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; | ;Data Science and Organizational Communication: | ||
; | ;Principal instructor: [[User:Groceryheist|Nate TeBlunthuis]] | ||
;Course Catalog Description: Fundamental principles of data science and its implications, including research ethics; data privacy; legal frameworks; algorithmic bias, transparency, fairness and accountability; data provenance, curation, preservation, and reproducibility; human computation; data communication and visualization; the role of data science in organizational context and the societal impacts of data science. | ;Course Catalog Description: Fundamental principles of data science and its implications, including research ethics; data privacy; legal frameworks; algorithmic bias, transparency, fairness and accountability; data provenance, curation, preservation, and reproducibility; human computation; data communication and visualization; the role of data science in organizational context and the societal impacts of data science. | ||
== Course Description == | == Course Description == | ||
The rise of "data science" reflects a broad and ongoing shift in how many teams, organizational leaders, communities of practice, and entire industries create and use knowledge. This class teaches "data science" as practiced by data-intensive knowledge workers but also as it is positioned in historical, organizational, institutional, and societal contexts. Students will gain an | The rise of "data science" reflects a broad and ongoing shift in how many teams, organizational leaders, communities of practice, and entire industries create and use knowledge. This class teaches "data science" as practiced by data-intensive knowledge workers but also as it is positioned in historical, organizational, institutional, and societal contexts. Students will gain an appriciation for the technical and intellectual aspects of data science, consider critical questions about how data science is often practiced, and envision ethical and effective science practice in their current and future organiational roles. The format of the class will be a mix of lecture, discussion, in-class activities, and qualitative and quantitative research assignments. | ||
The course is designed around two high-stakes projects. In the first stage of the students will attend the Community Data Science Workshop (CDSC). I am one of the organizers and instructors of this three week intensive workshop on basic programming and data analysis skills. The first course project is to apply these skills together with the conceptual material from this course we have covered so far to conduct an original data analysis on a topic of the student's interest. The second high-stakes project is a critical analysis of an organization or work team. For this project students will serve as consultants to an organizational unit involved in data science. Through interviews and workplace observations they will gain an understanding of the socio-technical and organizational context of their team. They will then synthesize this understanding with the knowledge they gained from the course material to compose a report offering actionable insights to their team. | The course is designed around two high-stakes projects. In the first stage of the students will attend the Community Data Science Workshop (CDSC). I am one of the organizers and instructors of this three week intensive workshop on basic programming and data analysis skills. The first course project is to apply these skills together with the conceptual material from this course we have covered so far to conduct an original data analysis on a topic of the student's interest. The second high-stakes project is a critical analysis of an organization or work team. For this project students will serve as consultants to an organizational unit involved in data science. Through interviews and workplace observations they will gain an understanding of the socio-technical and organizational context of their team. They will then synthesize this understanding with the knowledge they gained from the course material to compose a report offering actionable insights to their team. | ||
