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Uploaded byTony Hirst
B llabs
The document discusses various tools and techniques for working with datasets, including quick methods for analyzing and visualizing data using tools like OpenRefine, Google Earth, and R-Studio. It also covers building toolboxes and approaches for exploring data at different levels, from overviews to zooming in on specific details, as well as techniques for visualizing different data types and attributes using properties like node size, color, and proximity.
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- 1. Tools & techniques forworking with datasets Tony Hirst Dept of Communication and Systems The Open University
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- 8. “You can quicklycreate an online 3-D visualisation (with Google Earth) of these rare documents”
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- 16. All at once or one at a time?
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- 20. @mediaczar (Accession Plot)
- 24. Google Maps, 1884edition?
- 26. Overview first, zoom and filter, then details-on-demand From: The Eyes Have It:A Task by Data Type Taxonomy for Information Visualizations
- 29. • X and Y (at a push, Z) • Node size and colour • (Node label size and colour) • Edge thickness and colour • (Edge label and colour) • Node proximity/grouping • Clustering • Filtering and differential application of the above
- 32. Group by Hierarchy inside (implied) containment
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- 34. Similarities and differences
- 40. Single page app + linkage
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Editor's Notes
- #38 Let pi,j be the rate at which word i occurs in document j, and pj be the average across documents( sum Pij/ndocs)The size of each word is mapped to its maximum deviation ( maxi(pi,j- pj ) ), and its angular position is determined by the document where that maximum occurs.