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Public Data
Enhancing Data Discovery and Exploration Benjamin Yolken (yolken@google.com)
September 2011
Overview
Disseminating public statistics Google tools
- Public Data Explorer
- Fusion Tables
- Refine
Public Data Enhancing Data Discovery and Exploration Benjamin Yolken - - PowerPoint PPT Presentation
Public Data Enhancing Data Discovery and Exploration Benjamin Yolken - - PowerPoint PPT Presentation
Public Data Enhancing Data Discovery and Exploration Benjamin Yolken (yolken@google.com) September 2011 Overview Disseminating public statistics Google tools Public Data Explorer Fusion Tables Refine Conclusion Disseminating
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Disseminating Statistics
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Objective
Make public statistics accessible, useful, and well-organized.
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Public statistics (2)
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Public statistics (4)
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Accessible...
(1) Access: Data need to be online and findable
- Provider web sites
- Third-party aggregators
- Search engines
(2) Understanding: Statisticians aren't the only users
- Lay users: Teachers, students, journalists, policy makers
- Computers: Search engines
- If not accessible to non-experts, data can become unused or,
worse, misused
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Useful...
There are a lot of distractions today: tables and simple plots are not enough Need to engage not just with users' eyes, but also their brains
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Well-organized...
Go beyond flat lists of data...
- Topics
- Time periods
- Geographic regions
- Formats
- Languages, etc...
Ultimately, depends on having good metadata
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Google Tools
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Public Data Explorer (PDE) [Link]
What it is:
- Stand-alone product for interactively exploring and visualizing rich
datasets
- Visualizations can be shared or embedded on 3rd party sites
What it's good for:
- Reaching out to non-expert users
- Getting traffic to your site
- Categorical, aggregated, time-series data
Caveats:
- Datasets must be in Dataset Publishing Language (DSPL) format
○ Have some tools to help ○ Working on converters from other formats like SDMX
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PDE: Demo
Demo link
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PDE: Embed
Demo link
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Fusion Tables [Link]
What it is:
- Product for creating, editing, and sharing tabular data
What it's good for:
- Table edits and transformations: joining, filtering, aggregating, etc.
- Static visualizations, particularly maps
- Exposing data to users via APIs
Caveats:
- Not connected to PDE (yet)
- Not as useful for time series exploration
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Fusion Tables: Demo
Demo link
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Google Refine
What it is:
- Desktop-based tool for cleaning up and transforming tabular data
What it's good for:
- Bulk data transformations
- Faceted data browsing
- Outlier-detection and cleanup
Caveats:
- No collaboration features (yet)
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Google Refine
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Conclusion
Need to make statistics accessible, useful, organized Google has tools that can help Key advice: Think about the users, their needs Really exciting area, only scratched the surface in terms of what's possible
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Thank you! Questions?
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Appendix
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PDE Intro Video
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PDE: Metadata
Dataset Publishing Language (DSPL)
- Designed for interactive exploration and visualization
- Released under BSD, open source license
- Combines data tables (CSV) with metadata (XML)
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