ESWC2010 "Linked Data: Now what?" Panel Discussion slides

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  • 1. LOD achievements and challenges
    • Web - a global, distributed platform for data, information and knowledge integration
    • 2. exposing, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web using URIs and RDF
    • 3. Challenges
    Coherence: Relatively few, expensively maintained links
    Quality: partly low quality data and inconsistencies
    Performance: Still substantial penalties comparedto relational
    Data consumption: large-scale processing, schema mapping and data fusion still in its infancy
    Usability: Missing direct end-user tools and network effect
    These issues are closely related and need to be treated in an integrated, holistic fashion.
    Achievements
    Extension of the Web with a data commons (13.1 B facts)
    vibrant, global RTD community
    Industrial uptake begins (e.g. BBC, Thomson Reuters, Eli Lilly)
    Emerging governmental adoption in sight
    Establishing Linked Data as a deployment path for the Semantic Web.
    April 2008
    July 2007
    September 2008
    July 2009
  • 4. Make the Web a Linked Data Washing Machine
  • 5. Creating a network effect for Linked Data: Semantic Pingback
    update and notification services for LOD
    Downward compatible with Pingback (blogosphere)
    http://aksw.org/Projects/SemanticPingBack
  • 6. Linked Government Data - Ideal application scenario for Linked Data
    Public sector extremely fragmented (EU, national governments, states, local communities)
    Benefits:
    Transparency
    Close the gap between politicsand citizens
    Use of the creative potential of citizens
    new value added services
    4
  • 7. What was right?
    LOD as a pragmatic approach to the Semantic Web
    What was wrong?
    RDF being born after XML, LOD after the Semantic Web
    What should we do in the future?
    Establish a network effect around LOD
    Create the LOD washing machine
    Target Enterprise Information Integration,Open Governmental and Scientific Data
    From eat-your-own-dogfood toconvince-you-grandma
    What shouldn't we do?
    Neglect the interfaces between research,technology and applications