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Data sharing: Seeing & Thinking Together

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Presented at the:
Canadian Aviation Safety Collaboration Forum
International Civil Aviation Organization (ICAO)
Montreal, QC
January 23, 2019

This presentation was made in real-time while attending the Forum. The objective was to observe and listen, and share some examples outside of this community that may provide insight about data sharing models with a focus on governance.

Publié dans : Technologie
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Data sharing: Seeing & Thinking Together

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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

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