Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Data Visualisation & Data Management - Experiences & Lessons

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.

Dave Kelly

May 24, 2017
Tweet

More Decks by Dave Kelly

Other Decks in Education

Transcript

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

    View Slide

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

    View Slide

  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

    View Slide

  4. Galway2020

    View Slide

  5. Galway2020: Audience data in context (interactive)

    View Slide

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

    View Slide

  7. View Slide

  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

    View Slide

  9. Experiences & Lessons

    View Slide

  10. Planning & input

    View Slide

  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”
    !

    View Slide

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

    View Slide

  13. Standards & structures

    View Slide

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

    View Slide

  15. View Slide

  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
    "

    View Slide

  17. View Slide

  18. Pilot

    View Slide

  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”
    !

    View Slide

  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
    "

    View Slide

  21. Dr Patrick Collins & Dr Aisling Murtagh - Geography

    View Slide

  22. Consider outputs

    View Slide

  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”
    !

    View Slide

  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?
    "

    View Slide

  25. View Slide

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

    View Slide

  27. View Slide

  28. Galway’s Cultural Infrastructure

    View Slide

  29. View Slide

  30. Intellectual Property

    View Slide

  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
    !

    View Slide

  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
    "

    View Slide

  33. Sustainability &
    Maintenance

    View Slide

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

    View Slide

  35. David Kelly
    [email protected]
    THB-1011, Hardiman Research Building
    @davkell
    www.davidkelly.ie |
    Thank you

    View Slide