Each Dataset Biography must be unique, so selections are on a first-come, first-served basis.
Your Data Biography should tell a story about the dataset that addresses the following key aspects:
- Introduce the dataset and its contents. What kind of information is in there? How much data is there?
- Who collected, processed, and made available the data?
- How was the data collected, processed, and made available?
- Why was the data collected, what are its intended research questions?
- Where is the data stored today? How did you access it?
- When was the data collected?
- Considers potential limitations, biases, gaps, or ethical issues in the data.
Some additional notes:
- Remember to think about the data's journey from its original historical context to its current digital form. Document both the original sources and those who digitized the data!
- Krause's template spreadsheet is a useful starting point, but your final Data Biography should extend beyond this, bringing this information together into a coherent narrative.
- Digging deep is key for this assignment. You might need to delve into project details, read through "About" or "Methodology" sections, or document the absence of information.
- Feel free to expand upon Krause's template, considering additional categories like data format, processing steps, data dictionaries, and layers of mediation.
- For inspiration, you can take a look at this example of a Data Biography for the COVID-19 Tracking Data, or this example for the Shipwrecks dataset. These examples represent good Data Biographies; they give you a strong sense of what is expected in terms of structure and content, but keep in mind that they are not perfect. Use them as a guide to understand the scope of the assignment, while also thinking critically about how you can improve or add depth to your own Data Biography!
You will submit a reflection paper of between 1000 to 1500 words (~3 to 5 pages), that includes:
- An introduction to your dataset, providing details about its origin, ownership, collection process, purpose, and timeline.
- A discussion on how these specific details shape the kinds of questions that can be responsibly asked of the dataset.
- Your accompanying spreadsheet, if used, during your analysis (does not contribute to the overall page or word count).
Please format your file name as LastName-Data-Biography and email it to me by October 15, 11:59PM.
Class participation is an important aspect of this course. During the discussion and present sessions you are expected to contribute at least once. I understand that speaking up can sometimes feel intimidating, and it's not always the preferred mode of intellectual engagement for everyone. However, I want to reassure you that I genuinely value your contributions. It's absolutely fine if your thoughts aren't perfectly polished. Asking a question or admitting uncertainty is equally important and valuable. Diverse viewpoints and genuine dialogue are what make our discussions thrive. I encourage you to share your thoughts, respecting the guidelines outlined in our classroom etiquette.
Throughout this course, there will be two opportunities to present your work. The first presentation, which contributes 5% to your grade, involves sharing your Dataset Biography (see description above). The second, also worth 5%, revolves around your final research proposal's evolution (see description below) where you will elaborate on how you're integrating different Digital Humanities methodologies, tools, and datasets into your project. Both presentations offer a platform to showcase your work and receive feedback from me and your peers.
Throughout the course, there will be a series of smaller assignments that collectively contribute 15% to your overall grade. These tasks are specifically designed to enhance your technical skills and deepen your understanding of how digital tools and methodologies can be applied.
Your final assignment brings together the knowledge and skills you've acquired throughout this course, taking the form of a research proposal spanning approximately 2000 to 2500 words, excl. bibliography (ca. 9 to 12 pages, can go over when you're including bibliography and/or images). Guided by a clear research question, your task is to devise a comprehensive plan for a data-intensive research project.
This plan should be guided by the following elements:
- Research Question and Hypothesis: Articulate a central research question guiding your project and any hypotheses you aim to test or explore. This should form the foundation of your proposal and align closely with the dataset and methodologies you choose.
- Identification of a Dataset: Clearly specify the dataset you will be using, along with the rationale for its selection. Outline your envisioned approach to data collection, along with the specific methods for manipulation, annotation, and classification of the data, including the anticipated impact of these processes.
- Methodology: Describe the methodologies you will use to analyze the data, including the specific tools you will use and the anticipated impact of these tools on your research.
- Presentation and Dissemination: Describe how you plan to disseminate your results and present your project both within academia and to a broader audience, considering aspects like copyright, preservation, and sustainability.
When writing up your research proposal, it's important to translate these elements into a compelling and cohesive narrative. It isn't just about ticking boxes; it's about demonstrating your critical thinking skills and your ability to integrate and apply the various concepts and methodologies you've learned throughout this course. In other words, focus on articulating a clear research question and let your data handling and methodology reflect a nuanced understanding of the research process. Avoid falling into the trap of using jargon or clichéd phrases like "turbocharge [insert humanities subdiscipline here]". Be nuanced. Be specific. Be critical. Be creative. For guidance on crafting DH research proposals, take inspiration from this blogpost by Quinn Dombrowksi.
I will be evaluating your proposal holistically. Rather than just looking for the inclusion of certain key elements (as in the Data Biography assignment before), I'm interested in how well you synthesize and present your ideas. The one area where I will be particularly quantitative is in your use of citations: make sure to include at least 6 references that support the disciplinary context of your proposal (your bibliography won't count towards the final word count).
You will have the opportunity to present your research proposal in class on 5 December. This presentation will be followed by a Q&A session, where you will receive feedback from me and your peers-- feedback that you can still incorporate into your final, written research proposal.
Please format your file as LastName-Research-Proposal and email it to me by 13 December 2024, which is Dean's Date.