Topics

  • Applications of crowdsourcing for traditional semantic web tasks:
    • approaches and systems hiding the authoring of ontologies, semantic annotations, links between entities in heterogeneous sources behind more accessible user activities (for instance, playing games, creating business contacts, adding events to the agenda)
    • models and approaches for community-based crowdsourced support of the different lifecycle stages of Linked Data such as knowledge extraction, authoring, and repair
    • crowdsourcing tasks for gathering content semantics
    • paradigms for user involvement during semantic bootstrapping activities and studies discussing experiences in this area;
    • architectures for the combined use of different crowdsourcing approaches and means to enable interoperability and data reuse
  • Improvement of existing human computation approaches through usage of semantic web technologies:
    • applications of semantic technologies in building flexible and scalable crowdsourcing technology (e.g., declarative task models)
  • Crowdsourcing fundamentals (in the context of the Semantic Web):
    • frameworks for using crowdsourcing
    • human-computation workflows optimizing user and machine performance
    • crowd management (incl. expertise identification, worker task assignment, incentive management)
    • evaluation metrics of crowdsourcing tasks
    • methods for quality control and validation of crowd-produced work
    • paid vs. not paid crowdsourcing workflows
    • gaming platforms for supporting crowdsourcing activities
    • nichesourcing for specific domain knowledge acquisition
    • hybrid models, languages, techniques and implementations leveraging both machine and human intelligence
    • studies exploring the added value of crowd-generated knowledge compared to expert-driven scenarios
    • methods for resource management and task assignment in crowdsourcing-enabled systems