Google Fusion Tables: Web-Centered Data Management and

Collaboration

Hector Gonzalez, Alon Y. Halevy, Christian S. Jensen, Anno Langen, Jayant Madhavan, Rebecca Shapley, Warren Shen, Jonathan Goldberg-KidonGoogle Inc.

Proceedings of the 2010 international conference on Management of data(SIGMOD '10)

Introduction

• Cloud, Web, Powerful PC devices• How would we design data management

functionality for today's connected world?

Introduction

• The design goals of Fusion Tables • Functionality support of this design.• Other Paper provides architecture and

implementation.• Google Fusion Tables: Data Management,

Integration and Collaboration in the Cloud. Proceedings of the Symposium on Cloud Computing, 2010

Design Foundations

• Replace traditional database management? • Applications into the cloud?• Underlying Principles?– Small set of guiding principles – pay-as-you-go

Design Foundations

• New Application– Ecologists in the rain forests of Costa Rica– Circle of blue.– Current status of health clinics– The International Coffee Organization– Epidemiologist – Visualize data for senator– MTBGuru– Dairy farm in Brazil, manage in Thailand and California

Design Foundations

Underlying Principles• Provide Seamless Integration with the Web– Public Datasets for search engine– Visualization on Web– Powerful Collaboration

• Emphasize Ease of Use

Design Foundations

Underlying Principles• Provide Incentives for Sharing Data– loss of attribution– misuse and corruption of their data– others not being able to find the data easily.

• Facilitate Collaboration– discuss and comment

Data Management with Fusion Tables

• Data Acquisition– Upload file– Ease of use, fewer steps– No schema, type– System specify data of column to the type.– If they so desire, user can specify data types.

Data Management with Fusion Tables

• Data Acquisition– Upload file– Ease of use, fewer steps– No schema, type– System specify data of column to the type.– If they so desire, user can specify data types.

Data Management with Fusion Tables

• Data Sharing and Collaboration– Attribution and export– Search– Sharing and integration– Discussions

Data Management with Fusion Tables

• Data Sharing and Collaboration– Sharing and integration

Data Management with Fusion Tables

• Data Sharing and Collaboration– Discussions

Data Manipulation and Visualization

• Table, Map, Intensity map, Line, Bar, Pie, Scatte, Timeline

Data Manipulation and Visualization

• Table, Map, Intensity map, Line, Bar, Pie, Scatte, Timeline

Data Manipulation and Visualization

• Table, Map, Intensity map, Line, Bar, Pie, Scatte, Timeline

Data Manipulation and Visualization

• Table, Map, Intensity map, Line, Bar, Pie, Scatte, Timeline

Data Manipulation and Visualization

• Table, Map, Intensity map, Line, Bar, Pie, Scatte, Timeline

Data Manipulation and Visualization

• Table, Map, Intensity map, Line, Bar, Pie, Scatte, Timeline

Data Manipulation and Visualization

• HTML snippet

Fusion Tables API

• Platform for data management and collaboration

• Provide developers to extend the others• API for creating, inserting, deleting, and

updating rows in a table.• Authenticated through pre-existing methods

for all Google properties.

Related Work

• Several online database management tools exist– ManyEyes (many-eyes.com)– DabbleDB (dabbledb.com)– Socrata (socrata.com)– Factual (factual.com)

• Fusion Table– collaboration aspects of

data management and handles larger datasets.

Conclusions

• Much larger class of users– manage their data– integrated with their other online activities

• data owners to publish data on the Web• easier for users to discover data• Provide– more expressive data modeling– query capabilities– adequate performance on larger datasets.