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Ongoing Research in Data Studies


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Data Day 3.0
Tuesday, 29 March 2016, 9:30 to 10:45, Carleton University

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Ongoing Research in Data Studies

  1. 1. Ongoing Research in Data Studies Data Day 3.0 Tuesday, 29 March 2016, 9:30 to 10:45, Carleton University Dr Tracey P. Lauriault, School of Journalism and Communication, Carleton University & Programmable City Project, Maynooth University
  2. 2. Data Studies Vision  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 landscape of data assemblages and how they interact to form intersecting data products, services and markets and shape policy and regulation Rob Kitchin and Tracey P. Lauriault, Forthcoming, 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
  3. 3. How is the city translated into software and data? Programmable City Project Translation: City into Code/Data Transduction: Code/Data Reshape City THE CITYSOFTWARE/DATA Discourses, Practices, Knowledge, Models Mediation, Augmentation, Facilitation, Regulation How do software and data reshape the city?Rob Kitchin, 2013
  4. 4. Socio-technological data 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 Critical data studies New media studies game studies Critical Social Science Science Technology Studies Platform studies Places Practices Flowline/Lifecycle Surveillance studies Rob Kitchin, 2013
  5. 5. Knowledge Production Tracey P. Lauriault, 2012, Data, Infrastructures and Geographical Imaginations. Ph.D. Thesis, Carleton University, Ottawa, Making up Spaces and People – Modified Ian Hacking Dynamic Nominalism Framework
  6. 6. 3 Case Studies 1. Ontologizing the city 2. The making of homeless people 3. Open data
  7. 7. 1. Ontologizing the City
  8. 8. Ontologizing the City - From Old School National Cartographic Based Classification toward a Rules Based Real-World Object Oriented National Database Object of Study  Data assemblage of OSi PRIME2  Examine how ‘real’ things are understood in the new object oriented data model  Assess if these change how space is modelled and then acted upon Time frame  Jan. 2015-2018 Data Management and Ethics  ERC  Maynooth University  SSHRC Tri-Council Case Study Outputs  Case study report  Data assemblage  Tracing the production of space  Genealogy from class to object  Academic publications Funding  Programmable City Project  P.I. Prof. Rob Kitchin  NIRSA, Maynooth University  European Research Council Advanced Investigator Award  ERC-2012-AdG-323636-SOFTCITY
  9. 9. Data Collection Attend OSi & 1Spatial Road shows and public speaking events  One day coordinated field trip & group interviews at OSi Sligo (survey data capture unit)  Examine the Prime & Prime2 flow lines  Real-time survey and data update of a building  1.5 months as an embedded researcher, OSi in Phoenix Park  One-on-one interviews with key actors (Transcribed audio recordings):  Group interview  Document Collection  Collection of objects across time for Dublin
  10. 10. Prime 2 Models and Concepts Skin of the earth ‘real world’ object modelling 5 skin of the earth objects  Ways  Water  Vegetation  Artificial  Exposed  Z-Layer  Superimposed Objects  Segmentation & Connectivity  GDF1 GDF2 centrelines  Sites & Locals  Boundaries  Links objects using persistent ID’s  Form & Function object classification  3D data storage (CityGML LOD2)  Grouped
  11. 11. Seamless, topologically consistent blanket of polygons covers the entire surface of Ireland w/no holes or gaps
  12. 12. Cassini, 6”, 1st ed. Circa? Heuston station across time Cassini 6”, 1943-44 Cassini 25”, 1st ed, Circa? Cassini25”, 1936 Heuston Station, Prime2 MapGenie Heuston Station, Prime2 SOE
  13. 13. Evolution  Institutionally  Colonial surveyor  Military Mapping Organization  Civil Service National Mapping Organization (NMO)  State Body NMO  Will become a NMO w/in Tailte Éireann  Technologically  Data collection  Techniques  Scale  Geometry  Skill  Technologies  Dissemination  Scope  Colonial mapping  National mapping  Post Colonial mapping  OSi/OSNI/OSGB  EU / Inspire / NSDI  Global
  14. 14. Etymology
  15. 15. Relationality
  16. 16. Genealogy of a model
  17. 17. Genealogy of a data model