== Learning Objectives == | == Learning Objectives == | ||
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* Combine quantitative and qualitative data to generate critical insights into human behavior. | * Combine quantitative and qualitative data to generate critical insights into human behavior. | ||
* Discuss and evaluate ethical, social, organizational and legal trade-offs of different data analysis, testing, curation, and sharing methods. | * Discuss and evaluate ethical, social, organizational and legal trade-offs of different data analysis, testing, curation, and sharing methods. | ||
== Schedule == | == Schedule == | ||
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<br/> | <br/> | ||
=== Week 1 === | === Week 1: === | ||
<!-- [[HCDS_(Fall_2018)/Day_1_plan|Day 1 plan]] --> | <!-- [[HCDS_(Fall_2018)/Day_1_plan|Day 1 plan]] --> | ||
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;Assignments due | ;Assignments due | ||
* Fill out the pre-course survey | |||
* Attend week 1 of CDSW | |||
* Read: Provost, Foster, and Tom Fawcett. [http://online.liebertpub.com/doi/pdf/10.1089/big.2013.1508 ''Data science and its relationship to big data and data-driven decision making.''] Big Data 1.1 (2013): 51-59. | * Read: Provost, Foster, and Tom Fawcett. [http://online.liebertpub.com/doi/pdf/10.1089/big.2013.1508 ''Data science and its relationship to big data and data-driven decision making.''] Big Data 1.1 (2013): 51-59. | ||
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;Readings assigned | ;Readings assigned | ||
* Read: Barocas, Solan and Nissenbaum, Helen. [https://www.nyu.edu/projects/nissenbaum/papers/BigDatasEndRun.pdf ''Big Data's End Run around Anonymity and Consent'']. In ''Privacy, Big Data, and the Public Good''. 2014. | * Read: Barocas, Solan and Nissenbaum, Helen. [https://www.nyu.edu/projects/nissenbaum/papers/BigDatasEndRun.pdf ''Big Data's End Run around Anonymity and Consent'']. In ''Privacy, Big Data, and the Public Good''. 2014. | ||
;Homework assigned | ;Homework assigned | ||
* | * Reading reflection | ||
* Attend week | * Attend week 2 of CDSW | ||
<!-- ;Resources --> | <!-- ;Resources --> | ||
* Kling, Rob and Star, Susan Leigh. [https://scholarworks.iu.edu/dspace/bitstream/handle/2022/1798/wp97-04B.html ''Human Centered Systems in the Perspective of Organizational and Social Informatics.''] 1997 | |||
<!-- * Aragon, C. et al. (2016). [https://cscw2016hcds.files.wordpress.com/2015/10/cscw_2016_human-centered-data-science_workshop.pdf ''Developing a Research Agenda for Human-Centered Data Science.''] Human Centered Data Science workshop, CSCW 2016. --> | <!-- * Aragon, C. et al. (2016). [https://cscw2016hcds.files.wordpress.com/2015/10/cscw_2016_human-centered-data-science_workshop.pdf ''Developing a Research Agenda for Human-Centered Data Science.''] Human Centered Data Science workshop, CSCW 2016. --> | ||
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=== Week 2 === | === Week 2: === | ||
<!-- [[HCDS_(Fall_2018)/Day_2_plan|Day 2 plan]] --> | <!-- [[HCDS_(Fall_2018)/Day_2_plan|Day 2 plan]] --> | ||
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;Assignments due | ;Assignments due | ||
* Week | * Week 1 reading reflection | ||
* | * | ||
<!-- ;Agenda --> | <!-- ;Agenda --> | ||
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;Homework assigned | ;Homework assigned | ||
* | * Reading reflection | ||
* Attend week 2 of CDSW | * Attend week 2 of CDSW | ||
* [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A1:_Data_curation|Assignment 1: Data curation]] | |||
<!-- ;Resources --> | <!-- ;Resources --> | ||
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;Assignments due | ;Assignments due | ||
* Week | * Week 2 reading reflection | ||
* Attend week 2 of CDSW | * Attend week 2 of CDSW | ||
<!-- ;Agenda --> | <!-- ;Agenda --> | ||
