COMS5225 Critical Data Studies

http://doi.org/10.22215/tplauriault.courses.2019.coms5225
COMS5225
Assemblages, Genealogies and
Dynamic Nominalism
Week 13: Critical Data Studies
08, April 2019
Class Schedule: Mondays, 11:30 - 14:30
Location: HZB5437
Instructor: Dr. Tracey P. Lauriault
E-mail: Tracey.Lauriault@Carleton.ca
Office: 4110b River Building
Office Hours: Tuesdays 13:00-16:00
ORCID:0000-0003-1847-2738
CU IR: https://ir.library.carleton.ca/ppl/8

13 Weeks – 36 Hours
Weeks Date Assignments
Week 1 – What are data? Jan. 7
Week 2 – Assemblages, Indicators & Performance Measures Jan. 14 Assignment 1: Description
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
Study Break Feb. 18-22
Week 7 – Standards 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 & Big Data, Mapping, Poster Mar. 18 3.7 Print Poster & Submit to CULearn (Mar. 22
or even Sunday Mar. 24 night!)
Week 11 – Data Infrastructure, Probability & Risk Mar. 25 3.8 DRAFT Research Paper for Peer Review
Data Day 6.0 Mar. 26 3.9 Data Day 6.0
Week 12 – From Critical Theory to Action Apr. 1 3 Films
Week 13 – Assemblage, Genealogies & Dynamic Nominalism Apr.15 3.10 Submit Final Research Paper

Week 1 – What are data?
Ch. 1
Conceptualizing Data
Ch. 7
Data
Ch. 1
Numbers,
Power &
Organization
Ch. 21 Ch. 1
Statistics as
Social Science

Week 1 – Thematic Readings
▪ Gartner, Rosemary (2015) Crime: Knowledge about and
Prevalence. In International Encyclopaedia of the Social &
Behavioral Sciences, 164–69. Elsevier, 2015.
https://doi.org/10.1016/B978-0-08-097086-8.45004-X
▪ Hughes, Lorine A., and James F. Short. (2015) Crime,
Sociology Of.” In International Encyclopaedia of the Social
& Behavioral Sciences, 189–93. Elsevier,
https://doi.org/10.1016/B978-0-08-097086-8.45016-6.

1. Data Description and Conceptualization- Due Week
2, Jan. 14, 10:00AM (10%):
Select a dataset in the wild related this year’s theme.
In a total of 3 pages describe these data technically and in such a way that 10 years from now you will
be able to decipher the nature of these data.
▪ Technical descriptions of data generally include the following, but do not be limited to this: consider
format, sample size, headings, metadata, licences and terms of use, how are they disseminated, who
is the publisher, the producing institution, data authors if there are any, methodology, dates,
geography, classifications, models, methods, etc.
▪ Be sure to cite the dataset & provide the URL, be sure to cite any related documentation, you can
use footnotes, images and tables if useful, but do use full citation, captions and document styles. Get
to know these data.
▪ You will also conceptually frame these data according to Kitchin's 4 remaining conceptualizations
and identify any elements of the socio-technological assemblage. This can be done in a table.
▪ State why you are interested in this dataset, what you might use the data for, how the data are
conventionally used and explain what led you to trust them.
▪ NOTE: Images, tables and references will not go against your page count. Think of this as a critically
informed lab report.

Assignment 1 - Data Description
1. Police Reported hate crime, be census metropolitan area, Canada
https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3510019101
2. Ottawa Police Service (OPS) Incident
http://moto.data.socrata.com/dataset/Ottawa-Police/uacw-px76
3. Community Well-Being Index (for 1991) http://www.aadnc-
aandc.gc.ca/DAM/DAM-INTER-HQ-AI/STAGING/texte-
text/cwb_2006_1452011133706_eng.csv
4. Reveal’s RS3-SX Body Camera https://www.revealmedia.com/police-body-worn-
cameras
5. Uniform Crime Reporting Incident-Based Survey (UCR): Violations and Relation to
Victim, Grouped by Age and Sex
https://dataverse.scholarsportal.info/dataset.xhtml?persistentId=hdl:10864/11603
6. Police officers by rank and gender, municipal police services
https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3510019101

Week 1 – Reading Reflection Questions
▪How are data usually explained in popular discourses?
▪How does this week 1 exploration and description of data vary from the
ones you may have heard before?
▪Why do you think that data are often misunderstood when explored in
popular discourses?

