Difference between revisions of "Human Centered Data Science (Fall 2019)/Schedule"

From CommunityData
(some updates for 2019)
 
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=== Week 2: October 3 ===
 
=== Week 2: October 3 ===
[[HCDS_(Fall_2019)/Day_2_plan|Day 2 plan]]
 
 
 
;Ethical considerations: ''privacy, informed consent and user treatment''
 
 
 
;Assignments due
 
*Week 1 reading reflection
 
 
;Agenda
 
{{:HCDS (Fall 2019)/Day 2 plan}}
 
 
 
;Readings assigned
 
* Read:  boyd, danah and Crawford, Kate, Six Provocations for Big Data (September 21, 2011). A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society, September 2011. Available at SSRN: https://ssrn.com/abstract=1926431 or http://dx.doi.org/10.2139/ssrn.1926431
 
 
 
;Homework assigned
 
* Reading reflection
 
* [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A1:_Data_curation|A1: Data curation]]
 
 
;Resources
 
* Nissenbaum, Helen, [https://crypto.stanford.edu/portia/papers/RevnissenbaumDTP31.pdf Privacy as Contextual Integrity]
 
* National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. [https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/index.html ''The Belmont Report.''] U.S. Department of Health and Human Services, 1979.
 
* Bethan Cantrell, Javier Salido, and Mark Van Hollebeke (2016). ''[http://datworkshop.org/papers/dat16-final38.pdf Industry needs to embrace data ethics: Here's how it could be done]''. Workshop on Data and Algorithmic Transparency (DAT'16). http://datworkshop.org/
 
* Javier Salido (2012). ''[http://download.microsoft.com/download/D/1/F/D1F0DFF5-8BA9-4BDF-8924-7816932F6825/Differential_Privacy_for_Everyone.pdf Differential Privacy for Everyone].'' Microsoft Corporation Whitepaper.
 
* Markham, Annette and Buchanan, Elizabeth. [https://aoir.org/reports/ethics2.pdf ''Ethical Decision-Making and Internet Researchers.''] Association for Internet Research, 2012.
 
* Hill, Kashmir. [https://www.forbes.com/sites/kashmirhill/2014/06/28/facebook-manipulated-689003-users-emotions-for-science/#6a01653e197c ''Facebook Manipulated 689,003 Users' Emotions For Science.''] Forbes, 2014.
 
* Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. Hancock [http://www.pnas.org/content/111/24/8788.full ''Experimental evidence of massive-scale emotional contagion through social networks.''] PNAS 2014 111 (24) 8788-8790; published ahead of print June 2, 2014.
 
* Barbaro, Michael and Zeller, Tom. [http://query.nytimes.com/gst/abstract.html?res=9E0CE3DD1F3FF93AA3575BC0A9609C8B63&legacy=true ''A Face Is Exposed for AOL Searcher No. 4417749.''] New York Times, 2008.
 
* Zetter, Kim. [https://www.wired.com/2012/06/wmw-arvind-narayanan/ ''Arvind Narayanan Isn’t Anonymous, and Neither Are You.''] WIRED, 2012.
 
* Gray, Mary. [http://culturedigitally.org/2014/07/when-science-customer-service-and-human-subjects-research-collide-now-what/ ''When Science, Customer Service, and Human Subjects Research Collide. Now What?''] Culture Digitally, 2014.
 
* Tene, Omer and Polonetsky, Jules. [https://www.stanfordlawreview.org/online/privacy-paradox-privacy-and-big-data/ ''Privacy in the Age of Big Data.''] Stanford Law Review, 2012.
 
* Dwork, Cynthia. [https://www.microsoft.com/en-us/research/wp-content/uploads/2008/04/dwork_tamc.pdf ''Differential Privacy: A survey of results'']. Theory and Applications of Models of Computation , 2008.
 
* Hsu, Danny. [http://blog.datasift.com/2015/04/09/techniques-to-anonymize-human-data/ ''Techniques to Anonymize Human Data.''] Data Sift, 2015.
 
* Metcalf, Jacob. [http://ethicalresolve.com/twelve-principles-of-data-ethics/ ''Twelve principles of data ethics'']. Ethical Resolve, 2016.
 
