“Global Trends in Knowledge and
Information Management from the
iSchool at Toronto”
Presentation by Seamus Ross
Dean and Professor
May 21, 2014
ischool.utoronto.ca
Who are we and what is our legacy
TIMELINE CHART
 University of
Toronto Library
School Founded
 First ALA
Accreditation
1937
1928
197071
 MLIS Founded
(1970)
 PhD Founded
(1971)
 Move beyond
Library Science
into Information
Systems,
Archives,
Records
Management,
etc.
70s90s
1994
 Renamed MLIS
to MISt in
recognition of
changes in and
evolution of the
discipline
 Master of
Museum Studies
joins.
2006
2008
2014
 New Name:
Faculty of
Information
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People, Places, and Programs
• Programs offered:
–Master of Information (MI)
–Master of Museum Studies (MMSt)
– Doctoral Studies (PhD)
• People
– 28 faculty, 20 Staff and Librarians
– 405 MI, 76 MMSt, and 52 PhD students
•Places
–Bissell Bldg
–McLuhan Coach House
–Semaphore Labs in Robarts Library
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Foundations
• Information penetrates all aspects of our digitallymediated society
• Information professionals need to understand the
political, technological, and epistemological
consequences of changing information practices
• Education of information professionals must
therefore address issues of leadership and critical
thinking, and engage students with fundamental
concepts, theories, and practices
• Explorations of Information Use, Users, Technology
and Information Using Cultures are essential
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Key program characteristics (MI)
• Broad-based and inclusive, with informationfocused fields from different disciplinary and
professional viewpoints
• Flexible and customizable curriculum
– General Program
– Seven concentration options
– Thesis Option
• Increasing emphasis on Experiential and
Experimental learning
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Concentrations
Archives and Records Management
Critical Information Policy Studies
Culture and Technology
Information Systems and Design
Knowledge Management and Information
Management
• Knowledge Media Design
• Library and Information Science
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Information Systems and Design
• Focuses on the complex interplay between information
and communication technologies (ICTs) and information
practices, in the context of the needs and different
objectives of classes of information users in society and
organizations.
• Core themes of stewardship, organization, and
accessibility of information artifacts explored in relation
to the design and implementation of digital information
systems and media.
• Attention to personal, social, organizational, and societal
implications.
• Individuals, communities, and organizations who sponsor
or use these systems to create, communicate,
collaborate, and record information are, willingly or not,
engaged in an ongoing transformation of their
information environments.
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Knowledge Management and Information
Management
concepts, tools, and practices that enable the systematic, imaginative,
and responsible management of information in an organization or
community to promote social learning and innovation, and to provide
groups and individuals with the information they need to perform their
work
Topics include:
• Theoretical frameworks that integrate the creation, sharing, and
utilization of information and knowledge
• Effective use of information to support decision-making
• Knowledge access management, including metadata-enabled search
and resource discovery
• Strategic modeling of goals and dependencies for knowledge
management
• Design of information platforms for creating and sharing knowledge
• Health informatics as an elective specialization
•
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Recent IS&D Graduate Destinations
• Knowledge Management
Operations Specialist, PwC
• Business Analyst, Wunderman
• Business Analyst - Oracle ERP,
Deloitte
• Business Systems Analyst,
Regina Police Service
• Sr. Systems Analyst, Application
Analyst (Enterprise
Architecture), Rogers
• Senior Manager, Data Platform,
Globo.com
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Recent KMIM Graduate Destinations
• Business Analyst, Telefilm Canada
• Information Specialist, Bell
Canada
• Business Analyst, Ontario
government
• Knowledge Manager - Financial
Services & Innovation, PwC
• Information Specialist, George
Brown College
• Intelligence Analyst, Bennett
Jones LLP
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Professor Periklis Andritsos
Research focuses on the analysis of large
repositories and, more specifically, the
structure of discovery in order to facilitate
design and query optimisation.
Among his achievements:
clustering algorithm for categorical data,
which has also formed the basis of his work
on discovering alternative schemas in
databases with inconsistencies and errors.
His patented techniques have been
adopted.
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Prof Chun Wei Choo
Conducts research on knowledge
and information management,
information seeking, organizational
learning, and management of
information technology.
Recent externally funded research
focuses on: “Information seeking
and use in early warning systems”
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Prof Fiorella Foscarini
Research explores the issues of
diplomatics, genre theory, and
structuration within records
management and archival
principles and methods.
What is the relationship between
record keeping and organizational
cultures?
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Prof Andrew Clement
Research explores the social
and public policy implications of
information.
He focuses on identity, privacy,
and surveillance issues, as well
as related public education
initiatives.
Coordinates the Information
Policy Research Program (IPRP).
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Prof Eric Yu
Research focuses on the analysis and
design of information systems and
services in social contexts.
