data diversity & data cultures = flexible open by default policy

Government Information Day

Oct. 26, Library and Archives Canada

10:45 – 12:30 Government information & data ecosystem

Data Diversity & Data Cultures =

Flexible Open by Default Policy

Dr. Tracey P. LauriaultAssistant Professor of Critical Media and Big Data

School of Journalism and CommunicationCarleton University, Ottawa, ON, [email protected]

ORCID: orcid.org/0000-0003-1847-2738

mailto:[email protected]

Table of Contents

1. Critical Data Studies

2. Open Definitions

3. Types of Data

4. Data Cultures

5. Conclusion

Dr Tracey P. Lauriault, School of Journalism and Communication, Carleton University

1. Critical Data studies


Premise


Data are more than the unique arrangement of

objective and politically neutral facts

&

Data do not exist independently of the ideas,

instruments, practices, contexts and knowledges

used to generate, process and analyze them.

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

Socio-Technological Data Assemblage(Rob Kitchin, 2014, Kitchin & Lauriault 2014)

Algorithm studies

• Unpack the complex assemblages that produce, circulate, share/sell and utilise data in diverse ways;

• Chart the diverse work they do and their consequences for how the world is known, governed and lived-in;

• Survey the wider ecosystem of data assemblages and how they interact to form intersecting data products, services and markets and shape policy and regulation.

Critical Data Studies Vision

Rob Kitchin and Tracey P. Lauriault, 2018, Toward a Critical Data Studies: Charting and Unpacking Data Assemblages and their Work, in J. Eckert,, A. Shears & J. Thatcher, Geoweb and

Big Data, University of Nebraska Press , Pre-Print http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2474112

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2474112

2. Open Definitions


Open Data Definitions

• 1959 Antarctic Treaty

• 1992 - UNCED – Agenda 21 Chapter 40, Information for Decision Making

• 1996 Global Map

• 2002 – UNCED – Agenda 21 + 10 Down To Earth

• 2005 - Open Knowledge Foundation (OKNF) -11 Principles (Licence specific)

• 2007 GEOSS - Data Sharing Principles for the Global Earth Observing System of Systems

• 2007 - US Open Government Working Group -8 principles of Open Government Data

• 2007 Science Commons Protocol for Implementing Open Access Data

• 2007 Sunlight Foundation - 10 Principles for Opening Up Government Information

• 2007 OECD, Principles and Guidelines for Access to Research Data from Public Funding

• 2008 OECD, Recommendations on Public Sector Information

• 2009 W3C - Publishing Open Government Data

• 2010 Tim Berners-Lee 5 Star of Open Data

• 2010 Panton Principles for Open Data in Science

• 2010 Ontario Information Privacy Commissioner - 7 Principles

• 2013 Open Economics Principles

• US Association of Computing Machinery (USACM) – Recommendations on Open Government

• American Library Association (ALA) – Access to Government Information Principles

• 2013 G8 Open Data Charter

• 2015 International Open Data Charter

“In the context of Open

Information, Open by Default is

guided by the following set of

principles: Complete and

relevant: All government

information that has value to

the public is made available

unless there are privacy,

security or legal reasons for not

doing so”.

(Gov’t of Ontario Aug 11, 2017)

3. Types of Data


Types of Government Data

1. Survey Data

2. Geospatial Data

3. Spatial & Social Media

4. Scientific Data

5. Research Data

6. Knowledge Institution

7. Administrative Data


1. Survey Data

• Public Opinion Data

• Elections/Referenda

• Census

• Questionnaires

2. Geospatial Data

• Canadian Geospatial Data Infrastructure

• Remote Sensing –• Satellite & Radar &

• Drone & Air Photos

• Sensor Derived Data

• GeoDemographics

• Location

3. Spatial & Social Media

• Crowdsourcing

• Volunteered Geographic Information

• Twitter

• Facebook

• Linkedin

• GCTools

4. Scientific Data

• NRC

• NRCAN

• EnvCan

• Health Canada

• AAFC

• CSA

• Atomic Energy

• …..

5. Research Data

• Tri-Council Funded Data• CIHR

• NSERC

• SSHRC

• Research Data Canada

• Departments & Agencies• Scientific Data

• Collaborations

6. Knowledge Institutions

• Museums

• Archives

• Libraries

7. Administrative / Public Sector Data

• Data produced as part of the outcome of delivering and administering programs, services, projects, administration

• Performance & Accountability

• Audits

• Budgets

• Expenditures

• Contracts

• Business registry

• Grants & contributions

4. Data Cultures

Data Communities / Cultures

Research/scientific

Data

GovData

GeoDataPhysical

Sciences

AdminData

Public Sector Data

NGOs

Access to Data Open Data

Social

Sciences

2005

Operations Data

Infrastructural Data

Sensor Data

Social Media Data

AI/Machine Learning Data

Smart Open Data?2015

Private Sector

IOT

- Smart Cities

- Precision Agriculture

- Autonomous Cars

SM Platforms

Algorithms

AI

P2P – Sharing Economy

Predictive Policing

Surveillance

Digital Labour

Drones

5GPublic/Private Sector Data?

Crowdsourcing

Citizen Science

Civic Teck

OCAP

Local and

Traditional

Knowledge

2017-Beyond

5. Conclusion

Conclusion

• There will be many Open by Defaults• Data Types + Data Cultures

• Need to think infrastructurally• Institutions

• Standards - interoperability

• Technology

• Policy

• Law

• Regulation

• Long-term thinking• Archives

• Sustainable funding

• Expertise - science

• Not just data anymore• Algorithms

• Artificial intelligence

• Machine learning

• Autonomous

• Right to Repair

• Right to Explanation - Algorithms

• Data Subjects

• Right to Access

• Data Portability
