Not offered for the upcoming academic year

Not offered for the upcoming academic year

Data Governance is about formally managing critical data throughout the organization and making sure organizations derive value from it. Data Governance is a critical component for organizations leveraging data science and analytics to provide data-driven insights to their clients and consumers. Successful Data Governance is achieved by addressing the 4 v’s to ensure that the volume, variety, velocity, and veracity of data brings the most value. It is generally achieved by a combination of people, process and technology. An effective Data Governance function of an organization begins with focusing on the information most valuable to the organization and the structure that must be put in place to safeguard its integrity, security, quality, integration, meta-data, architecture and lifecycle while building the right infrastructure to support it.

Not offered for the upcoming academic year

Not offered for the upcoming academic year

Not offered for the upcoming academic year

Not offered for the upcoming academic year

Not offered for the upcoming academic year

Not offered for the upcoming academic year

Not offered for the upcoming academic year

INF2500H-INF2510H: Rotating electives on the themes of Knowledge Management and Information Management.

Current offerings can be viewed on the Faculty website.

INF2580H to 2589H: A special topics course allows for the introduction of new curriculum focusing on emerging topics that cut across concentrations or address the Master of Information curriculum as a whole.

The purpose of this course is to introduce students to the wide range of research within the field of Information being carried out within the Faculty. The course is organized around a series of talks that include faculty members speaking about common research interests, often from different disciplinary perspectives. These talks provide students with an overview of the diversity of scholarship in the faculty, including the multiple disciplines and subfields in which we operate. Students’ individual understandings and interests are at the center of the course pedagogy. As such, the course will be heavily discussion and event-based. The main objective of this course is to assist students in understanding the overall shape of the field of Information and to begin to discover their own personal place within it.

A systematic introduction to and analysis of the conceptual frameworks and methods (analytic, empirical, evaluative, etc.) employed in information research. Approaches to be considered to be selected from among: (i) discursive (cultural studies, literary theory, continental philosophy; (ii) science and engineering (computer science, HCI); (iii) conceptual (philosophy, mathematical); (iv) qualitative (social science), and (v) quantitative (social science).

Independent reading by student supplemented by regularly scheduled one-on-one meetings with advisor, the details of which will be spelled out in a contract jointly prepared by the student and advisor.

Historical and theoretical perspectives on technological change and its social implications provide a foundation for intensive study and critical analysis of new communication technologies. A grasp of the social, political and economic contexts in which technologies emerge allows the student to discern the way culture both shapes and is shaped by information and communication technologies. Course topics are thus chosen to broadly acquaint students with key historical moments in the history of technology and in the historical situatededness of academic knowledge production regarding media and technology. They provide a framework in which early theorizations of media and technology are studied to enrich current understanding of media. The course also provides grounding in a range of theorizations to give the student a broad overview of the multiplicity of approaches and methods that can aid investigations of technological change in social contexts. This graduate seminar explores the history of “new” media as agents of change in cultural, social, and spatial infrastructures, economies, and cultural politics.

This course investigates how power manifests unevenly across different media, technologies and in different cultural contexts. We will examine structural forces shaping the use and contestation of technologies and media, and critically investigate how technologies and media are used to constitute and organize social and power relations, both historically and in the contemporary context. Through considerations of race, class, gender, and sexuality, the course addresses how media and technology are implicated in social inequality, oppression and exploitation, and how these relations are contested and opposed. The aim of the course is to deepen our critical engagement with the processes, practices, and social relations of media and technology in contemporary political, economic, and social life.

The concept of evidence is central to both epistemology and the philosophy of science. Yet "evidence" is hardly a philosopher's term of art: it is not only, or even primarily, philosophers who routinely speak of evidence, but also lawyers and judges, historians and scientists, archivists and curators, investigative journalists and reporters, as well as the members of numerous other professions and ordinary people in everyday life. The concept of evidence is perhaps pre-theoretical compared to other concepts which enjoy similarly central standing within Information Studies. This course will introduce students to the nature of justified belief, argumentation, reasoning, innate knowledge, theory of measurements, persuasion and rhetoric, and related concepts.

