Google Fusion Tables

 Google Fusion Tables is an experimental data processing application created by Google Labs. It is made available as a browser extension for Chrome. All Google Fusion Tables files are saved in the user’s Google Drive account. As of this writing, a Google Drive account offered through an institution working on Google infrastructure—for instance, university-affiliated Gmail accounts—cannot be used with Google Fusion Tables.

 In addition to “Map of latitude,” its map view, Google Fusion Tables offers four additional data views: “Rows” (the data table, sortable by attribute), “Cards” (individual entities with all their metadata and any associated images), “Summary” (bar graphs counting entities relative to a selected attribute’s variables), and “Chart” (two-dimensional charts displaying the relationship between two attributes). All data views, including the Map view, can be filtered by date span, geography, or any other attributes.

 Map views in Google Fusion tables are simple, with point values or imported .kml shapefiles overlaying the familiar Google Maps interface. Map features can be clicked to display a static popup window, including the feature’s metadata and any associated images. The map can also be manipulated through data filtering, but visual customizability is minimal, and geoprocessing capability is absent.

Example Applications

While the author was unable to find any digital humanities projects that specifically listed Google Fusion Tables as their mapping infrastructure, there are several projects which are built using the Google Maps API and which display front-end interfaces that are very similar to a map produced by Google Fusion Tables.

One such project is the Cultural Atlas of Australia, which charts the locations of notable scenes in literary and filmed works set in Australia. Much as in the Google Fusion Tables map view, data points can be filtered by a number of variables, including time span, location type, and the classification of the source material (novel, film, etc.). Also, much like Google Fusion Tables, clicking on a map feature yields a static information box displaying the feature’s extended metadata. The Cultural Atlas of Australia demonstrates the maximum potential of a Google Fusion Tables-style map interface; in addition to its thorough data filtering options, the project increases its map’s interactivity by including information-box hyperlinks to web pages containing further information.

Digital Humanities Potential

Google Fusion Tables is a natural fit for projects with fairly simple display needs, and whose geospatial data is comprised of a collection of related but discrete point values, rather than a set of deeply interrelated entities whose kinships need to be highlighted easily. Aside from the data filtering interface, interactivity is fairly limited; time lapse animations are not supported, and point values are associated with static pop-up information boxes rather than multimedia or in-depth narratives.

The ideal project for Google Fusion Tables would utilize the technology to its fullest capability, without making conceptual demands that the tool is unable to accommodate. While the Google Drive interface allows for easy collaboration, the resulting map appears singly-authored; individual map features cannot be associated with a specific collaborator. Boundaries, overlaps, and other forms of ambiguity are not accommodated, and the authoritative Google map tiles present current-day political boundaries and satellite imagery as if they are static and unchanging.

A project such as an architectural inventory would be an ideal match for Google Fusion Tables; while the situation of an architectural structure in space is more complex from a humanistic standpoint than its mere latitude and longitude, the building itself resides at a fixed point, and thus the lack of spatial ambiguity does not do the project much conceptual harm. Information boxes could display photographs of the building as well as data on its construction, ownership history, and current status; furthermore, users could be encouraged to use the Google Street View function to view what the building looks like in a contemporary context, highlighting historical dissonances even though the interface initially seems to insist on a timeless interpretation.

Google Fusion Tables would be hospitable to similar projects whose conceptual core resided in drawing connections between historical and contemporary experiences of place—an illustrated map of the residences of a social network of artists or writers, or an inventory of sites of historical cultural trauma. Particularly with the integration of supplementary web pages, as in the Cultural Atlas of Australia, Google Fusion Tables could support a greater depth of exploration than its relatively simple interface suggests.

Advantages

Google Fusion Tables shares many of the virtues of Palladio—its simplicity, its ease of use—while sidestepping several of its drawbacks. The tool reads different kinds of data more easily, and is better at making inferences about the data it receives (e.g. automatically recognizing location data and datetime values). It allows the user to filter by as many or as few variables as they wish, and its information boxes yield rich metadata and can be configured to display associated images as well as text. Google Fusion Tables maps are easily embedded elsewhere, and the maps and their data can be saved indefinitely.

Because it is built on the Google Maps API, Google Fusion Tables particularly excels at automated geocoding—in addition to easily translating latitude-longitude values into point features, Google Fusion Tables automatically creates point values from street addresses. This unique feature may spare the user from manually geocoding street addresses, which—especially when dealing with a large dataset—could prove to be a significant time saver.

Drawbacks

If a project requires coverage or point-to-point data instead of point values, the files must be uploaded in .kml format; Google Fusion Tables is not interoperable with other common file formats, such as .shp or .json. Since .kml was at one point the proprietary geographic markup language for Google Maps, this restriction is perhaps unsurprising, but it does somewhat limit interoperability.

Very little can be done to visually customize a Google Fusion Tables map; the user must choose from a limited library of point-feature markers in a limited palette of colors, and the only map tiles available are the familiar map, satellite, and terrain Google base maps. While maps can be embedded with ease, they cannot be easily printed or exported as an image file.

External Links

• Google Fusion Tables
• GFT Tutorials