Week 2 - Assemblages, Indicators & Performance
Measures
Hammer, Ch. 4 Immervol, Ch. 9

Week 2 - Thematic Readings
▪ Gartner, Rosemary (2015) Crime: Knowledge about and
Prevalence. In International Encyclopaedia of the Social &
Behavioral Sciences, 164–69. Elsevier, 2015.
https://doi.org/10.1016/B978-0-08-097086-8.45004-X
▪ Hughes, Lorine A., and James F. Short. (2015) Crime, Sociology
Of.” In International Encyclopaedia of the Social & Behavioral
Sciences, 189–93. Elsevier, https://doi.org/10.1016/B978-0-08-
097086-8.45016-6.
▪ Deflem, Mathieu, and Samantha Hauptman. (2015) Policing. In
International Encyclopaedia of the Social & Behavioral Sciences,
260–65. Elsevier, https://doi.org/10.1016/B978-0-08-097086-
8.45007-5.
▪ McCall, Patricia L., and Joshua A. Hendrix. (2015) Crime Trends
and Debates. In International Encyclopaedia of the Social &
Behavioral Sciences, 194–202. Elsevier,
https://doi.org/10.1016/B978-0-08-097086-8.45050-6.

Week 2 - Thematic Materials
▪ Ottawa Police Service (2017) Annual Report,
https://www.ottawapolice.ca/en/annual-report-2017/resources/2017/OPS-2017-
Annual-Report-Online.pdf
▪ City of Ottawa (2017) Budget, https://ottawa.ca/en/news/budget-2017#adopted-
budget-2017-alternative-accessible-format
▪ Canadian Association of Chiefs of Police, Police Information and Statistics (POLIS)
Committee, https://www.cacp.ca/police-information-and-statistics-polis-
committee.html
▪ Public Safety of Canada (2015) Measuring the Performance of the Police: The
Perspective of the Public, Research Report: 2015-R034 by Anton Maslov
https://www.publicsafety.gc.ca/cnt/rsrcs/pblctns/2015-r034/2015-r034-en.pdf
▪ Public Safety Canada, Research Summary: Police Performance and Surveys,
https://www.publicsafety.gc.ca/cnt/rsrcs/pblctns/2015-s034/index-en.aspx
▪ Statistics Canada, (2018) Police Resources in Canada,
https://www150.statcan.gc.ca/n1/pub/85-002-x/2018001/article/54912-eng.htm

Week 2 - Indicator References
Ch. 3 & 4 Introduction

▪What would be the best way to track citizen satisfaction with the police?
▪Is there a particular form of data collection which would be more
accurate to represent citizen sentiment?

Week 3 - Facts
Ch. 2 pp. 15-41 & 89-103 Ch. 6 Ch. 3 Executive Summary

▪Ottawa Police Service (2017) Annual Report,
https://www.ottawapolice.ca/en/annual-report-2017/resources/2017/OPS-
2017-Annual-Report-Online.pdf
▪Public Safety and Emergency Preparedness Canada (2004) Public Confidence
in the Criminal Justice System, Research Summary,
https://www.publicsafety.gc.ca/cnt/rsrcs/pblctns/pblc-cnfdnc/pblc-cnfdnc-
eng.pdf
▪Statistics Canada (2014) General Social Survey of Victimization,
https://www150.statcan.gc.ca/n1/pub/85-002-x/2015001/article/14241-
eng.htm
▪Toronto Police Service Public Safety Data Portal
http://data.torontopolice.on.ca/pages/major-crime-indicators