Behind the International Standard i*,
which supports analysis and modeling
of strategic actor relationships.
His projects include designing for
security and privacy, agile software
development, and business modeling
for business intelligence
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3 Big Trends in Knowledge
and Information
Management:
• Big Data
• Open Data
• Curation
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Big Data opportunities and challenges
– Opportunities:
• Better-informed decisions
• More effecting information targeting
• Faster turnaround of new discoveries
– Challenges:
• Data comes in diverse formats
• Data contains imprecision or inconsistency
• Existing techniques do not scale
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• Methods:
– Deploy them in parallel for speed-up
– Incorporate semantic information (ontologies)
– Combination of Data Management and
Statistical methods
• Systems:
– Turn hardware into commodities so it can be
applied in different domains
• Methods & System:
– Need the appropriate methods and data to test
new methods and technological improvements
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Trends in Open Data
Trends in Open Data
• June 2013 G7 Open Data Charter
– Massive projects across G7 to increase availability of
machine-readable government data, from
weather/climate data to small business suppliers of
government services/contracts
• McKinsey 2013 Report
– Observed that making more data open could unleash an
estimated $3 trillion in annual economic potential.
– Enhances the value of the “big data” initiatives
– Has the potential for massive benefit for regular consumers.
(Big data has been largely beneficial to large private
corporate actors, at least to date.)
– Can enhance productivity significantly
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EU Open Data Initiative
• June 2013 – revision of data reuse directive
gave all EU member states two years to
revise national laws to comply with a
directive with the principles of:
– Charges to be made on the basis of actual cost
and clearly published;
– No cross-subsidies or exclusive data
arrangements;
– Requests must be processed within specified
periods of time
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US Open Data Initiative
• Announced in 2013; in May 2014, the CIO for
the USA announced some significant
progress
• “Freely available data from the US
government is an important national
resource.”
– strong recognition of the huge importance of
large government datasets as economic driver.
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Research Data Alliance
• Aims to facilitate the
construction of social and
technical bridges that enable
open sharing of data.
• The RDA vision is researchers
and innovators openly sharing
data across technologies,
disciplines, and countries to
address the grand challenges
of society.
• Funded by Australia, EC, and
USA
• https://rd-alliance.org/
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Trends in Digital and Data Curation
• Digital Curation an umbrella term –
Digital curation involves maintaining,
preserving and adding value to digital
material throughout its lifecycle
• That is it is Digital Curation applies more
broadly than to purely research data
DCC -- http://www.dcc.ac.uk/digitalcuration/what-digital-curation
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• Discussions of digital longevity have been
driven by perspective of memory institutions
which have not traditionally been in the
data business.
• Perspective has shaped the ways we
educate folks in digital curation.
• We have focused on preparing them for
curating data and not for creating value
from it. -- We are moving focus to include
both curating and value creation.
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Stijn Viaene in an essay about the data
science ecosystem as a process of “modeling,
discovery,operationalizing, and cultivation got
it right when he wrote
“It will take a lot of conversation to make data
science work. Data scientists can't do it on
their own. Success in data science requires a
multiskilled project team with data scientists
and domain experts working closely
together.” Data Scientists Aren't Domain
Experts (IT Professional, Dec 2013)
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Knowledge and Experiential requirements
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Curation – preservation sense
Data Analytics
Visualisation
Statistics
Machine Learning -- Automation
Metadata & Annotation
Information Architecture
Data Quality
Rights, Privacy, Security
Interoperability
Collection Development
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Liz Lyon, Data Scientist and co-founder of DCC
• “data engineer - focus on software
development, coding, programming, tools
• data analyst – focus on business/scientific
analytics and statistics e.g. R, SAS, Excel to
support researchers and modellers, business
• data librarian – focus on advocacy, research
data management / informatics in a university /
institute
• data steward – focus on long term digital
preservation, repositories, archives, data
centres
• data journalist – focus on telling stories and
news”
© liz-lyon-microsoft-escience-chicago-october- 2012-final.ppt (downloaded 17 Feb 2014)
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Educational Directions for the iSchool
• More experiential and experimental learning
environments
• Data analytics
• Data curation
• Information behaviour
• More data scientists
• More digital media enablers
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Challenges in Changing Direction
• Many of our students come from
Humanities/Social Science background
• Lack of awareness of growth potential and
variety among many recruits
• Perceived split between “traditional” and
“new” information disciplines – does not
actually exist, but perception is damaging
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My Question for you
• Are there opportunities for Collaborations?
• What do we need to be doing in our
programs?
• What trends to you, as experts and
employers, foresee?
• How can we prepare our graduates for
success in your industries?
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Thank you
seamus.ross@utoronto.ca
ischool.utoronto.ca