VALA14_burrows

  • 238 views
Uploaded on

Presentation delivered at #VALA14

Presentation delivered at #VALA14

More in: Education , Technology
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
238
On Slideshare
0
From Embeds
0
Number of Embeds
1

Actions

Shares
Downloads
0
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide
  • High-level look at HuNI – purpose, objectives, benefits and value
    Not going to look at the system architecture or the technical details of the project
    The HuNI Web site gives you all the project information
    The HuNI Wiki gives you all the technical details: data model, data integration pipelines, virtual laboratory functions
    I’m also going to give you some illustrations of the complexities of humanities research processes – which HuNI aims to address
  • 28 Australian data sources: mapped to a common Data Model, but not merged or de-duplicated
    Retain provenance of individual metadata records
    Data Model is deliberately broad and high-level – six high-level entities only
    Aggregated data will be published as RDF for reuse in the Linked Data Cloud
  • Discover and explore: any user (not logged in)
    Other functions: need an account. Will be open to general community, not just researchers
    Social linking – saying “this entity is related to that entity”
    Save and share: virtual collections
    Curate and import – working with Heurist to enable this
  • A few quick screen shots from the original prototype
    Search prototype is still available from the HuNI Web site
    The Virtual Lab functions (“My HuNI”) are being redeveloped – prototype no longer available
  • Search results
    Note: data sources, provenance information, ability to save record to a personal collection, ability to connect/link records
  • Network graph for each entity, showing other nodes connected to it (six degrees of separation)
  • A personal virtual collection
  • Details of the records in that collection
    Includes connections created by the user (i.e. me)
    “Entity types” will be replaced by entities from the new Data Model
  • Researcher- or user-centred – entity records, not library / museum / gallery catalogue records
    Data sources come from multiple disciplines – different vocabularies, different metadata schemas and database structures
    Data sharing not the norm in the humanities – can decide whether and when to share data
    Can build on others’ annotations (“massively single-player online game” – Will Wright)
    Collaboration at the heart of the virtual laboratory – shared collections, shared data, shared connections and links between entities
    Need to allow for the complex and unique nature of research in humanities and creative arts
  • A couple of examples to illustrate the nature of humanities data and humanities research
    Firstly: the multidisciplinary nature of data and research, and the way it’s centred on entities (people, works, objects, places, concepts…)
    Ned Kelly the person + the body + the author
  • Ned Kelly in literature
  • Ned Kelly in film
    Ned Kelly as theatre
  • Ned Kelly in art
  • Ned Kelly as popular culture and tourist attraction
  • Secondly: much of humanities research is about making connections and following trails
    Then assessing the significance of these connections and relationships
    Example – relationship between Paul Kelly to Ned Kelly, with 15 degrees of separation
    Paul Kelly – One night the moon – Kaarin Fairfax – Around the World in 80 Ways – Stephen MacLean – StarStruck –
    Gillian Armstrong – Journey among women – Tom Cowan – Promised Woman – Dorothy Hewett –
    Heartlands – John Kinsella – Randolph Stow – Tourmaline – Sidney Nolan – Ned Kelly
  • At the heart of humanities research – debates over categorization and definition
    A mistake to impose a normalized vocabulary – humanities data should not be homogenized!
    We’re trying to build some of this fuzziness into HuNI – with a bit of wah-wah too…
  • HuNI is due to be launched in June – opportunities to test and provide feedback before then

Transcript

  • 1. Humanities Networked Infrastructure Linking and Sharing Data for the Humanities and Creative Arts: building the HuNI Virtual Laboratory Dr Toby Burrows, HuNI Product Owner (University of W.A.) Prof Deb Verhoeven, HuNI Project Director (Deakin University) huni.net.au wiki.huni.net.au
  • 2. Building a new national data service that is of cultural significance and widely accessible, now and in the future Tools and apps The HuNI project is: •Integrating cultural data at a national level •Making this new data service accessible to all •Connecting to the Linked Data Cloud •Building the foundations for future growth App Tool HuNI lab app API HuNI National Data Service Existing 28 NEW Data sources App
  • 3. HuNI is… • Big – 275,000 entities and growing • Multi-disciplinary and cross-disciplinary – 28 data sources • Capable of answering complex questions quickly
  • 4. Users of the HuNI lab app can… • Discover and explore across the aggregated data • Make connections and create “socially-linked” data • Save and share their data and their findings • Curate and import their own data
  • 5. HuNI prototype
  • 6. HuNI will change the nature of humanities research • Working with data on a much larger scale • Breaking down disciplinary boundaries around data • Promoting data sharing • Encouraging collaboration to enrich data
  • 7. The amphibology of humanities data • How would you describe this music? • What’s Australian about this song?
  • 8. Follow our progress Project wiki wiki.huni.net.au HuNI website HuNI lab prototype huni.net.au ers Te s t * ed want app.huni.net.au