Data Visualisation & Data Management - Experiences & Lessons

Edited version of a presentation given to the BuSK (Building Shared Knowledge) project partners at NUI Galway, May, 2017.

The presentation outlines, with examples, experiences and lessons learned in the development of research projects from the social sciences that focus on data collection, management and visualisation.

Transcript

1. Data Visualisation &
   Management
   David Kelly – Digital Humanities Manager
   May, 2017
   – Experiences & Lessons
   

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2. Overview
   • Data Visualisation
   – Selected examples from Whitaker Institute
   projects
   • Data collection & management
   – Experiences & Lessons
   

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3. GalwayDashboard.ie
   Includes data from:
   CSO
   Galway City Council
   Galway County Council
   Enterprise Ireland
   IDA
   Údarás
   WDC
   PRTB
   EPA
   Póbal
   Economic Baseline Assessment for Galway City & County
   Prof. James Cunningham, Galway City Council, Galway County Council
   

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4. Galway2020
   

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5. Galway2020: Audience data in context (interactive)
   

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6. Cultural Networks
   Data from interviews with
   cultural practitioners:
   • Demographic
   • Funding
   • Relationship types
   • Geographic data
   Dr. Patrick Collins - Geography
   

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8. • Data structure
   • Merge existing data
   with data extracted
   from web sources
   • Data cleaning
   • Data enhancement
   through geo-coding
   • Web / storage
   infrastructure
   • Visualisation outputs
   http://mapping.creative-edge.eu
   Dr. Patrick Collins - Geography
   Data oriented
   project example
   

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9. Experiences & Lessons
   

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10. Planning & input
    

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11. “Crucially, plan ahead and get technical
    input early on.
    Raise awareness among partners of the
    importance of planning and structure so
    there’s a will to cooperate”
    !
    

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12. Talk to developers / designers as
    early as possible – preferably
    prior to data collection
    "
    

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13. Standards & structures
    

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14. “Because we collected the data in Excel
    it…left quite a bit of room for inconsistences
    in structure across the data collected”
    !
    

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16. • Agree standards for data structure before
    any collection
    – Data collection forms / templates
    – Various measurement units
    • date formats
    • levels of geo-data (city / county / local area /
    province…)
    • Abbreviations
    – Pre-defined categories / vocabularies
    "
    

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18. Pilot
    

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19. “Piloting could help too – taking a small
    portion of data and seeing how things work
    in practice. We collected data…that we
    didn’t do anything with because it was so
    patchy in places.”
    “Piloting could help to understand where to
    focus data gathering, what’s feasible to
    collect and help test the data gathering
    format/structure”
    !
    

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20. • Pilot collection of same data in more than one
    region
    – Identify potential inconsistencies early
    • Experiment with output formats for different
    stakeholders
    – User test with stakeholders
    "
    

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21. Dr Patrick Collins & Dr Aisling Murtagh - Geography
    

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22. Consider outputs
    

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23. “Having a structure around data
    collection linked to outputs and
    visualisation is key.”
    “The exact nature of the desired end-product might
    not be clear from the start. The structure could need to
    be re-visited at different stages of development.”
    “If this kind of process was built in it could also help to
    establish a clearer idea about the end output and how
    to achieve it”
    !
    

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24. • Think about outputs for different audiences
    – Presentation format – static / interactive,
    narrative, video, animation, raw data. (Or mixed?)
    – Formats for open data; are visual outputs
    downloadable / shareable?
    – Meta-data associated with various outputs
    (original sources, years, etc)
    • Work forward from research plan and
    backwards from desired outputs
    – Will you have the data you need, in the format
    you need, to produce the outputs you want?
    "
    

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26. Display the high-level
    overview
    Allow user to
    explore based on
    their interests
    http://mapping.creative-edge.eu/business
    

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28. Galway’s Cultural Infrastructure
    

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30. Intellectual Property
    

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31. “Thinking about intellectual property
    within this process is key…when project
    proposals are put together this doesn’t often
    get considered deeply and can limit what
    you can do.
    “I think it really needs specialist knowledge
    and can remain a grey area for non-
    experts. This makes it challenging to
    balance openness and data protection
    !
    

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32. • Engage with subject matter specialist early
    in the planning process
    • Consider data sources being used, and
    the impact they may have later in the
    project
    "
    

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33. Sustainability &
    Maintenance
    

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34. • Plan beyond the life of the project
    – How (or is) the data updated?
    – Plans for data preservation?
    – Plans for infrastructure maintenance?
    "
    

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35. David Kelly
    david.d.kelly@nuigalway.ie
    THB-1011, Hardiman Research Building
    @davkell
    www.davidkelly.ie |
    Thank you
    

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