<br/>
 
<hr/>
 
<br/>
 
 
=== Week 3: October 10 ===
 
 
[[HCDS_(Fall_2019)/Day_3_plan|Day 3 plan]]
 
[[HCDS_(Fall_2019)/Day_3_plan|Day 3 plan]]
  
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=== Week 4: October 17 ===
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=== Week 3: October 10 ===
 
[[HCDS_(Fall_2019)/Day_4_plan|Day 4 plan]]
 
[[HCDS_(Fall_2019)/Day_4_plan|Day 4 plan]]
 
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=== Week 5: October 24 ===
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=== Week 4: October 17 ===
 
[[HCDS_(Fall_2019)/Day_5_plan|Day 5 plan]]
 
[[HCDS_(Fall_2019)/Day_5_plan|Day 5 plan]]
  
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;Crowdwork research resources
 
;Crowdwork research resources
 
* WeArDynamo contributors. ''[http://wiki.wearedynamo.org/index.php?title=Basics_of_how_to_be_a_good_requester How to be a good requester]'' and ''[http://wiki.wearedynamo.org/index.php?title=Guidelines_for_Academic_Requesters Guidelines for Academic Requesters]''. Wearedynamo.org
 
* WeArDynamo contributors. ''[http://wiki.wearedynamo.org/index.php?title=Basics_of_how_to_be_a_good_requester How to be a good requester]'' and ''[http://wiki.wearedynamo.org/index.php?title=Guidelines_for_Academic_Requesters Guidelines for Academic Requesters]''. Wearedynamo.org
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<hr/>
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=== Week 5: October 24 ===
 +
[[HCDS_(Fall_2019)/Day_2_plan|Day 2 plan]]
 +
 +
 +
;Ethical considerations: ''privacy, informed consent and user treatment''
  
  
 +
;Assignments due
 +
*Week 1 reading reflection
  
 +
;Agenda
 +
{{:HCDS (Fall 2019)/Day 2 plan}}
 +
 +
 +
;Readings assigned
 +
* Read:  boyd, danah and Crawford, Kate, Six Provocations for Big Data (September 21, 2011). A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society, September 2011. Available at SSRN: https://ssrn.com/abstract=1926431 or http://dx.doi.org/10.2139/ssrn.1926431
 +
 +
 +
;Homework assigned
 +
* Reading reflection
 +
* [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A1:_Data_curation|A1: Data curation]]
 +
 +
;Resources
 +
* Nissenbaum, Helen, [https://crypto.stanford.edu/portia/papers/RevnissenbaumDTP31.pdf Privacy as Contextual Integrity]
 +
* National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. [https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/index.html ''The Belmont Report.''] U.S. Department of Health and Human Services, 1979.
 +
* Bethan Cantrell, Javier Salido, and Mark Van Hollebeke (2016). ''[http://datworkshop.org/papers/dat16-final38.pdf Industry needs to embrace data ethics: Here's how it could be done]''. Workshop on Data and Algorithmic Transparency (DAT'16). http://datworkshop.org/
 +
* Javier Salido (2012). ''[http://download.microsoft.com/download/D/1/F/D1F0DFF5-8BA9-4BDF-8924-7816932F6825/Differential_Privacy_for_Everyone.pdf Differential Privacy for Everyone].'' Microsoft Corporation Whitepaper.
 +
* Markham, Annette and Buchanan, Elizabeth. [https://aoir.org/reports/ethics2.pdf ''Ethical Decision-Making and Internet Researchers.''] Association for Internet Research, 2012.
 +
* Hill, Kashmir. [https://www.forbes.com/sites/kashmirhill/2014/06/28/facebook-manipulated-689003-users-emotions-for-science/#6a01653e197c ''Facebook Manipulated 689,003 Users' Emotions For Science.''] Forbes, 2014.
 +
* Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. Hancock [http://www.pnas.org/content/111/24/8788.full ''Experimental evidence of massive-scale emotional contagion through social networks.''] PNAS 2014 111 (24) 8788-8790; published ahead of print June 2, 2014.
 +
* Barbaro, Michael and Zeller, Tom. [http://query.nytimes.com/gst/abstract.html?res=9E0CE3DD1F3FF93AA3575BC0A9609C8B63&legacy=true ''A Face Is Exposed for AOL Searcher No. 4417749.''] New York Times, 2008.
 +
* Zetter, Kim. [https://www.wired.com/2012/06/wmw-arvind-narayanan/ ''Arvind Narayanan Isn’t Anonymous, and Neither Are You.''] WIRED, 2012.
 +
* Gray, Mary. [http://culturedigitally.org/2014/07/when-science-customer-service-and-human-subjects-research-collide-now-what/ ''When Science, Customer Service, and Human Subjects Research Collide. Now What?''] Culture Digitally, 2014.
 +
* Tene, Omer and Polonetsky, Jules. [https://www.stanfordlawreview.org/online/privacy-paradox-privacy-and-big-data/ ''Privacy in the Age of Big Data.''] Stanford Law Review, 2012.
 +
* Dwork, Cynthia. [https://www.microsoft.com/en-us/research/wp-content/uploads/2008/04/dwork_tamc.pdf ''Differential Privacy: A survey of results'']. Theory and Applications of Models of Computation , 2008.
 +
* Hsu, Danny. [http://blog.datasift.com/2015/04/09/techniques-to-anonymize-human-data/ ''Techniques to Anonymize Human Data.''] Data Sift, 2015.
 +
* Metcalf, Jacob. [http://ethicalresolve.com/twelve-principles-of-data-ethics/ ''Twelve principles of data ethics'']. Ethical Resolve, 2016.
 