Week 3 - Critical Thinking Material

CRAP Test
Currency
▪ Site or page date
▪ Is the date of publication or last revision published (often at the bottom of the
page)?
▪ When was the site or page last updated?
Reliability
▪ Evidence of the peer review process (e.g., in an "About us" or editorial
statement)
▪ A bibliography or reference list
Authority
▪ Author's credentials
▪ Look for information about the author of the site or page.
▪ Is the author qualified to publish on this topic?
▪ E.g, Can you identify the author's education and relevant professional experience?
▪ Look up the author's name in the Carleton University Library catalogue or Wikipedia.
▪ URL
▪ Read the uniform resource locator (URL) carefully to determine if you are reading
someone's personal page.
▪ You need to investigate the author carefully because personal pages have no
publisher or domain owner to vouch for the information.
▪ Domain
▪ Is the domain extension appropriate for the content?
▪ Government sites: .gov
▪ Educational sites: edu
▪ Nonprofit organizations: .org
Publisher
▪ Identify the publisher (individual or organization) of the site or
page.
▪ The publisher operates the server computer from which the site or
page is issued. Do you know anything about the publisher?
"About us" links
▪ Read the information on the site or page about the author and/or
publisher.
▪ This could be under "about us," "philosophy," "background," or
"bibliography" tabs.
Page design or structure
▪ Page design is not always an indicator of credibility but if a site or
page is easy to navigate, you'll be able to assess the information
more easily.
Purpose/Point of view
▪ "About us" links
▪ Read the information on the site or page about the author and/or
publisher.
▪ This could be under "about us" or "philosophy", "background" or
"bibliography" tabs.
▪ Is there advertising?
Cross reference information
▪ Try to verify the information by cross referencing the material.
▪ Look up some of the references in Google Scholar (through the
Carleton University Library).

We’re hardwired to believe….
▪Psychologists, criminologists, cognitive scientists suggest that we are
hardwired to think in certain ways
▪And Lawton, hints that to be critical thinkers we need to work around this
wiring
1. Zero sum – win-win
2. Folk knowledge
3. Stereotyping
4. Sycophancy
5. Conservatisms
6. Tribalism
7. Religion
8. Revenge
9. Fonfabulations

▪To what degree should police research/findings be reproducible due to their
hyper specific context? Can a social phenomena be replicated?
▪How are ‘facts’ or definitions conceptualized at a police department, and how
are they (if they are) standardized?
▪Would it be beneficial for police forces to have a standardized research
methods and definitions, and to what scale (provincial, country, globally, etc.)?
▪How can we change “who counts” in police force data, where marginalized
people seem over-represented?
▪Who gets to count the police?
▪Legitimacy?
▪If the way in which we interact with the world is based on our personal
perceptions, is there such a thing as objectivity?

Week 4 - OPS Field Trip

Post
OPS
Visit
Brainstorm

Colour coding legend:
- Darker blue – main
topic
- Lighter blue – main
components of
assemblage
- Purple – bigger ideas or
concepts to unpack
- Pink – interesting
things to
note/particularly stood
out to me
- Black – smaller
aspects/questions to ask
Post
OPS
Visit
Brainstorm

Post
OPS Visit
Brainstorm

Post OPS
Visit Brainstorm

Week 5 - Categories and Social Sorting
Ch. 9 Making Up People Ch. 1 & 7

Ch. 4 Ch. 8

▪From our trip to OPS, did we see any instances of boundary work across
OPS departments (e.g. police & coms center) or between the OPS and
other services (e.g. Stats Can)? How did this affect their operations/data
collection/database reliability?
▪How would you define racial categories?
▪Is there a difference between self-categorization and categorization
imposed by a legal governing body?
▪And who gets to decide what categories are legitimate?

