1.
Canadian Aviation Safety Collaboration Forum
Data sharing:
Seeing & Thinking Together
International Civil Aviation Organization (ICAO)
Montreal, QC
January 23, 2019
Dr. Tracey P. Lauriault
Assistant Professor, Critical Media and Big Data
Communication and Media Studies
School of Journalism and Communication
Carleton University
E-mail: Tracey.Lauriault@Carleton.ca
https://orcid.org/0000-0003-1847-2738
CU IR: https://ir.library.carleton.ca/ppl/8

2.
Research and thinking that applies critical social theory to data
& technology to explore the ways in which:
Data are more than the unique arrangement of objective and
politically neutral facts
&
Understands that data do not exist independently of ideas,
techniques, technologies, systems, people and contexts
regardless of them being presented in that way
Critical Data Studies
Tracey P. Lauriault, 2012, Data, Infrastructures and Geographical Imaginations.
Carleton University, Ottawa, http://curve.carleton.ca/theses/27431

3.
Technological Citizenship
 We live in a technological society
 Decisions about technology are political
 We should not leave all technological decisions to the technocrats
 3 preconditions for technological citizenship
 Agency
 Capacity to act – power
 Knowledge
 Those who possess those preconditions have the responsibility to act and
intervene in the technological society
Andrew Feenberg, 2011
https://www.sfu.ca/~andrewf/copen5-1.pdf

4.
Socio-Technological Assemblage
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
Modified by Lauriault from Kitchin, 2014, The Data Revolution, Sage.

5.
Observations
“sharing data across organizations and broadly within the industry... expand the
concept of safety in numbers beyond the borders of your organization to the
industry…”
“…we are not competing on safety…”
Christopher San Giovanni, 22 Jan. 2019
 Multi-scale, broad scope of data sharing
 Many heterogeneous actors in one interrelated sector operating a vast global
system
 Much data, will to share, a governance structure / infrastructure is required
Can data sharing help you think like a large social and
technological system?
Do you have the data to help you see the whole system and do
you have the data to prevent, pre-empt and predict?

6.
Some Data Sharing Examples
 Global Earth Observation System of Systems (GEOSS)
 UN Global Working Group (GWG) on Big Data
 Committee on Data of the International Council for Science (CODATA)
 Research Data Alliance (RDA)
 World Data System (WDS)
 Canadian Geospatial Data Infrastructure (CGDI)
 Canadian Institute for Health Information (CIHI)
 Portage
 Ontario Geospatial Data Exchange (OGDE)

7.
Global Earth Observation System of Systems
 Coordinated, independent EO, information and processing systems that interact
and provide access to diverse information for a broad range of users in both
public and private sectors.
 GEOSS links these systems to strengthen the monitoring of the state of the Earth.
 It facilitates the sharing of environmental data and information collected from the
large array of observing systems contributed by countries and organizations within
GEO.
 GEOSS ensures that these data are accessible, of identified quality and
provenance, and interoperable to support the development of tools and the
delivery of information services.
 GEOSS increases our understanding of Earth processes and enhances predictive
capabilities that underpin sound decision-making:
 it provides access to data, information and knowledge to a wide variety of users.

8.
UN Global Working Group (GWG) on Big Data
 Statistical Commission to explore the benefits and challenges of the use
of new data sources and technologies for official statistics and SDG
indicators.
 The GWG addresses issues pertaining to methodology, quality,
technology, data access, legislation, privacy, management and finance,
and provide adequate cost-benefit analyses.
 The GWG consists currently of 28 member countries and 16 international
organizations.
 See the Project Inventory https://unstats.un.org/bigdata/inventory.cshtml
 See the Sandbox https://joinup.ec.europa.eu/solution/big-data-
sandbox/about
http://doi.org/10.22215/tplauriault.courses.2018.coms4407

9.
Committee on Data of the International Council
for Science
 Exists to promote global collaboration to advance Open Science and to
improve the availability and usability of data for all areas of research.
 Supports the principle that data produced by research and susceptible to
be used for research should be as open as possible and as closed as
necessary.
 Advances the interoperability and the usability of such data:
 FAIR (Findable, Accessible, Interoperable and Reusable).
 Promotes the policy, technological and cultural changes that are essential to
promote Open Science, CODATA helps advance ISC’s vision and mission of
advancing science as a global public good.
 See Data policy committee: http://www.codata.org/strategic-
initiatives/international-data-policy-committee

