Weeks 4&5 QA

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Grand Valley State University *

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Information Systems

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Dec 6, 2023

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docx

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Weeks 4 & 5 QA 1. What is the transparency strategy for displaying massive data sets? Is it a "good" strategy? Why or why not? Transparency displays the overview directly on top of the focus. It is not a good strategy because overlapping scales and information result in confusing images. 2. Compare and contrast F+C and O+D F+C (Federated Learning + Centralized Model): Centralized model on a central server. Preserves data privacy as raw data stays on clients. Scalable for many clients but needs significant server resources. Communication overhead due to frequent model updates. O+D (Orchestrated + Decentralized Model): Decentralized models with no single central model. Privacy concerns may exist depending on model coordination. Highly scalable, especially for many decentralized models. Communication overhead for model coordination. 3. Describe what it means to use the “chainsaw” method. Remove rows or columns of data when giving an overview to make the data easier to see and clearer to interpret. 4. Name three different strategies for navigation when using very large datasets. Chainsaw, Hammer, Combine 5. What is the difference between a zooming approach and a overview & detail approach for navigation? What are the advantages & disadvantages of each approach? In zooming, you have just one window (or screen) of information at any time. You are able to get detailed information by zooming in and overview information by zooming out. Since you can't zoom in and out at the same time, you can only view either detail or overview information at any time. With an overview & detail approach, you will have two windows (or screens). One of the windows provides an overview while the other provides the detail information. The advantage is that you get to view both at the same time, but each of your windows must be smaller to fit on your viewing window.

6. What would be a useful strategy to reduce data quantity? Reduce the amount of data shown. Leave the data that is critical to analysis and remove the rest. 7. What’s not a con of the ‘Zooming’ navigation approach? A Context is lost when zooming in. B Users can get lost. C Moving long distances can be tedious. D Zooming in too far can crash certain systems. D 8. What are some pros and cons of the Focus and Context navigation approaches? Pros: Enhanced understanding of data. Maintains contextual awareness. Reduces cognitive load. Efficient navigation in complex datasets. Facilitates better decision-making, especially for multiscale data. Cons: Can lead to visual clutter. May have a learning curve. Limited screen space can be a constraint. Implementing interactivity can be complex. Performance issues with large datasets. Requires careful design and may be subjective in determining detail levels. Not suitable for all types of data or applications. 9. Define the "Keyhole Problem" and give a method of addressing it. The Keyhole Problem is the issue of being stuck "zoomed into" the data set and losing perspective along with having no ability to look for patterns or even what you can look for. Using an overview, we can get a high level view of the data that allows us to intuitively recognize patterns or trends still have the ability to drill down into the details we need, if we desire to do so. 10. Which of the following is not an approach for scaling a large dataset?

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