  18. 18. Models are also actors  Models shape  how the world is viewed  the world of work  tools & techniques  the structure of an organization  how organizations interconnect with others  Models augment space  Models are socially constructed by people
  19. 19. 2. Making of Homeless People
  20. 20. http://www.homel http://www.dublincit count-figures-rough- sleeping-winter-2014- across-dublin-region /en/census/censu s2011reports/ho melesspersonsinirel andaspecialcensus 2011report/ The making of homeless people
  21. 21. Homeless case study scope Object of Study: A. Dublin Ireland:  Pathway Accommodation and Support System (PASS)  Dublin Street Count  Central Statistics Office (CSO) national census enumeration of the homeless. B. Boston, MA, USA:  Homelessness Data Exchange (HDX) Housing and Urban Development (HUD) Housing Inventory Count (HIC)  Boston Health Commission Annual Street/Point- in-Time (PIT) Count of Homelessness  US Census Bureau National Survey of Homeless Assistance Providers and Clients (NSHAPC) C. Ottawa, ON, Canada:  National Homelessness Information System (HIFIS)  Ottawa Street Count  Statistics Canada national census enumeration of the homeless.  Federation of Canadian Municipalities (FCM) Municipal Data Collection Tool (MDCT) indicators on Homelessness Funding  Programmable City Project  P.I. Prof. Rob Kitchin  NIRSA, Maynooth University  European Research Council Advanced Investigator Award  ERC-2012-AdG-323636-SOFTCITY
  22. 22. Homeless case study outputs A. 3 site specific city case studies for comparative analysis  3 CS reports with accompanying data, information and literature including:  3 national homeless shelter intake software systems  3 city specific point in time street counts  3 national statistical agency censuses which enumerated people who are homeless  Interview recordings and transcripts from key informants  Repository of related grey literature  B. Data Assemblages  Data assemblage for each intake data system, street count and homeless census  Comparative analysis of these data assemblages  C. Construction of homeless people and homelessness  Application of the modified Ian Hacking framework to the making up of homeless people and spaces  3 homelessness data classification genealogies  Comparative analysis of genealogies  D. Academic Papers
  23. 23. 3. Open data
  24. 24. Open data case study Object of Study A. Dublin, Republic of Ireland (NI) B. Ottawa, ON & Montreal, QC, Canada  National, County Level Public Sector Data Portals  Academic Portals  Public, Academic and Private Sector Partnership Portals/Initiatives  Open access to data initiatives  The private sector data dissemination on behalf & w/ the public sector.  Research projects  Civil Society Initiatives  Initiatives that have shaped debates on openness & transparency  Indicators & evaluation  Consultants/developers  Other actors  Tools & Instruments Case Study Outputs: A. 2 site specific city case studies B. Data Assemblages & Landscape C. Open Data discourse Analysis D. Academic Papers Funding  Programmable City Project  P.I. Prof. Rob Kitchin  NIRSA, Maynooth University  European Research Council Advanced Investigator Award  ERC-2012-AdG-323636-SOFTCITY
  25. 25. Open Licences
  26. 26. Open Source/Formats/Specs
  27. 27. Open Infrastructure
  28. 28. Open Data Definitions (sample)  1959 Antarctic Treaty  1992 - UNCED – Agenda 21 Chapter 40, Information for Decision Making  1996 Global Map  2002 – UNCED – Ageday 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 Informatio  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
  29. 29. Data cultures Research Data GovData GeoData Physical Sciences Public Sector Data Access to Data Open Data Social Sciences 2005 VGI Crowdsource Citizen Science Scientists, Cultural Institutions E-Government, CTOs AdminData
  30. 30. Communication & Media Studies
  31. 31. Core courses  COMM 5225 (0.5) Critical Data Studies  DATA 5000: Introduction to Data Science Electives  COMM 5203 (0.5) Communication, Technology & Society  COMM 5224 (0.5) Internet Infrastructure & Materialities  COMM 5221 (0.5) Science & the Making of Knowledge
  32. 32. Acknowledgements The research for these studies is funded by a European Research Council Advanced Investigator award ERC-2012-AdG-323636-SOFTCITY. I would like to express my gratitude to Ordnance Survey Ireland (OSi), Dublin City Council and the Open Data Community in Ireland for generously sharing their knowledge and time.