<!-- {{:HCDS (Fall 2018)/Day 3 plan}} --> | <!-- {{:HCDS (Fall 2018)/Day 3 plan}} --> | ||
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;Homework assigned | ;Homework assigned | ||
* | * Reading reflection | ||
* Attend week 3 of CDSW | * Attend week 3 of CDSW | ||
<!-- ;Resources --> | <!-- ;Resources --> | ||
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<!-- * Hickey, Walt. [https://fivethirtyeight.com/features/the-bechdel-test-checking-our-work/ ''The Bechdel Test: Checking Our Work'']. FiveThirtyEight, 2014. --> | <!-- * Hickey, Walt. [https://fivethirtyeight.com/features/the-bechdel-test-checking-our-work/ ''The Bechdel Test: Checking Our Work'']. FiveThirtyEight, 2014. --> | ||
<!-- * J. Priem, D. Taraborelli, P. Groth, C. Neylon (2010), ''[http://altmetrics.org/manifesto Altmetrics: A manifesto]'', 26 October 2010. --> | <!-- * J. Priem, D. Taraborelli, P. Groth, C. Neylon (2010), ''[http://altmetrics.org/manifesto Altmetrics: A manifesto]'', 26 October 2010. --> | ||
<!-- <\!-- --> | <!-- <\!-- --> | ||
<!-- * TeBlunthuis, N., Shaw, A., and Hill, B.M. (2018). Revisiting "The rise and decline" in a population of peer production projects. In ''Proceedings of the 2018 ACM Conference on Human Factors in Computing Systems (CHI '18)''. https://doi.org/10.1145/3173574.3173929 --> | <!-- * TeBlunthuis, N., Shaw, A., and Hill, B.M. (2018). Revisiting "The rise and decline" in a population of peer production projects. In ''Proceedings of the 2018 ACM Conference on Human Factors in Computing Systems (CHI '18)''. https://doi.org/10.1145/3173574.3173929 --> | ||
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<!-- * Aschwanden, Christie. [https://fivethirtyeight.com/features/science-isnt-broken/ ''Science Isn't Broken''] FiveThirtyEight, 2015. --> | <!-- * Aschwanden, Christie. [https://fivethirtyeight.com/features/science-isnt-broken/ ''Science Isn't Broken''] FiveThirtyEight, 2015. --> | ||
<!-- -\-> --> | <!-- -\-> --> | ||
<!-- *Chapter 2 [https://www.practicereproducibleresearch.org/core-chapters/2-assessment.html "Assessing Reproducibility"] and Chapter 3 [https://www.practicereproducibleresearch.org/core-chapters/3-basic.html "The Basic Reproducible Workflow Template"] from ''The Practice of Reproducible Research'' University of California Press, 2018. --> | <!-- *Chapter 2 [https://www.practicereproducibleresearch.org/core-chapters/2-assessment.html "Assessing Reproducibility"] and Chapter 3 [https://www.practicereproducibleresearch.org/core-chapters/3-basic.html "The Basic Reproducible Workflow Template"] from ''The Practice of Reproducible Research'' University of California Press, 2018. --> | ||
<!-- * sample code for API calls ([http://paws-public.wmflabs.org/paws-public/User:Jtmorgan/data512_a1_example.ipynb view the notebook], [http://paws-public.wmflabs.org/paws-public/User:Jtmorgan/data512_a1_example.ipynb?format=raw download the notebook]). --> | <!-- * sample code for API calls ([http://paws-public.wmflabs.org/paws-public/User:Jtmorgan/data512_a1_example.ipynb view the notebook], [http://paws-public.wmflabs.org/paws-public/User:Jtmorgan/data512_a1_example.ipynb?format=raw download the notebook]). --> | ||
<!-- *''See [[Human_Centered_Data_Science/Datasets#Dataset_documentation_examples|the datasets page]] for examples of well-documented and not-so-well documented open datasets.'' --> | <!-- *''See [[Human_Centered_Data_Science/Datasets#Dataset_documentation_examples|the datasets page]] for examples of well-documented and not-so-well documented open datasets.'' --> | ||
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<hr/> | <hr/> | ||
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=== Week 4 === | === Week 4: October 18 === | ||
<!-- [[HCDS_(Fall_2018)/Day_4_plan|Day 4 plan]] --> | <!-- [[HCDS_(Fall_2018)/Day_4_plan|Day 4 plan]] --> | ||
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;Assignments due | ;Assignments due | ||
* | * Reading reflection | ||
<!-- ;Agenda --> | <!-- ;Agenda --> | ||