Week 6 - Administrative and Survey Data
Ch. 1 & 2 Ch. 2,
Desrosiere
pp.201-222 Ch. 4 Ch. 14

Week 6 – Thematic Readings

Proposal

▪ Considering Curtis’ (2002) analysis of making census population and critically thinking about the
ethics behind Microdata linkages and the issue surrounding privacy, do you think that public good
outweighs privacy intrusion?
▪ What might differ between government and policing institutions in the way they think about and use
data, security concepts, economic knowledge? And is this the same everywhere?
▪ Who are and what can we say the government (and policing) is, in a time when it encompasses so
much, across so many institutions, geographies, platforms, and actors?
▪ Further, how is accountability to be handled when acts of government (and policing) are so far
removed from actors?
▪ How do police conceptualize themselves according to Foucault’s models (justice, administrative, or
government), if at all? How might these be reflected in their performance measurements? The
“balanced model” for example, “properly consider[s] cost versus results and quality trade-offs”
(Kiedrowski et. al, 2013, p. 16). Is this a turn away from singular conceptualizations of responsibility?
Towards a “whole complex of knowledges” (Foucault, 1994, p. 220)?
▪ Would an uniformed set of standards and guidelines help governments to use data better? Or
should different sets of data each be contextualized in their own space for their specific purpose?
What questions need to be asked about data before we can use them in a manner that takes into
account the fact that they are not neutral?

Week 7 - Standards
Ch. 3 Ch. 2 pp. 3-35 & 149-177 Ch. 12

▪ Canadian Centre for Crime Statistics, Revising the
classification of founded and unfounded criminal
incidents in the Uniform Crime Reporting Survey
https://www150.statcan.gc.ca/n1/pub/85-002-
x/2018001/article/54973-eng.htm
▪ Ottawa Police Service (2016) Regulated Interactions,
https://www.ottawapolice.ca/en/news-and-
community/RegulatedInteractions.aspx
▪ Ottawa Police Service (2017) Annual Report:
COLLECTION OF IDENTIFYING INFORMATION –
DUTIES & PROHIBITIONS POLICY: ANNUAL REPORT
https://www.ottawapolice.ca/en/about-
us/resources/Regulated_Interactions_2017Annual_Rep
ort_Final.pdf
▪ United Nations Office on Drugs and Crime, Standards
and Manuals, https://www.unodc.org/unodc/en/data-
and-analysis/standards-and-manuals.html
▪ Open Corporates
https://opencorporates.com/info/about
▪ IATI http://www.aidtransparency.net/

Week 7 - What is a standard?

Draft Abstract

DRAFT Abstract

▪ Who gets to decide what standards should exist? How might standards actually work against their goal of objectivity depending on who decides what they are
going to be and how are they operationalized?
▪ Creation of an increasingly “known” citizen and subsequent shared (standard) identity.
▪ IDs as forms of knowledge in itself (generating new categories of data, becoming a uniform way to “know” people).
▪ The way ID mechanisms become tied to economic/social possibilities or consequences.
▪ Navigation of subjectivities (gov. levels, demographic groups, etc.) towards standard ID form
▪ Similar systems of thought; Foucault’s governmentality & “population as datum,” and Hobbesian logic.
▪ Can we see similarities between the SSN and IDNYC? How can we interpret the statement “IDNYC…gives all of us the opportunity to show who we are—New
Yorkers” (NYC, 2019)?
▪ How is “New Yorker” an identity? What is the standard “New Yorker”?
▪ Who determines what should be standardized and the process? These readings allowed me to really start thinking critically about how standards are truly
embedded in society, buy why? and how are they embedded? Who and how are they governed and enforced?
▪ Question for the class: How are biometric data collected by the Canadian government stored?
▪ Should citizens have a right to “opt-in” or “opt-out” when providing their biometric data?
▪ How does the OPS collect / use these data?
▪ Where do collected data get sent and who transforms them into a biometric fact?
▪ Using Mork Lomell’s (2011) understanding of police annual reports as performative and persuasive which present an idealized image of the institution, in what
ways can we descriptively map the Ottawa Police Service’s annual report?
▪ Do standards have power? What do they afford?

