Have lots of vector and raster data and want to share it using Google Earth, Maps, and more? You’ll soon have a new cloud-based option: Google Earth Builder. Upload your data, organize it into a catalogue, add cartographic styling, and Google does the rest.

Unlike my earlier post on Fusion Tables, I haven’t had a chance to play with Earth Builder. We’ll likely ask for that when new data import APIs are available (more on that below) – but a webinar from Directions Media provides a clear picture of what’s coming. The announcement and ensuing discussion resonates with a few themes I’d like to highlight here.

Relationship with Similar Google Geo Offerings
Google EarthGoogle Earth Enterprise also lets you build and share globes with Google Maps and Earth clients. However, it’s a software and not cloud-based solution: All of the data storage and processing is handled on the customer’s hardware, and the customer provides the security infrastructure.

Google Fusion tablesGoogle Fusion Tables also lets you upload vector data to the cloud and share it with Google Maps and Earth clients. The two products are tightly related; we learn from the webinar that Fusion Tables is one of the back-ends for Earth Builder. Fusion Tables is focused on small datasets and simple use cases: You can start with a spreadsheet with addresses and other columns, and end up with an publishable map in just a few minutes. In addition to supporting much larger and more complex vector datasets, Google Earth Builder adds a host of features: raster storage and processing, flexible options for loading data (multiple formats, coordinate systems, and data transfer methods), analytics, improved cartography, and a flexible security model for editors and viewers.

Highlights from the Google Earth Builder Webinar
If you’re interested in more detail, the intro video, webinar, and Where 2.0 talk should cover the bases. Here’s what stuck with me:

  1. Cloud platforms and applications are making gains. Clearly, the benefits (effortless upgrades, scalability, anywhere access, easier collaboration, economy of scale) outweigh the negatives (reduced control of data and applications, dependency on third parties for mission critical systems) in some cases. It’s all about the overall experience; I’m becoming convinced that cloud-based solutions can deliver competitive robustness, availability, and value.
  2. Breaking down silos, or improving data sharing and reuse, remains a holy grail. One of the motivating use cases for Google Earth Builder is a common story: Different groups maintain different datasets, but you want to provide a common, up-to-date view of all the data. On this blog, we’ve explored different approaches to this challenge, ranging from centralizing your data to various schemes for synchronizing or exchanging it continuously or just-in-time. I’m not convinced that Google Earth Builder could serve as an organization’s primary spatial data store (e.g., see James Fee’s post), but I can see it providing incentives for groups within an organization to share data.
  3. The Data Volume Villain is alive and well. I was happy to hear that some customers are providing data to Google Earth Builder by sending hard disks. This tells us that data volumes remain a real challenge, and that (IMO) Google is responding in the right way.
  4. APIs will be available to load data from other systems. When asked about importing from spatial databases and web services, they said APIs are planned to enable third party solutions to do just that – we will certainly be watching with interest! As with my Fusion Tables example, an interim solution is to export and transform your data into a format that Google Earth Builder understands. This could be integrated with their REST upload API for an end-to-end solution.

Your Thoughts on Google Earth Builder?
What’s your take on Google’s latest geospatial cloud offering? Will you be further investigating Google Earth Builder, or is it not on your radar? Why or why not?

About Data Cloud Computing Data Silos Google Fusion Tables Google Maps Spatial Data Web Mapping

Paul Nalos

Comments

Leave a Reply

Your email address will not be published. Required fields are marked *

Related Posts