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;Homework assigned | ;Homework assigned | ||
* | * Reading reflection | ||
* | * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A1:_Data_curation|A1: Data curation]] | ||
<!-- ;Resources --> | <!-- ;Resources --> | ||
<!-- * Olteanu, A., Castillo, C., Diaz, F., & Kiciman, E. (2016). ''[http://kiciman.org/wp-content/uploads/2017/08/SSRN-id2886526.pdf Social data: Biases, methodological pitfalls, and ethical boundaries]. --> | <!-- * Olteanu, A., Castillo, C., Diaz, F., & Kiciman, E. (2016). ''[http://kiciman.org/wp-content/uploads/2017/08/SSRN-id2886526.pdf Social data: Biases, methodological pitfalls, and ethical boundaries]. --> | ||
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=== Week 5 === | === Week 5: === | ||
; Technology and Organizing | ; Technology and Organizing | ||
; Assignments due | ; Assignments due | ||
* Week | * Week 4 reading reflection | ||
* | * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A1:_Data_curation|A1: Data curation]] | ||
; Readings assigned | ; Readings assigned | ||
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; Homework Assigned | ; Homework Assigned | ||
* | * Reading reflection | ||
* A2: | * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A2:_Bias_in_data|A2: Bias in data]] | ||
<br/> | <br/> | ||
<hr/> | <hr/> | ||
<br/> | <br/> | ||
=== Week 6 === | === Week 6: === | ||
; Data science in Organizational Contexts | ; Data science in Organizational Contexts | ||
; Assignments due | ; Assignments due | ||
* Week | * Week 5 reading reflection | ||
* A2: | * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A2:_Bias_in_data|A2: Bias in data]] | ||
;Readings assigned (Read both, reflect on one) | ;Readings assigned (Read both, reflect on one) | ||
* Wang, Tricia. ''[https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75e3d7 Why Big Data Needs Thick Data]''. Ethnography Matters, 2016. | * Wang, Tricia. ''[https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75e3d7 Why Big Data Needs Thick Data]''. Ethnography Matters, 2016. | ||
* Shilad Sen, Margaret E. Giesel, Rebecca Gold, Benjamin Hillmann, Matt Lesicko, Samuel Naden, Jesse Russell, Zixiao (Ken) Wang, and Brent Hecht. 2015. ''[http://www-users.cs.umn.edu/~bhecht/publications/goldstandards_CSCW2015.pdf Turkers, Scholars, "Arafat" and "Peace": Cultural Communities and Algorithmic Gold Standards]''. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW '15) | * Shilad Sen, Margaret E. Giesel, Rebecca Gold, Benjamin Hillmann, Matt Lesicko, Samuel Naden, Jesse Russell, Zixiao (Ken) Wang, and Brent Hecht. 2015. ''[http://www-users.cs.umn.edu/~bhecht/publications/goldstandards_CSCW2015.pdf Turkers, Scholars, "Arafat" and "Peace": Cultural Communities and Algorithmic Gold Standards]''. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW '15) | ||
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<hr/> | <hr/> | ||
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=== Week 7 === | === Week 7: October 25 === | ||
[[HCDS_(Fall_2018)/Day_5_plan|Day 5 plan]] | |||
[[:File:HCDS 2018 week 5 slides.pdf|Day 5 slides]] | |||
;Introduction to mixed-methods research: ''Big data vs thick data; integrating qualitative research methods into data science practice; | ;Introduction to mixed-methods research: ''Big data vs thick data; integrating qualitative research methods into data science practice; crowdsourcing'' | ||
;Assignments due | ;Assignments due | ||
* | * Reading reflection | ||
<!-- ;Agenda --> | <!-- ;Agenda --> | ||
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;Homework assigned | ;Homework assigned | ||
* | * Reading reflection | ||
* | <!-- * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A3:_Crowdwork_ethnography|A3: Crowdwork ethnography]] --> | ||
<!-- ;Qualitative research methods resources --> | <!-- ;Qualitative research methods resources --> | ||