<br/>
 
<br/>
 
<hr/>
 
<hr/>
 
<br/>
 
<br/>
 +
  
 
=== Week 6: October 31 ===
 
=== Week 6: October 31 ===

Revision as of 22:01, 4 September 2019

This page is a work in progress.


Week 1: September 26

Day 1 plan

Introduction to Human Centered Data Science
What is data science? What is human centered? What is human centered data science?
Assignments due
Agenda

HCDS (Fall 2019)/Day 1 plan

Readings assigned
Homework assigned
  • Reading reflection
Resources




Week 2: October 3

Day 3 plan


Reproducibility and Accountability
data curation, preservation, documentation, and archiving; best practices for open scientific research
Assignments due
  • Week 2 reading reflection
Agenda

HCDS (Fall 2019)/Day 3 plan

Readings assigned
Homework assigned
  • Reading reflection
Resources


Assignment 1 Data curation resources






Week 3: October 10

Day 4 plan

Interrogating datasets
causes and consequences of bias in data; best practices for selecting, describing, and implementing training data


Assignments due
Agenda

HCDS (Fall 2019)/Day 4 plan

Readings assigned (Read both, reflect on one)
Homework assigned


Resources




Week 4: October 17

Day 5 plan


Introduction to mixed-methods research
Big data vs thick data; integrating qualitative research methods into data science practice; crowdsourcing


Assignments due
  • Reading reflection


Agenda

HCDS (Fall 2019)/Day 5 plan


Readings assigned (Read both, reflect on one)


Homework assigned


Qualitative research methods resources
Wikipedia gender gap research resources
Crowdwork research resources





Week 5: October 24

Day 2 plan


Ethical considerations
privacy, informed consent and user treatment


Assignments due
  • Week 1 reading reflection
Agenda

HCDS (Fall 2019)/Day 2 plan


Readings assigned


Homework assigned
Resources





Week 6: October 31

Day 6 plan

Interrogating algorithms
algorithmic fairness, transparency, and accountability; methods and contexts for algorithmic audits
Assignments due
Agenda

HCDS (Fall 2019)/Day 6 plan

Readings assigned


Homework assigned
  • Reading reflection


Resources





Week 7: November 7

Day 7 plan

Critical approaches to data science
power, data, and society; ethics of crowdwork


Assignments due
  • Reading reflection
  • A3: Crowdwork ethnography


Agenda

HCDS (Fall 2019)/Day 7 plan

Readings assigned (read both, reflect on one)
Homework assigned


Resources





Week 8: November 14

Day 8 plan

Human-centered algorithm design
algorithmic interpretibility; human-centered methods for designing and evaluating algorithmic systems


Assignments due
  • Reading reflection


Agenda

HCDS (Fall 2019)/Day 8 plan

Readings assigned
Homework assigned
  • Reading reflection
Resources





Week 9: November 21

Day 9 plan

Data science for social good
Community-based and participatory approaches to data science; Using data science for society's benefit
Assignments due
  • Reading reflection
  • A4: Final project plan
Agenda

HCDS (Fall 2019)/Day 9 plan

Readings assigned
Homework assigned
  • Reading reflection
Resources





Week 10: November 28 (No Class Session)

Readings assigned
  • NONE
Homework assigned
  • A5: Final presentation
Resources





Week 11: December 5

Day 11 plan

Final presentations
course wrap up, presentation of student projects


Assignments due
  • A5: Final presentation


Agenda

HCDS (Fall 2019)/Day 11 plan

Readings assigned
  • none!
Homework assigned
  • A6: Final project report (due 12/9 by 11:59pm)
Resources
  • one




Week 12: Finals Week (No Class Session)

  • NO CLASS
  • A6: FINAL PROJECT REPORT DUE BY 5:00PM on Tuesday, December 10
  • LATE PROJECT SUBMISSIONS NOT ACCEPTED.