Book contents
- Network Science in Archaeology
- Cambridge Manuals in Archaeology
- Network Science in Archaeology
- Copyright page
- Contents
- Tables
- Boxes
- Acknowledgments
- Introduction to the Online Resources Associated with This Book
- 1 Introducing Network Science for Archaeology
- 2 Putting Network Science to Work in Archaeological Research
- 3 Network Data
- 4 Exploratory Network Analysis
- 5 Quantifying Uncertainty in Archaeological Networks
- 6 Network Visualization
- 7 Spatial Networks and Networks in Space
- 8 Uniting Theory and Method for Archaeological Network Research
- Book part
- Glossary
- References
- Index
- References
6 - Network Visualization
Published online by Cambridge University Press: 06 April 2023
Book contents
- Network Science in Archaeology
- Cambridge Manuals in Archaeology
- Network Science in Archaeology
- Copyright page
- Contents
- Tables
- Boxes
- Acknowledgments
- Introduction to the Online Resources Associated with This Book
- 1 Introducing Network Science for Archaeology
- 2 Putting Network Science to Work in Archaeological Research
- 3 Network Data
- 4 Exploratory Network Analysis
- 5 Quantifying Uncertainty in Archaeological Networks
- 6 Network Visualization
- 7 Spatial Networks and Networks in Space
- 8 Uniting Theory and Method for Archaeological Network Research
- Book part
- Glossary
- References
- Index
- References
Summary
When many people (network researchers included) think about networks, the first thing that pops into their head is the classic network node-link diagram. In its simplest form a network graph is just a collection of points on a page representing entities of some sort with lines drawn to indicate the connections among those entities. Network visuals can be small and include only a few actors and relations where structural patterns and positions can be clearly observed. They can also be dizzyingly complex bundles of thousands, tens of thousands, or more entities and connections where general textures of relations and topological features might be visible but the positions of most nodes and edges are obscured by complexity. In either case, such visuals can paint a fascinating picture of a dataset and help a researcher recognize, interpret, and explain patterns in all manner of relational data that would otherwise be difficult to identify or communicate even with the myriad of network metrics available.
- Type
- Chapter
- Information
- Network Science in Archaeology , pp. 193 - 236Publisher: Cambridge University PressPrint publication year: 2023
References
Further Reading
The following references provide detailed discussions of a variety of visualization techniques or evaluations of different kinds of visualizations for communicating information to a diversity of intended audiences.
The following references provide general information on the design of data-based visualizations and design.
Bach, Benjamin, and van Garderen, Mereke 2023 Beyond the Node-Link Diagram: A Fast Forward about Network Visualisation for Archaeology. In The Oxford Handbook of Archaeological Network Research, edited by Brughmans, Tom, Mills, Barbara J., Munson, Jessica L., and Peeples, Matthew A.. Oxford University Press, Oxford.Google Scholar
Beck, Fabian, Burch, Michael, Diehl, Stephan, and Weiskopf, Daniel 2017 A Taxonomy and Survey of Dynamic Graph Visualization. Computer Graphics Forum 36(1):133–159.Google Scholar
Kandel, Sean, Heer, Jeffrey, Plaisant, Catherine, Kennedy, Jessie, van Ham, Frank, Riche, Nathalie Henry, Weaver, Chris, Lee, Bongshin, Brodbeck, Dominique, and Buono, Paolo 2011 Research Directions in Data Wrangling: Visualizations and Transformations for Usable and Credible Data. Information Visualization 10(4):271–288.Google Scholar
Schöttler, Sarah, Yang, Yalong, Pfister, Hanspeter, and Bach, Benjamin 2021 Visualizing and Interacting with Geospatial Networks: A Survey and Design Space. Computer Graphics Forum 40(6):5–33.Google Scholar