10.
Research Data Alliance
 RDA provides a neutral space where its members can come together:
 through focused global Working and Interest Groups
 to develop and adopt infrastructure that promotes data-sharing and data-
driven research
 accelerate the growth of a cohesive data community that integrates
contributors across domain, research, national, geographical and
generational boundaries.
 See Recommendations & Outputs: https://www.rd-
alliance.org/recommendations-and-outputs/all-recommendations-and-
outputs

11.
World Data System
 Objectives of WDS are as follows:
 Enable universal and equitable access to quality-assured scientific data, data
services, products and information
 Ensure long term data stewardship
 Foster compliance to agreed-upon data standards and conventions
 Provide mechanisms to facilitate and improve access to data and data
products
 Trusted Scientific Data Services and Data Communities
 Communities of Excellence for Scientific Data Services
 See Data Sharing Principles: https://www.icsu-wds.org/services

12.
Canada Geospatial Data Infrastructure
 The relevant base collection of:
 standards
 policies
 applications and
 governance
 that facilitate the access, use, integration, and preservation of
spatial data.
 GeoConnections lead the CGDI through:
 the use of standards-based technologies and
 operational policies for data sharing and integration
 Developed in partnership between provinces, territories, private
sector and standards bodies and the federal family
 See Standards and Operational Policies:
https://www.nrcan.gc.ca/earth-sciences/geomatics/canadas-
spatial-data-infrastructure/8902

13.
CGDI Principles
1. Open
enables better decision making, the CGDI is
based on open, barrier-free data sharing
and standards that allow users to exchange
data.
2. Accessible
allows users to access data and services
seamlessly, despite any complexities of the
underlying technology.
3. Evolving
the network of organizations participating
in the CGDI will continue to address new
requirements and business applications for
information and service delivery to their
respective users.
4. Timely
the CGDI is based on technologies and
services that support timely or real-time
access to information.
5. Sustainable
is sustained by the contributions of the participating organizations
and broad user community and through the infrastructure’s
relevance to these groups.
6. Self-organizing
the CGDI enables various organizations to contribute geospatial
information, services and applications, and guide the infrastructure’s
development.
7. User and community driven
emphasizes the nurturing of and service to a broad user community.
These users, including Canadians in general, will drive the CGDI’s
development based on user requirements.
8. Closest to source
maximizes efficiency and quality by encouraging organizations
closest to source to provide data and services. Thereby eliminating
duplication and overlap.
9. Trustworthy
is continually enhanced to protect sensitive and proprietary data.
The CGDI offers this protection through policies and mechanisms
that enable data to be assessed for quality and trusted by users.
Canadian Geospatial Data Infrastructure Vision, Mission and
Roadmap (2012) The Way Forward

14.
Canadian Institute for Health Information
 Independent, not-for-profit organization that provides essential information on
Canada’s health systems and the health of Canadians.
 Provides comparable and actionable data and information that are used to
accelerate improvements in health care, health system performance and
population health across Canada.
 Stakeholders use our broad range of:
 health system databases,
 measurements and standards,
 evidence-based reports and analyses,
 Data confidentiality & privacy
 Neutral and independent role
 Although we play an integral role in providing relevant and reliable data and analyses
to policy-makers in Canada’s health systems, we are neutral and objective in fulfilling
our mandate. We neither create nor take positions on policy.

15.
Portage
 Dedicated to the shared stewardship of research data in Canada through:
 Developing a national research data culture
 Fostering a community of practice for research data
 Building national research data services and infrastructure
 Communities of Practice
 Data Repositories

16.
Ontario Geospatial Data Exchange (OGDE)
 A Program of Land Information Ontario (LIO)
 Allows organizations to share geographic data about Ontario through a single
agreement administered by LIO.
 There is no cost associated with joining.
 Membership to OGDE:
 Municipal, provincial or federal government
 Indigenous community
 Conservation authority
 Public health unit
 Non-profit organization
 College or university
 Public utility
 Restricted access to members only w/specific agreements

17.
What is common
 Sharing for common good
 Stakeholder developed governance, principles and values,
 Stakeholder developed protocols, policies, procedure, rules, practices, values,
roles & responsibilities
 Regulation & Law
 Shared infrastructural responsibility
 Sharing agreements, accords, MOUs, etc.
 Data quality
 Data standards
 Privacy
 Security
 Lifecycle data management