<!-- * Ladner, S. (2016). ''[http://www.practicalethnography.com/ Practical ethnography: A guide to doing ethnography in the private sector]''. Routledge. --> | <!-- * Ladner, S. (2016). ''[http://www.practicalethnography.com/ Practical ethnography: A guide to doing ethnography in the private sector]''. Routledge. --> | ||
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<!-- * Usability.gov, ''[https://www.usability.gov/how-to-and-tools/methods/system-usability-scale.html System usability scale]''. --> | <!-- * Usability.gov, ''[https://www.usability.gov/how-to-and-tools/methods/system-usability-scale.html System usability scale]''. --> | ||
<!-- * Nielsen, Jakob (2000). ''[https://www.nngroup.com/articles/why-you-only-need-to-test-with-5-users/ Why you only need to test with five users]''. nngroup.com. --> | <!-- * Nielsen, Jakob (2000). ''[https://www.nngroup.com/articles/why-you-only-need-to-test-with-5-users/ Why you only need to test with five users]''. nngroup.com. --> | ||
<!-- ;Wikipedia gender gap research resources --> | <!-- ;Wikipedia gender gap research resources --> | ||
<!-- * Hill, B. M., & Shaw, A. (2013). ''[journals.plos.org/plosone/article?id=10.1371/journal.pone.0065782 The Wikipedia gender gap revisited: Characterizing survey response bias with propensity score estimation]''. PloS one, 8(6), e65782 --> | <!-- * Hill, B. M., & Shaw, A. (2013). ''[journals.plos.org/plosone/article?id=10.1371/journal.pone.0065782 The Wikipedia gender gap revisited: Characterizing survey response bias with propensity score estimation]''. PloS one, 8(6), e65782 --> | ||
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<!-- * Maximillian Klein. ''[http://whgi.wmflabs.org/gender-by-language.html Gender by Wikipedia Language]''. Wikidata Human Gender Indicators (WHGI), 2017. --> | <!-- * Maximillian Klein. ''[http://whgi.wmflabs.org/gender-by-language.html Gender by Wikipedia Language]''. Wikidata Human Gender Indicators (WHGI), 2017. --> | ||
<!-- * Source: Wagner, C., Garcia, D., Jadidi, M., & Strohmaier, M. (2015, April). ''[https://www.aaai.org/ocs/index.php/ICWSM/ICWSM15/paper/viewFile/10585/10528 It's a Man's Wikipedia? Assessing Gender Inequality in an Online Encyclopedia]''. In ICWSM (pp. 454-463). --> | <!-- * Source: Wagner, C., Garcia, D., Jadidi, M., & Strohmaier, M. (2015, April). ''[https://www.aaai.org/ocs/index.php/ICWSM/ICWSM15/paper/viewFile/10585/10528 It's a Man's Wikipedia? Assessing Gender Inequality in an Online Encyclopedia]''. In ICWSM (pp. 454-463). --> | ||
<!-- * Benjamin Collier and Julia Bear. ''[https://static1.squarespace.com/static/521c8817e4b0dca2590b4591/t/523745abe4b05150ff027a6e/1379354027662/2012+-+Collier%2C+Bear+-+Conflict%2C+confidence%2C+or+criticism+an+empirical+examination+of+the+gender+gap+in+Wikipedia.pdf Conflict, criticism, or confidence: an empirical examination of the gender gap in wikipedia contributions]''. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work (CSCW '12). DOI: https://doi.org/10.1145/2145204.2145265 --> | <!-- * Benjamin Collier and Julia Bear. ''[https://static1.squarespace.com/static/521c8817e4b0dca2590b4591/t/523745abe4b05150ff027a6e/1379354027662/2012+-+Collier%2C+Bear+-+Conflict%2C+confidence%2C+or+criticism+an+empirical+examination+of+the+gender+gap+in+Wikipedia.pdf Conflict, criticism, or confidence: an empirical examination of the gender gap in wikipedia contributions]''. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work (CSCW '12). DOI: https://doi.org/10.1145/2145204.2145265 --> | ||
<!-- * Christina Shane-Simpson, Kristen Gillespie-Lynch, Examining potential mechanisms underlying the Wikipedia gender gap through a collaborative editing task, In Computers in Human Behavior, Volume 66, 2017, https://doi.org/10.1016/j.chb.2016.09.043. (PDF on Canvas) --> | <!-- * Christina Shane-Simpson, Kristen Gillespie-Lynch, Examining potential mechanisms underlying the Wikipedia gender gap through a collaborative editing task, In Computers in Human Behavior, Volume 66, 2017, https://doi.org/10.1016/j.chb.2016.09.043. (PDF on Canvas) --> | ||