Healy, Kieran 2018 Data Visualization: A Practical Introduction. Princeton University Press, Princeton, NJ.Google Scholar
Schwabish, Jonathan 2021 Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks. Columbia University Press, New York.Google Scholar
Tufte, Edward R. 2001 The Visual Display of Quantitative Information. Graphics Press, Cheshire, CT.Google Scholar
Wilke, Claus O. 2019 Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures. O’Reilly Media, Sebastopol, CA.Google Scholar
Yau, Nathan 2011 Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. John Wiley & Sons, Hoboken, NJ.Google Scholar
Bach, Benjamin, and van Garderen, Mereke 2023 Beyond the Node-Link Diagram: A Fast Forward about Network Visualisation for Archaeology. In The Oxford Handbook of Archaeological Network Research, edited by Brughmans, Tom, Mills, Barbara J., Munson, Jessica L., and Peeples, Matthew A.. Oxford University Press, Oxford.Google Scholar
Beck, Fabian, Burch, Michael, Diehl, Stephan, and Weiskopf, Daniel 2017 A Taxonomy and Survey of Dynamic Graph Visualization. Computer Graphics Forum 36(1):133–159.Google Scholar
Kandel, Sean, Heer, Jeffrey, Plaisant, Catherine, Kennedy, Jessie, van Ham, Frank, Riche, Nathalie Henry, Weaver, Chris, Lee, Bongshin, Brodbeck, Dominique, and Buono, Paolo 2011 Research Directions in Data Wrangling: Visualizations and Transformations for Usable and Credible Data. Information Visualization 10(4):271–288.Google Scholar
Schöttler, Sarah, Yang, Yalong, Pfister, Hanspeter, and Bach, Benjamin 2021 Visualizing and Interacting with Geospatial Networks: A Survey and Design Space. Computer Graphics Forum 40(6):5–33.Google Scholar
Healy, Kieran 2018 Data Visualization: A Practical Introduction. Princeton University Press, Princeton, NJ.Google Scholar
Schwabish, Jonathan 2021 Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks. Columbia University Press, New York.Google Scholar
Tufte, Edward R. 2001 The Visual Display of Quantitative Information. Graphics Press, Cheshire, CT.Google Scholar
Wilke, Claus O. 2019 Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures. O’Reilly Media, Sebastopol, CA.Google Scholar
Yau, Nathan 2011 Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. John Wiley & Sons, Hoboken, NJ.Google Scholar
Bach, Benjamin, and van Garderen, Mereke 2023 Beyond the Node-Link Diagram: A Fast Forward about Network Visualisation for Archaeology. In The Oxford Handbook of Archaeological Network Research, edited by Brughmans, Tom, Mills, Barbara J., Munson, Jessica L., and Peeples, Matthew A.. Oxford University Press, Oxford.Google Scholar
Beck, Fabian, Burch, Michael, Diehl, Stephan, and Weiskopf, Daniel 2017 A Taxonomy and Survey of Dynamic Graph Visualization. Computer Graphics Forum 36(1):133–159.Google Scholar
Kandel, Sean, Heer, Jeffrey, Plaisant, Catherine, Kennedy, Jessie, van Ham, Frank, Riche, Nathalie Henry, Weaver, Chris, Lee, Bongshin, Brodbeck, Dominique, and Buono, Paolo 2011 Research Directions in Data Wrangling: Visualizations and Transformations for Usable and Credible Data. Information Visualization 10(4):271–288.Google Scholar
Schöttler, Sarah, Yang, Yalong, Pfister, Hanspeter, and Bach, Benjamin 2021 Visualizing and Interacting with Geospatial Networks: A Survey and Design Space. Computer Graphics Forum 40(6):5–33.Google Scholar
Healy, Kieran 2018 Data Visualization: A Practical Introduction. Princeton University Press, Princeton, NJ.Google Scholar
Schwabish, Jonathan 2021 Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks. Columbia University Press, New York.Google Scholar
Tufte, Edward R. 2001 The Visual Display of Quantitative Information. Graphics Press, Cheshire, CT.Google Scholar
Wilke, Claus O. 2019 Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures. O’Reilly Media, Sebastopol, CA.Google Scholar
Yau, Nathan 2011 Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. John Wiley & Sons, Hoboken, NJ.Google Scholar