COMS 5225 Week 8 Mapping Indigenous Knowledge Critical

COMS 5225 Week 8: Mapping & Indigenous Knowledge Critical Data Studies 04 March, 2019 Class Schedule: Mondays, 11: 30 - 14: 30 Location: HZB 5437 Instructor: Dr. Tracey P. Lauriault E-mail: Tracey. Lauriault@Carleton. ca Office: 4110 b River Building Office Hours: Tuesdays 13: 00 -16: 00 ORCID: 0000 -0003 -1847 -2738 CU IR: https: //ir. library. carleton. ca/ppl/8 http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

Weeks 13– Assemblages, Weeks. Indicators – 36 Hours & Performance Measures Date Assignments Week 1 – What are data? Jan. 7 Week 2 Jan. 14 Week 3 – Facts Jan. 21 Week 4 – Field Trip Ottawa Police Services Jan. 28 3. 1 Field Trip Week 5 – Categories and Social Sorting Feb. 4 3. 2 Data Assemblage Brainstorm Week 6 – Administrative and Survey Data Feb. 11 3. 3 Paper & Poster Quad Chard Feb. 25 3. 4 DRAFT Paper Outline + Poster Abstract Mar. 1 3. 5 Submit Poster Abstract to CUIDS Week 8 – Mapping & Indigenous Knowledge Mar. 4 Assignment 4: In Library Assignment Week 9 – Big Data Mar. 11 3. 6 DRAFT Poster for Peer Review Week 10 – Probability & Risk Mar. 18 3. 7 Print Poster & Submit to CULearn (Mar. 20) Week 11 – Data Infrastructure Mar. 25 3. 8 DRAFT Research Paper for Peer Review Assignment 1: Description Study Break Feb. 18 -22 Week 7 – Standards Data Day 6. 0 Mar. 26 3. 9 Data Day 6. 0 Week 12 – From Critical Theory to Action Apr. 1 Week 13 – Assemblage, Genealogies & Dynamic Nominalism Apr. 8 http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225 3. 10 Submit Final Research Paper

Week 8: Agenda 1. 2. 3. 4. Data Day 6. 0 – Abstracts & Outlines Midterm Evaluation Reading Submissions In-Library Map Assignment http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

Data Day 6. 0 - Abstract § 3 Steps 1. Register for Data day 6. 0 2. Consent to publish 3. Abstract Submission § Abstracts must include: § Poster title § Full name of student(s) § Student(s) current program of study § Student(s) supervisor name http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225 § An outline of your research that should include and address the following § Introduction § Methodology § Results/Conclusion § Citations/References

Midterm Eval Response number: 1 The in-class discussions about work and ability to workshop ideas/ get feedback from both the professor and the other students (including the assumption that we are all at different stages and effort is the important part) The splitting up of readings so that each person does not have a lot to do every single week is also very helpful http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225 Not really sure at this point The course is tough but if you put the work in it's fair and the ability to resubmit work after discussion & feedback helps alleviate a lot of concerns Perhaps providing the initial feedback on the data description/ reading reflections a bit sooner, time permitting

Events http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

What your prof has been up to! https: //ico. org. uk/media/2259369/democrac y-disrupted-110718. pdf http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225 https: //www. statcan. gc. ca/eng/subjects/standard/naics/2017/index

Readers – Week 8 § Dylan - Sparke, Gundus § Liane - Peluso, Phillips § Jane - Harley, Scassa http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

Week 8 - Thematic Materials http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

4. Indigenous knowledge and communication infrastructure in-class mapping Assignment Week 8 Mar. 4 (10%) § In the Map, Data and Government Information Centre there is a map display entitled the Evolution of the Communication Infrastructure in Canada with some maps about Aboriginal People in Canada. The maps are organized into groups, you will be assigned a set of maps and will be provided with an inclass assignment. You will be required to consider the Harley paper and the Phillips keynote. § Look at authors, names, titles, table of contents, the placement of things, vocabulary, labels, data contributors, relative importance, etc. http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