<!-- * Amanda Menking and Ingrid Erickson. 2015. ''[https://upload.wikimedia.org/wikipedia/commons/7/77/The_Heart_Work_of_Wikipedia_Gendered,_Emotional_Labor_in_the_World%27s_Largest_Online_Encyclopedia.pdf The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia]''. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). https://doi.org/10.1145/2702123.2702514 --> | <!-- * Amanda Menking and Ingrid Erickson. 2015. ''[https://upload.wikimedia.org/wikipedia/commons/7/77/The_Heart_Work_of_Wikipedia_Gendered,_Emotional_Labor_in_the_World%27s_Largest_Online_Encyclopedia.pdf The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia]''. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). https://doi.org/10.1145/2702123.2702514 --> | ||
<!-- ;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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=== Week 8 === | === Week 8: === | ||
<!-- [[HCDS_(Fall_2018)/Day_6_plan|Day 6 plan]] --> | <!-- [[HCDS_(Fall_2018)/Day_6_plan|Day 6 plan]] --> | ||
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;Assignments due | ;Assignments due | ||
* | * Reading reflection | ||
<!-- ;Agenda --> | <!-- ;Agenda --> | ||
<!-- {{:HCDS (Fall 2018)/Day 6 plan}} --> | <!-- {{:HCDS (Fall 2018)/Day 6 plan}} --> | ||
;Readings assigned | ;Readings assigned | ||
* Hill, B. M., Dailey, D., Guy, R. T., Lewis, B., Matsuzaki, M., & Morgan, J. T. (2017). ''[https://mako.cc/academic/hill_etal-cdsw_chapter-DRAFT.pdf Democratizing Data Science: The Community Data Science Workshops and Classes].'' In N. Jullien, S. A. Matei, & S. P. Goggins (Eds.), Big Data Factories: Scientific Collaborative approaches for virtual community data collection, repurposing, recombining, and dissemination. | * Hill, B. M., Dailey, D., Guy, R. T., Lewis, B., Matsuzaki, M., & Morgan, J. T. (2017). ''[https://mako.cc/academic/hill_etal-cdsw_chapter-DRAFT.pdf Democratizing Data Science: The Community Data Science Workshops and Classes].'' In N. Jullien, S. A. Matei, & S. P. Goggins (Eds.), Big Data Factories: Scientific Collaborative approaches for virtual community data collection, repurposing, recombining, and dissemination. | ||
;Homework assigned | ;Homework assigned | ||
* | * Reading reflection | ||
<!-- ;Resources --> | <!-- ;Resources --> | ||
<!-- * Ethical OS ''[https://ethicalos.org/wp-content/uploads/2018/08/Ethical-OS-Toolkit-2.pdf Toolkit]'' and ''[https://ethicalos.org/wp-content/uploads/2018/08/EthicalOS_Check-List_080618.pdf Risk Mitigation Checklist]''. EthicalOS.org. --> | <!-- * Ethical OS ''[https://ethicalos.org/wp-content/uploads/2018/08/Ethical-OS-Toolkit-2.pdf Toolkit]'' and ''[https://ethicalos.org/wp-content/uploads/2018/08/EthicalOS_Check-List_080618.pdf Risk Mitigation Checklist]''. EthicalOS.org. --> | ||
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<!-- * Julia Angwin, Jeff Larson, Surya Mattu and Lauren Kirchner. ''[https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Machine Bias: Risk Assessment in Criminal Sentencing]. Propublica, May 2018. --> | <!-- * Julia Angwin, Jeff Larson, Surya Mattu and Lauren Kirchner. ''[https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Machine Bias: Risk Assessment in Criminal Sentencing]. Propublica, May 2018. --> | ||
<!-- * [https://www.perspectiveapi.com/#/ Google's Perspective API] --> | <!-- * [https://www.perspectiveapi.com/#/ Google's Perspective API] --> | ||
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<!-- === Week 7 === --> | <!-- === Week 7 === --> | ||
<!-- <\!-- [[HCDS_(Fall_2018)/Day_7_plan|Day 7 plan]] -\-> --> | <!-- <\!-- [[HCDS_(Fall_2018)/Day_7_plan|Day 7 plan]] -\-> --> | ||
<!-- <\!-- [[:File:HCDS 2018 week 7 slides.pdf|Day 7 slides]] -\-> --> | <!-- <\!-- [[:File:HCDS 2018 week 7 slides.pdf|Day 7 slides]] -\-> --> | ||
<!-- ;Critical approaches to data science: ''power, data, and society; ethics of crowdwork'' --> | <!-- ;Critical approaches to data science: ''power, data, and society; ethics of crowdwork'' --> | ||
<!-- ;Assignments due --> | <!-- ;Assignments due --> | ||
