Stresses analytical models of how problems are solved and decisions are made in information organizations. Introduces models and methods from organization theory, decision science, and information needs and uses studies.

The course will introduce students to the legal framework that applies to the creation, management, preservation and use of public and private archival documents in Canada. The specific objective of this course is to provide students with an understanding of the fundamental concepts of the Canadian legal system and of the implications and challenges of the law for public and private sector archival institutions.

This course introduces students to the ethics, principles, frameworks, and methodologies implicated in the design and creation of data collection and governance systems centered on the rights to sovereignty and self-determinism of First Nations, Inuit, and Métis peoples, as well as Indigenous peoples in a global context. The course surveys the legal and political dynamics of Indigenous-settler relations, with an emphasis on the problematic history of data collection by state and non-state actors within Indigenous populations, and on the data sovereignty countermeasures developed and deployed by Indigenous communities. This course develops students’ understanding of key distinctions between Indigenous and western epistemic traditions, worldviews, and ways of being by incorporating Indigenous methodologies and understandings of data collection and research into its critical and analytical frame. Special attention is paid to the data governance and sovereignty principles embodied in core frameworks such as the OCAP (Ownership, Control, Access, and Possession) and CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) models, and the emerging legal and jurisdictional implications of policy mechanisms such as UNDRIP (United Nations Declaration on the Rights of Indigenous Peoples). The course engages with emerging trends and case studies in Indigenous data governance, inclusive of operationalized examples of core frameworks across various jurisdictions such as the Inuit Circumpolar Council, and through data governance policy development within settler governments, institutions, and industries.

This course will provide students with knowledge needed to understand the advocacy process and exercise professional leadership in the advocacy of library issues. Such advocacy may relate to policy, funds, support, or partnership, and may be directed to internal or external decision-makers. The course includes the nature of advocacy and its relationship to promotion and marketing, decision-makers’ environments and their perceptions of libraries, research on influence, and the identification and strategic engagement of influencers and decision-makers. Major emphasis is on the development of advocacy programs (objectives, target groups, obstacles, communication tools, and evaluation). Although the course focuses on publicly funded libraries, most principles, examples, and case studies are relevant to all types of libraries and to related institutions.

The primary objective of this course is to provide students with a comprehensive understanding of current global and national issues surrounding intellectual freedom, library neutrality, and the right to information. Through theoretical readings, historical analysis, case studies, and interactive scenarios, students will explore the complexities of information access, censorship, and the role of various entities in shaping knowledge circulation and limitation. While the course will offer a basic theoretical, legal, and historical introduction to the subject, the main emphasis will be on present-day issues facing intellectual freedom globally, given the rise of authoritarianism, government and corporate surveillance, government thought control through the manipulation of media, regional wars, global psychological warfare, and campaigns of misinformation.

Develop an appreciation of the modern public library’s history paying particular attention to the wider social forces (economic, political, cultural, social, technological, and professional), which have shaped its evolution and that of public librarianship from the mid-19th century.

This course examines books and other textual artifacts as material objects, focusing on methods of production and manufacture, and how they affect the transmission of texts. Students are introduced to theories and methods of bibliographical description and analysis, and to their application across a range of media. Classes cover the history of textual production, from hand-press to digital books, and its relevance to disciplines such as librarianship, digital curation, and digital humanities.

This course investigates print and digital publishing ecosystems both holistically and through their individual functions, including authorship, publishing, printing, bookselling, librarianship, and reading. Drawing on disciplinary perspectives such as publishing studies, media studies, and book history, the course considers topics such as literary production, distribution, and circulation, with emphasis on connections between past and present. The interplay between social, cultural, economic, technological, and political forces will be examined through case studies on small and large scales, from the local to the transnational.

This course serves as an introduction to rare book and manuscript librarianship. Students will explore concepts ranging from book history and bibliographical description to the stewardship of rare books and manuscripts, and strategies for advocacy and outreach on behalf of special collections. While especially relevant for students interested in special collections librarianship, the course is accessible for all students with interests in rare books and manuscripts.

Business processes are pervasive in our lives: in banks, telecommunication centers, webservices, and healthcare. Processes in organizations are there to make sure that the business goals are achieved in an efficient way with the highest quality of products and/or services. The field of Business Process Management (BPM) focuses on improving an organization’s performance by managing, analyzing and improving its processes.

The first part of the course comprises basic concepts of Business Process Management. We shall learn the BPM lifecycle: (Re)Design, Modeling, Executing, Monitoring and Optimizing business processes. Moreover, we shall cover the methodological aspects of BPM such as modeling languages, model discovery, qualitative and quantitative analysis of processes models.