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 in-class 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.

MacOdrum Library Atlas of Canada & Canada
Year Book Display

▪ Using Phillips’ notion and understanding of the problem of standards, how can we
understand “dipstick” data and the problem of big data and how sporadic research
we’ve examined in our class readings? Why does Phillip’s stress the notion for
understanding the context of data?
▪ do cartographers have similar third-party financing/market/licensing considerations?
▪ Who makes use of maps, who owns them, and is this different than who creates
them?
▪ How might this raise similar concerns as in Scassa? In Scassa, crime mapping is
envisioned as a tool of “civil engagement” – do maps have these same goals? How
might this differ with a “scientific” map vs. a national map?
▪ Is engagement similar or different in crime vs. maps? We can also consider paper vs.
digital mapping – does digital mapping allow more engagement?
▪ If street-level officers are resistant to knowledge and procedural changes that conflict
with ingrained training principles and front line practice, how could police services
work to effectively introduce new technological and data-oriented practices into
operations

Week 9 – Big Data

Week 9 – Thematic Material

DRAFT

▪Does understanding the internal problems of police using big data (i.e. costs,
which would be increased exponentially by the implementation of wearable
technology) abate some of our concerns over privacy and surveillance?
▪A lot of work has been done to identify the current issues with corporate
surveillance in the online world, but what can be done to protect consumers?
▪Should there be a governing body that oversees the actions of these data
brokers, to ensure that the consumers best interests are protected?
▪Do consumers have the right to request the “dossier” of information that major
platforms such as Facebook and Google have collected on them?
▪Who is the true owner of these data?
▪After our visit to the OPS, are they ready to shift towards a big data
environment?
▪What is the discursive regime of the OPS?

Week 10 – Probability & Risk

Local and Traditional Knowledge

Licencing LTK

▪ Would the use of predictive analytics make the OPS’ operations more evidence-based
as Mears suggests?
▪ Are there any other examples (OPS or otherwise) of classification systems reflecting
social, political, religious, and/or cultural beliefs (Crawford, 2017) of the group
constructing it?
▪ The US Department for Justice states that federal law enforcement may consider race
in the effort of protecting national security (US Department of Justice, 2003, cited
from, Guzik, 2009). With this in mind, how can we overcome racial biases in society
when they are embedded in society from legislation to design in algorithms?
▪ How can we ensure that the design of the algorithms do not have racial biases from
the get go?
▪ Considering Schlehahan et al and Mentello’s considerations surrounding pre-emptive
policing and the issues with surveillance, do you think Ottawa Police Services should
engage with predictive policing?
▪ Are there any particular considerations that should be raised because of Ottawa is
Canada’s nation-state capital?

Week 11 - Infrastructure

Final Abstract & Poster

Data Day 6.0

Data Day 6.0 Program

▪What kind of infrastructural improvements would be most beneficial to the
OPS?
▪Can smart city technology be used to inform the OPS in terms of predictive
policing (a theme from last weeks readings)?
▪What kind of big data analysis can be done with data collected through smart
city technologies such as IoT and could those be used for surveillance
purposes? Who owns these data? How can they be governed?
▪Pallito offers a notion toward a normative framework for analyzing bargains
involving privacy in which the “first-order duty is to the self” in which we ought
to value our own privacy. Do you agree with the concluding chapter or are
there real concrete actions that are missing? What would you add?