Assignments http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

3. Research Paper & Poster Ottawa Police Service Data Assemblage 50% Students will demonstrate their familiarity with the course material by applying critical data studies concepts and theories related to this year’s theme which is Ottawa Police Services assemblage of data, indicators, maps, crime statistics and governance. In this assignment students are to research and map out the socio-technological data assemblage of the Ottawa Police in a poster project. The poster will be submitted at the Data Day 6. 0 Conference on March 26 organized by the Carleton Institute for Data Science. Students will also write a 15 -page research paper about this assemblage, and are asked to ontologically and epistemologically consider the Ottawa Police Services data processes? What currently frames the data collection approach? If that framing changes, what would change? Is there a data governance plan in place? What else could be collected and why? Are there any biases? Is this a data driven institution? Is the public adequately informed? 3. 1 Field Trip to the downtown Ottawa Police Communication Centre Week 4, Jan. 28 3. 2 Ottawa Police Data Assemblage Brain Storm, Week 5, Feb. 4 (5%) § Students can use Mindmap, Coggle. it, or power point or any other tool to draw out/illustrate anything related to the sociotechnological assemblage of the data and data system encountered during the field trip. Student will share their observations for 5 minutes each in class the following week. 3. 3 Poster Project Proposal, 1 -page Quad Chart, Week 6 Feb. 11 (5%) § Introduce what you will examine § Provide two potential research questions § State your methodological approach § References http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

3. Ctnd. 3. 4 DRAFT Outline of the paper and poster abstract for peer review Week 7, Feb. 25 § Follow the CUIDS instructions. 3. 5 Submit Final Poster Abstract to CUIDS date TBD (5%) 3. 6 Digital Draft of Poster for In-Class Peer Review Week 9 Mar. 11, in class (5%) § See CUIDS instructions. Note that a poster is a form of scholarly communication common in science and engineering. Keep in mind that your poster will be somewhat different, and you will adapt it to critical data studies and your topic. This is not an infographic. Here are some useful guidelines: § NYU Libraries Guide: http: //guides. nyu. edu/c. php? g=276826&p=1846154 § Urbana Champaign Library Guide: http: //guides. library. illinois. edu/c. php? g=347412&p=2343433 § 10 Simple Rules for a Good Poster Presentation: https: //www. ncbi. nlm. nih. gov/pmc/articles/PMC 1876493/ 3. 7 Print poster and submit digital copy to CULearn Week 10 Mar. 20 (15%) § If your poster is accepted for Data Day 6. 0 a print out of your poster will be required and generally there is a cost to this (+/-40$). Should your poster not be accepted a digital copy only is to be submitted. Whether or not your poster is accepted does not affect your mark. 3. 9 Submit a draft paper for peer review Week 11, March 25 3. 8 Attend Data Day 6. 0 Poster Session Week 11 on Tuesday Mar. 26 3. 10 Submit final paper to CULearn Week 13 April 8, 20%. A copy of the paper and poster will also be shared with Cameron Hopgood, Manager, Business Performance Unit at the Ottawa Police Service. http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

Data Day 6. 0 - Poster § Posters must adhere to the following requirements (failure to do so will result in your poster being ineligible for prizes). § Maximum dimensions = 4 ft. X 4 ft. (1. 22 m X 1. 22 m). Please note that your poster may be smaller than these dimension but should not be larger. § Font size must be legible from a short distance. Suggested font sizes are: 44 for titles, 38 -40 for body text, 18 -24 for captions under images, and 18 for references. § Your poster may be landscape or portrait. http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225 § The following information must be present: § Poster title § Full name of student(s), student(s)’ current program of study, student(s)’ supervisor name § Diagrams/tables/charts/algorithms/pictur es § Introduction § Methodology § Datasets & limitations § Results § Conclusion § References § Acknowledgements

Poster Evaluation Criteria http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

2. Weekly 1 -2 -page (max) Reading Reflections (30%) submit 6 / 11 Weeks by 10 AM day of class § Students are asked to submit weekly critical reflections of a combination of a set of readings, thematic readings and thematic encyclopaedia readings. § Students will conceptually integrate the material for that week and will identify concepts that may inform their paper and/or poster project. The reflection should end with a question for the class. http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