<!-- * Reading reflection --> | <!-- * Reading reflection --> | ||
<!-- <\!-- * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A3:_Crowdwork_ethnography|A3: Crowdwork ethnography]] -\-> --> | |||
<!-- <\!-- ;Agenda -\-> --> | <!-- <\!-- ;Agenda -\-> --> | ||
<!-- <\!-- {{:HCDS (Fall 2018)/Day 7 plan}} -\-> --> | <!-- <\!-- {{:HCDS (Fall 2018)/Day 7 plan}} -\-> --> | ||
<!-- ;Readings assigned (read both, reflect on one) --> | <!-- ;Readings assigned (read both, reflect on one) --> | ||
<!-- * Read: Baumer, E. P. S. (2017). ''[http://journals.sagepub.com/doi/pdf/10.1177/2053951717718854 Toward human-centered algorithm design].'' Big Data & Society. --> | <!-- * Read: Baumer, E. P. S. (2017). ''[http://journals.sagepub.com/doi/pdf/10.1177/2053951717718854 Toward human-centered algorithm design].'' Big Data & Society. --> | ||
<!-- * Read: Amershi, S., Cakmak, M., Knox, W. B., & Kulesza, T. (2014). ''[http://www.aaai.org/ojs/index.php/aimagazine/article/download/2513/2456 Power to the People: The Role of Humans in Interactive Machine Learning].'' AI Magazine, 35(4), 105. --> | <!-- * Read: Amershi, S., Cakmak, M., Knox, W. B., & Kulesza, T. (2014). ''[http://www.aaai.org/ojs/index.php/aimagazine/article/download/2513/2456 Power to the People: The Role of Humans in Interactive Machine Learning].'' AI Magazine, 35(4), 105. --> | ||
<!-- ;Readings assigned --> | <!-- ;Readings assigned --> | ||
<!-- ;Homework assigned --> | <!-- ;Homework assigned --> | ||
<!-- * Reading reflection --> | <!-- * Reading reflection --> | ||
<!-- * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A4:_Final_project_plan|A4: Final project plan]] --> | <!-- * [[Human_Centered_Data_Science_(Fall_2018)/Assignments#A4:_Final_project_plan|A4: Final project plan]] --> | ||
<!-- ;Resources --> | <!-- ;Resources --> | ||
<!-- * Neff, G., Tanweer, A., Fiore-Gartland, B., & Osburn, L. (2017). Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies and Data Science. Big Data, 5(2), 85–97. https://doi.org/10.1089/big.2016.0050 --> | <!-- * Neff, G., Tanweer, A., Fiore-Gartland, B., & Osburn, L. (2017). Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies and Data Science. Big Data, 5(2), 85–97. https://doi.org/10.1089/big.2016.0050 --> | ||
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<!-- * Bivens, R. and Haimson, O.L. 2016. ''[http://journals.sagepub.com/doi/pdf/10.1177/2056305116672486 Baking Gender Into Social Media Design: How Platforms Shape Categories for Users and Advertisers]''. Social Media + Society. 2, 4 (2016), 205630511667248. DOI:https://doi.org/10.1177/2056305116672486. --> | <!-- * Bivens, R. and Haimson, O.L. 2016. ''[http://journals.sagepub.com/doi/pdf/10.1177/2056305116672486 Baking Gender Into Social Media Design: How Platforms Shape Categories for Users and Advertisers]''. Social Media + Society. 2, 4 (2016), 205630511667248. DOI:https://doi.org/10.1177/2056305116672486. --> | ||
<!-- * Schlesinger, A. et al. 2017. ''[http://arischlesinger.com/wp-content/uploads/2017/03/chi2017-schlesinger-intersectionality.pdf Intersectional HCI: Engaging Identity through Gender, Race, and Class].'' Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI ’17. (2017), 5412–5427. DOI:https://doi.org/10.1145/3025453.3025766. --> | <!-- * Schlesinger, A. et al. 2017. ''[http://arischlesinger.com/wp-content/uploads/2017/03/chi2017-schlesinger-intersectionality.pdf Intersectional HCI: Engaging Identity through Gender, Race, and Class].'' Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI ’17. (2017), 5412–5427. DOI:https://doi.org/10.1145/3025453.3025766. --> | ||
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=== Week 9 === | <hr/> | ||
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=== Week 9: November 22 (No Class Session)=== | |||
[[HCDS_(Fall_2018)/Day_8_plan|Day 9 plan]] | |||
;Data science for social good: ''Community-based and participatory approaches to data science; Using data science for society's benefit'' | ;Data science for social good: ''Community-based and participatory approaches to data science; Using data science for society's benefit'' | ||