In the second part of the course, the focus shifts to a Data Science methodology for BPM, namely Process Mining. The students will learn the three basic steps of Process Mining: discovery of models from data, conformance analysis of the resulting models with data, and performance analytics. The emphasis of the Process Mining part will be on performance analytics.

The course will cover state-of-the-art literature, and as part of the final grade will require the students to present real business case studies on applications of BPMM in industry.

Note: Formerly a special topics course.  Effective fall 2020, the course is a regular course.

This course can be used to fulfil the "Managerial" Professional Requirement

Data science is a fast-growing field and new tools and techniques are designed everyday to perform data analysis in quick and robust ways. This course covers the fundamentals of data science using the R language and environment for statistical computing and graphics. R is currently widely used by information students and data scientists from various disciplines. The course will teach students how to do data science in an easy way. It is designed for students from the social sciences and from non-programming backgrounds. The course focus is not on learning a new programming language but rather on providing students with skills to approach various research questions that involve analysis of social sciences data. We will learn skills of data collection, storage, cleaning, transformation, visualization, and various techniques of data analysis. Most important, we will learn how those skills are applied in research involving the social world. We will apply those techniques to analyze structured tabular data, networked data, and unstructured text data through experimenting on real datasets, including online data. This course will provide students with a new skill highly in demand in the information and data
sciences job markets.

This course can be used to fulfil the "Technical" Professional Requirement.

Theoretical and practical implications for a user-centered perspective on the development of computerized information systems. Topics include user participation, alternative development methodologies, end-user computing, prototyping techniques, computer-supported cooperative work. Emphasis on the development of systems at the workgroup level using common software packages.

The term ‘information architecture’ (IA) generally refers to how online content is structured to support effective information use. Course lectures are divided into three rubrics: Information Design Fundamentals (design principles), Information Architecture Development Process (development methods), and Professional Practice (working as an information architect). An explicitly user-centred (‘bottom-up’) approach to the development process will be taken throughout. At the end of this course, students will be able to differentiate between the various disciplines implicated explicitly or implicitly in the development of information architecture. They will be able to understand and apply basic principles of cognitive psychology, industrial design, systems analysis and human-computer interaction to the practice of information architecture. Student will also learn to apply simple user-centred methods to address information architecture problems in the context of work places and practices. Finally, students will learn to apply information architecture principles and development methods to create and refine an information architecture schema to address an information design problem, and to create a rapid prototype to demonstrate information architecture schemata. The format of the course comprises lectures, reinforced by two assignments, a quiz and a final exam.

This course introduces students to the selected theories underlying reading studies and readers’ advisory (RA); the major genres and sub-genres of fiction and non-fiction materials that comprise the core of RA work; a wide array of RA print and electronic tools; and current practices of delivering RA services in both public and academic libraries, with the focus on the former. The concept of integrated RA will be reviewed, and alternative formats for providing advisory services will be discussed (films, music, games, Living Libraries, etc.).

Practica in selected aspects of professional work designed for advanced level students to strengthen and build on theoretical knowledge and to develop specialized skill in aspects of professional information work and environments through supervised experiential learning and seminar presentations.

An exploration of the evolution of records and record-keeping practices, primarily in the western world, from antiquity to the present day and the role played by archives in that evolution. Consideration will be given to the socio-cultural contexts in which records have been created, used, and preserved over the centuries, the role of records in the lives of organizations and individuals, the places of their creation and preservation, and record genres and media.

An introduction to principles, conceptual issues, and practical problems of managing organizational records, both paper-based and electronic. Reviews the legal, administrative, and technical environments that affect the creation, management and use of records. Discusses standards and policies that relate to organizational records and examines functional requirements for record-keeping. Identifies organizational and human factors that affect the creation and use of records. Finally, the course acquaints students with the strategies, techniques and tactics for ensuring that electronic records are captured, preserved and usable over time.

The course covers both theoretical and practical aspects of managing information processes in organizations. In terms of theory, it introduces conceptual frameworks for the management of organizational information processes, including an analysis of their implications for the design and implementation of information systems and services.

This course examines various notions of information architecture, systems architecture, and organizational architecture, and their inter-relationships and interactions. Examples will be drawn from a wide variety of systems types, including traditional information systems, document management systems, workflow systems, groupware, Internet and intranet systems, enterprise systems, data warehousing, metadata repositories, and intelligent agents. Issues will include dealing with legacy and change, enterprise-wide interoperability and beyond (e.g., e-commerce), convergence of information content and processing, and support for knowledge management. Frameworks and techniques for architectural modeling, analysis, and design will be considered.

