Working with Palladio
Palladio is a web-based platform for the visualization of multi-dimensional data. The program was created in connection with The Republic of Letters project at Stanford University.
Perhaps the connections you want to see do not make sense to be mapped, like those between people. This is where Palladio’s usefulness comes excels. Graphs allows you to create network visualizations based on different facets of your data. In general, network graphs display relationships between entities, and work best if all your nodes (dots) are the same type of information. They are especially useful to show connections between people. The network graph makes it especially visible that there are some slight inconsistencies in the data; cleaning and standardizing your data is critical.
A Palladio project begins first with the tabular data you have on your computer. Copy and paste out of your spreadsheets, drag-and-drop to upload tabular data (e.g. .csv, .tab, .tsv), or link to a file in a public Dropbox folder to create a new Palladio project.
Once you have uploaded this data into the Palladio interface, you can then refine it and visualize. Information that can be represented in a table format (any data you enter into a spreadsheet program) will work with Palladio. All data is represented by delimited-separated values. Palladio supports the following delimiters: commas, semicolons, and tabs.
To use features like mapping coordinates or filtering by timeline and timespan, Palladio needs to be able to read your data types properly. Allocating time to review your data sets can help you make sure your data is as clean as possible before the Palladio visualization process.
You can load data into Palladio in several ways:
- drag a .csv file into the box
- copy and paste your data
- type directly into the box.
When your data is initially loaded into Palladio, you may see several of your data dimensions flagged for review with a red dot. Palladio refers to table attributes as ‘dimensions’. It may flag special characters that may or may not be intentional. You can filter the values and review them for accuracy. If there is an issue in your data, you can edit it outside of Palladio and reload the data. When you have checked each flagged character, the red dot will disappear.
Use the Edit Dimension view to see how often a value appears in your data. The number on the side of each entry indicates its frequency. You can also choose to sort your data by value. Another way to review your data is to search for values within a dimension. Palladio automatically assigns each dimension a data type. Here, you can see that Palladio reads “accession date” as a Number. Click to edit a dimension and change its data type.
If there is a dimension of your data that you do not want to include in your Palladio project, you can disable it by clicking on the eye icon. Disabled dimensions can be enabled again at any time. You can also join tables together e.g., the ‘Interviewed‘, ‘Places‘, and ‘Enslaved‘ tables for the WPA Slave Narratives project were joined by Name attribute to add locational information. Joining data is typically used to append the fields of one table to those of another through an attribute or field common to both tables through a common field, known as a key.
Add titles to your tables and data also.
Save your data set:
Palladio does not store your data, so each project lasts only as long as your browser session unless you download it.
In the Graph view, you can visualize the relationships between any two dimensions of your data. Graph information will be displayed as nodes connected by lines. Nodes can be scaled to reflect their relative magnitude within your data. The display of links and labels can be toggled on and off. Export Graph visualizations as .svg files.
In the List view, dimensions of your data can be arranged to make customized lists. Export List visualizations as .csv files.
In the Gallery view, data can be displayed within a grid setting for quick reference. Here dimensions of your data can also be linked to outside web-based information. Sort your data according to different dimensions.
The Map feature is used to pinpoint coordinates and connections between them. Hovering over the connection shows you the direction of the move. You can change the map itself to be standard maps like satellite or terrain, or even just land masses with no human-created geography, like roads or place names.
In the Map view, you can see any coordinates data as points on a map. Relationships between distinct points can be connected by lines, with the arc of the line representing the flow of the relationship.
Spatial analysis on historical data with Palladio allows you to use other maps as base maps, provided that the map has been georeferenced (assigned coordinates based on locations represented on the image).
Create a Map:
Points on the map can be visualized by point or point-to-point (fig 2). The point can be sized to represent their relative magnitude within your data. With the map’s tooltip function, you can select which data will be displayed when hovering over a specific point on the map. Joining tables like ‘Interviewed‘, ‘Places‘, and ‘Enslaved‘ for the WPA Slave Narratives project by Name attribute adds locational information to make map visualization possible.
Zoom in and out and full extent controls are available (upper left of Fig 2). Export the nodes and links of Map visualizations (though not the Map background itself) as .svg files.
The first step is to specify the type of map you would like to see. To do so, choose from the menus within the settings panel. You can choose from two types of map views: ‘Points’ or ‘Point to Point’. (Note that access to these functions will depend on the kinds of information you’ve uploaded. You wouldn’t, for example, be able to use the ‘Point to Point’ function unless Palladio recognizes a dataset with more than one type of coordinates column, ie. ‘Where Interviewed’ and ‘Where Enslaved.’)
‘Points’ map view
In the ‘Points’ map view, Palladio can map out a collection of unique locations, based on any coordinates data (longitude, latitude) you’ve entered.
In Points view you can only select one dimension. If you toggle Size points, the sizes of each dot will relates to their frequency within your data. You can specify how you would like to count your data by using the Count By function. Note you can only count by unique tables uploaded in your data. Hovering over specific dots will display corresponding data. You can select which type of data to display on hovering, by using the Tooltip label.
Below the ‘Type of Map’ menu is a second menu, ‘Places.’ This menu will be populated with any data for which there are coordinates, and the menu choices will be named for the headers of columns containing coordinates data. The map will be populated with dots representing each individual value in your coordinates data.
‘Point-to-Point’ map view
The point to point view give us a node-link map. Here you will select two different dimensions (ie. source city and destination city) and see the links between various points.
The arc of the link between two points represents the direction of the flow. Think of direction in a clockwise function.
Map Custom Filters:
In addition to loading datasets, it is possible to add a map custom filters while visualizing data.
The Facet, Timeline, and Timespan filters each allow filtering by multiple parameters, and the various criteria overlap in different ways. When applying multiple criteria within a facet filter, only rows that meet all criteria will be included in the display. When selecting multiple timelines, rows that meet any criteria will be included in the display. If you create two or more filters, only rows that meet all criteria in all filters will be included in the display.
Create a graph
Create a Bivariate Graph
Palladio offers a bivariate graph to show associations between two different dimensions. The default is a simple force-directed layout. The strength of Palladio in investigating these associations comes with pairing the graph view with our different filters. Any of your data dimensions can become a source or target dimension for the graph.
You can size nodes according to their connectedness in your data. Orient your graph spatially by dragging and dropping nodes across the screen. Investigate multiple dimensions of the data using interactive filters like the Facet Filter shown below.
The settings window allows you to control the source and target data, show links, highlight either the source or target data for easier reading. To save your graph, download it as a .svg file.
You can view .svg files within a web browser or perform edits in a vector program like Adobe Illustrator.