;Assignments due | ;Assignments due | ||
* | * Reading reflection | ||
* A4: Final project plan | |||
;Agenda | |||
{{:HCDS (Fall 2018)/Day 9 plan}} | |||
;Readings assigned | ;Readings assigned | ||
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;Homework assigned | ;Homework assigned | ||
* Reading reflection | * Reading reflection | ||
;Resources | ;Resources | ||
* Daniela Aiello, Lisa Bates, et al. [https://shelterforce.org/2018/08/22/eviction-lab-misses-the-mark/ Eviction Lab Misses the Mark], ShelterForce, August 2018. | * Daniela Aiello, Lisa Bates, et al. [https://shelterforce.org/2018/08/22/eviction-lab-misses-the-mark/ Eviction Lab Misses the Mark], ShelterForce, August 2018. | ||
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=== Week 10 === | === Week 10: November 29 === | ||
[[HCDS_(Fall_2018)/Day_10_plan|Day 10 plan]] | |||
[[:File:HCDS 2018 week 10 slides.pdf|Day 10 slides]] | |||
;User experience and big data: ''Design considerations for machine learning applications; human centered data visualization; data storytelling'' | ;User experience and big data: ''Design considerations for machine learning applications; human centered data visualization; data storytelling'' | ||
;Assignments due | ;Assignments due | ||
* | * Reading reflection | ||
<!-- ;Agenda --> | <!-- ;Agenda --> | ||
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;Homework assigned | ;Homework assigned | ||
* | * A5: Final presentation | ||
<!-- ;Resources --> | <!-- ;Resources --> | ||
<!-- *Fabien Girardin. ''[https://medium.com/@girardin/experience-design-in-the-machine-learning-era-e16c87f4f2e2 Experience design in the machine learning era].'' Medium, 2016. --> | <!-- *Fabien Girardin. ''[https://medium.com/@girardin/experience-design-in-the-machine-learning-era-e16c87f4f2e2 Experience design in the machine learning era].'' Medium, 2016. --> | ||
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<!-- * Megan Risdal, ''[http://blog.kaggle.com/2016/06/13/communicating-data-science-an-interview-with-a-storytelling-expert-tyler-byers/ Communicating data science: an interview with a storytelling expert].'' Kaggle blog, 2016. --> | <!-- * Megan Risdal, ''[http://blog.kaggle.com/2016/06/13/communicating-data-science-an-interview-with-a-storytelling-expert-tyler-byers/ Communicating data science: an interview with a storytelling expert].'' Kaggle blog, 2016. --> | ||
<!-- * Brent Dykes, ''[https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/ Data Storytelling: The Essential Data Science Skill Everyone Needs].'' Forbes, 2016. --> | <!-- * Brent Dykes, ''[https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/ Data Storytelling: The Essential Data Science Skill Everyone Needs].'' Forbes, 2016. --> | ||
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=== Week 11 === | === Week 11: December 6 === | ||
[[HCDS_(Fall_2018)/Day_11_plan|Day 11 plan]] | |||
;Final presentations: course wrap up, presentation of student projects'' | ;Final presentations: course wrap up, presentation of student projects'' | ||
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;Assignments due | ;Assignments due | ||
* | * A5: Final presentation | ||
;Agenda | |||
{{:HCDS (Fall 2018)/Day 11 plan}} | |||
;Readings assigned | ;Readings assigned | ||
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;Homework assigned | ;Homework assigned | ||
* | * A6: Final project report (by 11:59pm) | ||
;Resources | |||
* ''one'' | |||
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=== Week 12: Finals Week (No Class Session) === | === Week 12: Finals Week (No Class Session) === | ||
* NO CLASS | * NO CLASS | ||
* | * A6: FINAL PROJECT REPORT DUE BY 11:59PM | ||
<!-- * LATE PROJECT SUBMISSIONS NOT ACCEPTED. --> | <!-- * LATE PROJECT SUBMISSIONS NOT ACCEPTED. --> | ||
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</div> | </div> | ||
[[Category:Groceryheist drafts]] | [[Category:Groceryheist drafts]] |