At the heart of every Data Science project exists the planning, design and execution of experiments. Such experiments aim at understanding the data, potentially cleaning it and performing the necessary data analysis for knowledge discovery and decision-making. Without knowing the experimental design processes that are used in practice, researchers may not be able to discover what is really hidden in their data. The first aim of this course is to look at existing experimental designs that take into account the questions that need to be answered as well as the nature of the data and the different parameters used by algorithms.

Subsequently, the course will introduce different qualitative and quantitative methods to assess the quality of the results.

All concepts will be accompanied by examples and the students will have practical exercises and a project in which they will demonstrate their knowledge.

Machine learning has recently become the dominant field in AI research and constitutes the main part of the tools applied in industry-based AI positions. Business analysts, data scientists and AI engineers are required to know machine learning at different levels. The course will give a broad high-level overview of state-of-the-art machine learning methodologies. We shall focus on the application of these techniques to real-world data using the most advanced tools available for Python. The techniques will include: linear regression, basic techniques for classification, advanced regression and classification
methods, and unsupervised learning.

This course can be used to fulfil the "Technical" Professional Requirement.

The purpose of this course is to provide students with an understanding of the needs of archival users, and methods for facilitating access to archival material. The course focuses on information seeking behaviour in an archival context, and the principles, design, and implementation of access and outreach services in an archives. Topics covered are: the information needs of the major user groups including historians, genealogists, administrators, media specialists and school children; remote and on-site access services that meet the needs of various user groups; user education, public programming, outreach, and archival advocacy.

Introduction to policymaking and the players and stakes involved in information creation, access and use. Emphasis on the political, economic, legal and social issues affecting information and its institutions, including relevant social theory and analytical methods. The focal policy issues considered in depth will vary from year to year: e.g. government information, intellectual property, intellectual freedom, (universal) access, cultural content, community networking, and privacy.

This course addresses problems, practices, and techniques that arise from the growing use of visualization media to analyze and interpret data, manage information complexity, and communicate data-driven messages. Based on principles from visual studies, graphic design, visual art, perceptual psychology, and cognitive science, students will acquire the ability to use and understand several important visualization methods and how to critically interrogate the application of visualization technologies in novel contexts.

Knowledge management from an information systems perspective. Analyzing information and knowledge processes in organizations. Explicit and implicit/tacit knowledge in software systems and in human social systems. Languages and models for codifying knowledge. Application of information technologies to knowledge management. Ontologies and the semantic web. Knowledge management in information systems development. Applications in selected areas such as enterprise management, e-commerce, healthcare, media, and education.

Theories and methods of appraisal for records retention and archives acquisition to include managing records, constructing historical identities and pluralizing social memory. Emphasis on appraisal for archives acquisitions, including organizational and personal records in multiple formats, media and systems. The multiple uses of appraisal will be emphasized, especially in information management, record-keeping system designs, legacy conversions, and in managing change and innovation in archives. Emphasis on professionally responsible accountability to contemporaries and the future.

With reference to different types of metadata (structural, descriptive, rights management, administrative, preservation, etc.) this course provides an examination of semantic and syntactic metadata schemas and applications across diverse domains, such as education, medicine, government information, cultural sector institutions, publishing, etc. Analyses of international metadata standards development, and a case study approach to metadata projects within a content management framework are important components of the course.

The influx of data that is created, gathered, stored and accessed has given birth to some new areas of data analysis. The terms “predictive analytics”, “big data” and “data science” are prevalent in scientific as well as broad audience publications and often make part of new business opportunities. Understanding the significance of techniques that perform analytics and knowing how to interpret their results offers a unique advantage in the performance of information professionals within an organization.

User Interface Design is broadly concerned with the design of user interfaces for machines and software. On computer screens, this refers to the shaping and the presentation of navigation controls and information displays, as well as functional controls. With the gradual rise over the last decade in mobile and ubiquitous computing (the “internet of things”), the study of user interface design has necessarily broadened to small screens and even everyday objects. Students will learn basic principles of user interface design, interaction models and laws, differentiation of interaction styles, and different user interface paradigms. More practical topics may include physical ergonomics, cognitive ergonomics, design guidelines for different platforms, differentiation of interaction styles, design widgets, accessibility, localization, and software prototyping tools.