This course will allow students to deeply explore a methodological approach that they could use in their media focused dissertations. For the purposes of this course, “media” will be defined broadly as encompassing all types of communication media, including social media, radio and television media, mobile media, etc. The methodological approach that students choose to focus on in this course should fall within the domain of “social science,” which includes quantitative methods such as surveys, experiments, and digital trace collection, and qualitative methods such as interviews and participant observation. Hybrid approaches that draw on more than one of these methods will also be encouraged when they fit within the students’ dissertation objectives. This course will also engage students to consider ethical issues relating to their dissertation projects. Given the seminar format of this course, students will be exposed to methodological approaches chosen by other students in the class, thereby broadening their methodological foundations. Further, at the beginning of the course, students broaden and firm-up their methodological foundations by reviewing methodological approaches that are commonly used in the social sciences. It should be noted that given the limited duration of this course, we will not focus deeply on data analytics. Nevertheless, students will need to consider the types of analyses that are appropriate once they have collected data for their dissertations, and they will be encouraged to follow up on these analytic approaches through other means.

This course is a survey of cultural and interpretive methods as they are applied to the study of media and technology across fields such as media studies, science and technology studies, cultural studies, game studies, and internet studies. Students will learn about genealogical, analytical and interpretative approaches to media content and technologies as well as cultural and critical ethnographic approaches to the understanding of media audiences, online communities, and creative labour participants. The emergent ethical and political dimensions of cultural and interpretive research will be stressed. This course presents the opportunity for students to learn and apply foundational theories in the field of Media, Technology and Culture through coursework deliverables such as research papers, proposal reviews, and research design documents. This fulfills objectives such as PLO 2: Research and Scholarship – b. The ability to make informed judgments on complex and emerging issues in information studies, which may require the creation of innovative methodologies, as well as c. The ability to produce original research, or other advanced scholarship, of a quality to satisfy peer review, and to merit publication in diverse scholarly and practitioner venues.

A reading course in a special field to be carried out under the supervision of a member of the faculty (With the permission).

This course is designed to help students develop knowledge of empirically grounded theories of teaching and learning, to use those theories to reflect on their own learning and to guide pedagogical design, to practice the work of teaching and soliciting student feedback, and to develop scholarly inquiries into their teaching.

An intensive workshop for post-candidacy doctoral students to assist in the development of the conceptual structure of their dissertations. Writing a doctoral dissertation is a larger intellectual project than most doctoral students have undertaken at any prior point in their studies. Doing a good job requires developing a conceptually coherent and compelling argument that makes the case for the claim(s) being advanced and defended. Developing such arguments is a hard-won skill, which must be practiced, honed, and refined over many iterations. A number of factors can impede the process of formulating a conceptually sound argument, especially in the context of a dissertation: (i) the magnitude of the writing task can get in the way of focus on the argument itself; (ii) writers can become mired in the details of a set of findings, and find it difficult to grasp the logical structure of what is to be claimed; (iii) the best structure for the ultimate argument is often far from clear early in the process. Arguments often need be adjusted during the dissertation process—often completely restructured (an analogy, in prose, to refactoring a computer program); (iv) once draft prose is created, it has a tendency to draw the writer ineluctably into an endless process of incremental adjustments and edits, at the expense of addressing more urgent and fundamental structural problems in the underlying conceptual framework. The aim of this seminar is to assist doctoral students in framing, articulating, developing, and revising the conceptual structure of the arguments on which their dissertations will be based. Techniques to be developed include the developments of skeletons—short, distilled, logical précis of arguments, stripped of all prose, rhetoric, introductions, etc., designed to reveal the conceptual structure of an argument in a bare-bones manner. Developing a good skeleton is extraordinarily difficult, but more than repays the effort in simplifying and making more effective the subsequent writing process.

This course surveys theories of HCI design, models of user interfaces, interface design, and empirical approaches for analyzing systems and interfaces. Through individual and/or group research projects, this course emphasizes applied user experience (UX) design grounded in a multi-disciplinary analysis of the interplay between human factors, human perception, and societal and cultural dimensions. Students will evaluate designs of emerging, novel interactions through an emphasis on UX lifecycle, usability, utility, and acceptance. PhD students have priority. MI and MMSt students can enroll by permission of the instructor. Students would email the instructor with the following information: 1) list research methods courses taken and 2) list experience and/or courses taken in the field of UX design or Human Computer interaction) – space is limited

Quantitative approaches have a common concern: How can others be confident that our statistical approaches have been brought to bear on appropriate datasets? This course focuses on the 'data' of data science. It develops in students an appreciation for the many ways in which dealing with a dataset can get out-of-hand, and establishes approaches to ensure data science is conducted in ways that engenders trusted findings.

