YFCC tutorial: privacy-aware visualization

The lbsn structure data scheme is in active development. We started writing a documentation here, but we’re far away from completeness. For this reason, I created this complete and working guide for demonstrating privacy-aware processing of lbsn data on a specific visualization type (grid based aggregation).

Results

In addition to the release file, latest HTML converts of notebooks are available here:

• 01_preparations.html
• 02_yfcc_gridagg_raw.html
• 03_yfcc_gridagg_hll.html
• 04_interpretation.html

There are two additional HTMLs produced in notebooks:

• yfcc_compare_raw_hll.html includes all figures and allows to compare raw/HLL through HTML tabs.
• yfcc_usercount_est.html interactive map of worldwide user count, for comparison of raw/HLL per bin.

There are a couple of additional notebooks available:

• the HLL Introduction (01_hll_intro.ipynb) explains basic concepts and tools for working with the privacy-aware lbsn data
• the Privacy Test Alex explores two possible attack vectors through an intersection attack
• the Outlier Analysis shows how to analyze outliers across multiple geo-accuracy levels (Geohash)

raw:
hll: