Visit Challenge.gov for the Official Rules
Open for submissions October 1, 2020 - May 17, 2021
|Team||Total Awards||Open Sourced||Development Contest||APA Citation|
|Minutemen||$58,000.00||Yes||Repository link||McKenna R. (2021). Adaptive Granularity Mechanism (version 1.0). URL: https://github.com/ryan112358/nist-synthetic-data-2021|
|DPSyn||$48,000.00||Yes||Repository link||Chen A., Li N., Li Z., Wang T. (2021). DPSyn: An algorithm for synthesizing microdata for data analysis while satisfying differential privacy (version 1.0). URL: https://github.com/agl-c/deid2_dpsyn|
|jimking100||$24,000.00||Yes||Repository link||King, J. (2021). Privitized Histograms (Version 1.0.0) [Computer software]. https://github.com/JimKing100/PrivacyHistos|
|Duke Privacy Team||$12,000.00||--||--|
|MGD: A Utility Metric for Private Data Publication||1st||$5,000.00|
|Practical DP Metric||2nd||$3,000.00|
|Confusion Matrix Metric||2nd||$3,000.00|
|Bounding Utility Loss via Classifiers||3rd||$2,000.00|
|Confusion Matrix Metric||People's Choice Award||$1,000.00|
Large data sets containing personally identifiable information (PII) are exceptionally valuable resources for research and policy analysis in a host of fields supporting America's First Responders such as emergency planning and epidemiology.
Temporal map data—information that is geographically situated and may change over time—is of particular interest to the public safety community in applications such as optimizing response time and personnel placement, natural disaster response, epidemic tracking, demographic data and civic planning. Yet, the ability to track a person's location over a period of time presents particularly serious privacy concerns.
The Differential Privacy Temporal Map Challenge will invite solvers to develop algorithms and metrics that preserve data utility while guaranteeing individual privacy is protected.
Participants will compete in a series of coding sprints using differential privacy methods on temporal map data. These data sets may contain the records of hundreds or thousands of individuals, each contributing to a sequence of events. The goal is to create a privacy-preserving dashboard map that shows changes across different map segments over time.
The best solutions will be publicly recognized and up to $276,000 in cash prizes may be awarded to top-performing teams.
The NIST PSCR Differential Privacy Temporal Map Challenge follows on the success of the 2018 Differential Privacy Synthetic Data Challenge, extending the reach and utility of differential privacy algorithms.
|Preregistration||August 24, 2020|
|Open to submissions||October 1, 2020 - January 5, 2021|
|NIST PSCR Compliance check (for public voting)||January 5-6, 2021|
|Public voting||January 8-21, 2021|
|Judging and Evaluation||January 5, 2021 - February 2, 2021|
|Winners Announced||February 4, 2021|
|Preregistration||August 24, 2020|
|Sprint #1 - Participation||October 1, 2020 - November 15, 2020|
|Sprint #1 - Evaluation||November 15, 2020 - December 11, 2020|
|Sprint #1 - Winners announced||January 5, 2021|
|Sprint #2 - Participation||January 6, 2021 - February 22, 2021|
|Sprint #2 - Evaluation||February 22, 2021 - March 22, 2021|
|Sprint #2 - Winners announced||March 23, 2021|
|Sprint #3 - Participation||March 29, 2021 - May 17, 2021|
|Sprint #3 - Evaluation||May 17, 2021 - June 15, 2021|
|Sprint #3 - Winners announced||June 16, 2021|
|Open Source Deposit - Submissions due||July 5, 2021|
|Development Plan - Submissions due||July 5, 2021|
|Development Plan - Evaluation||July 5-9, 2021|
|Development Plan - Winners announced||July 14, 2021|
|Development Execution - Submission due||October 9, 2021|
|Development Execution - Evaluation||October 9-23, 2021|
|Development Execution - Winners announced||October 27, 2021|
*NOTE: NIST reserves the right to revise the dates at any time
Looking for great resources to get started? Here are a few ways to learn more about the math behind differential privacy.
Email: psprizes [at] nist.gov