It focuses not only on statistical modelling, but also on everything that comes before modelling, and by focusing on those steps, places modelling and analysis on a more firm foundation. In assessment, students will conduct end-to-end data science projects using real-world data, enabling them to fulling understand potential pitfalls. The focus of the learning will be on:

1. actively reading and consider relevant literature;
2. actively using the statistical programming language R in real-world conditions;
3. gathering, cleaning, and preparing datasets; and
4. choosing and implementing statistical models and evaluating their estimates.

Humanity is now violating six of the nine planetary boundaries that represent a safe ecological space for human life, including climate change, without meeting its declared social goals of equity, justice, health, and human flourishing. Technology is often positioned as a magic solution to resolve the dilemma of 'sustainable development,' but it is implicated in so much destruction and suffering that it is clear: its role is conflicted.

This course begins with the difficult task of recognizing these challenges with neither flawed optimism nor fatalist pessimism. It locates students at the present juncture of interconnected crises with the task of figuring out what we should do next. Tech Otherwise means to make tech "differently, in the service of our collective and sustainable well being." Tech Otherwise (pubpub.org)

The course draws on frameworks such as degrowth, the pluriverse, and decolonization to invite students to explore how information technologies can be shaped otherwise in ways that genuinely support human and ecological flourishing, to imagine new pathways, and to decide how their own research plans may contribute to these goals. Topics include the social responsibility of tech workers; decolonization, limits to growth, degrowth, and post-growth; the meaning of technological innovation under capitalism, commons, and degrowth; cooperative paradigms of tech development; and sustainable development and its alternatives.

Data mining concerns the steps needed to discover insights (e.g., identify patterns) from the collected data. Given the extensive data graduate students face in their studies, students need to understand the concepts of data mining techniques to process and analyze such massive data. This course provides an overview of the data mining pipeline. The course also provides an overview and hands-on skills in conducting research enabled by AI techniques (i.e., AI-powered research) to gain insights from data. The course also guides students through a complete journey of data mining steps (starting from data collection until presenting the obtained results) in real projects.

This course fulfills the "Research Methods and Design" area of the PhD curriculum.

In this course, students will examine and interrogate craft and materials-based practices in information studies. Topics might include book and paper arts (both historical and contemporary) and their role in GLAM institutions; critical data materialization and visualization using craft techniques (such as materializations of data using textiles, light, and sound); and the intersecting histories of craft and information practices in a variety of cultural contexts. Students will read a variety of theoretical and methodological readings on craft and will be invited to create crafts-based final projects that intersect with their dissertation research.

This course fulfils the "Design, Applied, and Creative Practice" area of the PhD curriculum.

This design research studio course examines interactive technology design in Human-Computer Interaction (HCI), Computer Supported Cooperative Work (CSCW), and related fields, highlighting key polemical moments that have influenced technology design and design research methodologies. The course begins by examining how the field has historically recognized its limits, particularly in understanding the disconnect between technical systems and their social contexts, as well as the methods employed for usability evaluation. Topics may include value-sensitive design and the integration of ethical considerations into technology design methods; persuasive design, highlighting the opportunities and challenges of designing for behaviour change; the reflective, critical, and participatory turns in HCI; the development of postcolonial approaches to design; labour issues in technology; and the history of critical technical practice-approaches to rethinking technology design.

The seminar concludes with an investigation of contemporary design paradigms that challenge assumptions about growth, participation, and alternative futures in technology. Students will undertake or further develop their own design research project and respond to weekly readings in a design workbook, articulating their reflections to polemical moments through open-ended, speculative design proposals, analysis, and reflection.

This course fulfills the “Design, Applied, and Creative Practice” area of the PhD curriculum.

This series of courses allows for the introduction of new curriculum that focuses on advanced topics in artificial intelligence (INF3200H-INF3210H).