Week 12 - From Critical Theory to Action

Week 12 – Thematic Materials

▪Using GDP as a measurement of national wellbeing is required to be a member
of the United Nations, which (while itself is a problematic organization) brings
with it access to assistance from the World Bank and International Monetary
Fund. However, GDP is not an accurate measure of how people are doing. How
can we even start to go about reorganizing worldviews so that GDP is pushed
to the side like a relic, allowing us to make more nuanced assessments about
ourselves and our neighbours (both locally and across the globe)?
▪How has the critical theory learned in this class changed (or perhaps has not)
your perspective on data and the OPS?
▪Does the phrase “technology can be used for bad or for good” (from Do Not
Resist) imply that technology is initially constructed neutral (and then used
well/poorly)?
▪What would be a better way to think about the possibilities and consequences
of technology?
▪Can/should we even use terms like “good” and “bad”?

Week 13 - Assemblages, Genealogies and
Dynamic Nominalism
“data are commonly understood to be the raw material produced by
abstracting the world into categories, measures and other
representational forms – numbers, characters, symbols, images, sounds,
electromagnetic waves, bits – that constitute the building blocks from
which information and knowledge are created” (Kitchin, 2014:1)
“data do not exist independently of the ideas, instruments, practices,
contexts and knowledges used to generate, process and analyze them”
(Kitchin, 2014:2)

Material Platform
(infrastructure – hardware)
Code Platform
(operating system)
Code/algorithms
(software)
Data(base)
Interface
Reception/Operation
(user/usage)
Systems of thought
Forms of knowledge
Finance
Political economies
Governmentalities - legalities
Organisations and institutions
Subjectivities and communities
Marketplace
System/process
performs a task
Context
frames the system/task
Digital socio-technical assemblage
HCI, Remediation studies
Critical code studies
Software studies
New media studies
Game studies
Critical Social Science
Science Technology Studies
Platform studies
Places
Practices
Flowline/Lifecycle
Surveillance Studies
Critical data studies
Algorithm Studies
Socio-Technological Assemblage
Modified by Lauriault from Kitchin, 2014, The Data Revolution, Sage.

Dynamic NominalismModified from Ian Hacking’s Dynamic Nominalism
Tracey P. Lauriault, 2012,

Social-shaping qualities of data
Kitchin, 2012, Programmable City

Critical Data Studies
Research and thinking that applies critical social theory to data to
explore the ways in which they are never
▪ simply neutral,
▪ objective,
▪ independent,
▪ raw representations of the world,
Data are instead understood to be:
▪ situated,
▪ contingent,
▪ relational,
▪ contextual, and
▪ do active work in the world.
Kitchin and Lauriault, 2015

Critical Data Studies Vision
▪Unpack the complex assemblages that produce, circulate, share/sell and
utilise data in diverse ways;
▪Chart the diverse work they do and their consequences for how the
world is known, governed and lived-in;
▪Survey the wider landscape of data assemblages and how they interact
to form intersecting data products, services and markets and shape
policy and regulation.
Kitchin and Lauriault, 2015

7 provocations
1. Situate data regimes in time and space
2. Expose data as inherently political and whose interests they serve
3. Unpack the complex, non-deterministic relationship between data and society
4. Illustrate the ways in which data are never raw
5. Expose the fallacies that data can speak for themselves and that big data will
replace small data
6. Explore how new data regimes can be used in socially progressive ways
7. Examine how academia engages with new data regimes and the opportunities of
such engagement.
Craig Dalton and Jim Thatcher, 2014
Image Source: Economic Times, Indicators page, 2013
http://articles.economictimes.indiatimes.com/2013-03-13/news/37683866_1_trade-data-
interstate-trade-inter-state-trade

Data
Indicators
Facts
Classification
Institutions
Standards
Maps
Big Data
Prediction
Infrastructure
Producing Knowledge
Action

Critically Engaged Pedagogy
Topic Theory
Domain Theory
Domain
Praxis
OPS Site Visit & Interview
Grey Literature
& Data
Crime, Safety,
Policing, etc.
Critical Data
Studies

Assignments

2. Weekly 1-2-page (max) Reading Reflections (30%)
submit 6 / 11 Weeks by 10AM 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.

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 socio-
technological 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

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/PMC1876493/
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.

COMS5225 Critical Data Studies

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