Reading Reflections § Data, indicators, facts & categories, Administrative Data & Survey Data § When reading consider: § The theme for that week – how do they relate § The assemblage – consider both the content and the context § Identify key actors and their influence § Integrate across the readings – what is common, different, conflicting ideas, etc. § How can these readings help with your research essay and poster § Think about what these things do in the world § Bring a question to the class http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225

Dylan (13, 1200) Liane (04/26/2011, Indian Status #) Week 3 Week 4 Week 5 Week 6 Hanna (12, . . . 2, statcan data viz) Olivia (44, Serial #s & IP Add. ) Jane (11. 22. 33, . . . , Migrant data, SOP, TFW) 1. Kitchin, Manovich, Gartner, Chart Week 1 Week 2 Maddy (666, crtc Act #s, PRI) 1. Liane - Immervol, 1. Dylan - Hammer, Mc. Call, Deflem, C. Ottawa CACP, 2017 2. Dylan -Igo, Campbell, Stat. Can 2014 Field 3. Dylan - Hacking 1986, Bazelon, Holmes 2. Liane - Curtis, Stat. Can Linkages Week 7 Week 8 4. Dylan - Sparke, Gundus 3. Liane - Edwards, Mork 4. Liane - Peluso, Phillips All 1. Hanna - Sparrow, 2. Maddy - Kitchin, Deflem, PSC Mc. Call, PSC 2015 Research Summary 3. Maddy - Gruber, Rosemberg, 2. Hanna - Gruber, 1. Olivia - Bauchspies, NAS, Campbell, PSEP 2015 Campbell, Toronto Lawton? Zhucherman? Field 4. Maddy - Zuberi, Reitman, 1. Jane - Bowker, Williams, Holmes 2. Jane - Foucault, Kredrowski 5. Maddy - Marks, Dencik 3. Hanna - Lampland, Bright, CCCS 6. Maddy - Sismondon, 2. Olivia - Millerand, Mrkic, 3. Jane - Igo, IDNYC, Gabrielson Stat. Can UN Crime Mac. Naughton, OPS 2017 4. Jane - Harley, Scassa Week 10 5. Liane - Mantello, Schlehahn, Bales Week 11 6. Liane - Dourish, Pallito, OPS 2013 4. Hanna - Pasquale, Saskia, Cracked Labs 5. Hanna - Guzik, Lapowski, Backman 6. Hanna - Edwards, Galdon, CBC, OPS 2017 All - Kitchin Assemblage, Hacking Dynamic Nominalism & Foucault Genealogies - we will encouter All - Kitchin Assemblage, Hacking All - Kitchin Assemblage, Dynamic Nominalism All - Kitchin Assemblage, Hacking Dynamic & Foucault Hacking Dynamic Nominalism & Foucault Genealogies - we will encouter 5. Dylan - Verhoef, Funk, Week 9 Hexagon Week 12 6. Dylan - Nash All - Kitchin Assemblage, Hacking Dynamic Nominalism & Foucault Genealogies - we will Week 13 encouter Tracey (42, Credit Score) 3. Olivia - Anderson, Kitchin, Ferguson, CACP 4. Olivia - Hacking 1990, 5. Jane - Crawford, Mears, Backman Arandau, Bales 5. Olivia - Hughes, CITIG, OPSB 2016, OPS 2017 IM/IT 6. Olivia - 60 Min, Lauriault, 6. Jane - Atkinson, LAPD, Milan Elliot http: //doi. org/10. 22215/tplauriault. courses. 2019. coms 5225 Stat. Can 2018, Eurostat, Lambert, UNAids Jerven, CRAP, Rough Guide Field Lyon, Foster, OHRS Star, Desrosiere, Justice Data Lab OPS 2016, UN, Open. Corp. , IATI Kitchin Calof, Coleman, Sanders, Kitchin, UN Big Data Donoho, Mears, Bales, RAND ASDI, OPS 2016 Innovation, PWC, OPS 2017 Budget Goldstein, Ratto, Weigend All - Kitchin Assemblage, Hacking Dynamic Nominalism & Foucault Genealogies - we will encouter