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CFP Semantic Web Journal:
Special Issue on Human Computation and Crowdsourcing (HC&C) in the Context of
the Semantic Web
http://tinyurl.com/q6brzzc
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Submission Deadline: March 31, 2015 (23:59 Hawaii Standard Time)
Stemming from its original motivation of extending the Web with a layer of
semantic representation, the Semantic Web (SW) aims to solve a set of complex
problems that computers cannot yet fully master such as the creation of
conceptual models, the semantic annotation of various media types, or entity
linking across Linked Open Datasets. As a result, the large-scale deployment of
Semantic Web technologies often depends on the availability of significant
human contribution, traditionally provided by specialised experts, for example,
ontology engineers to build ontologies or annotators to create the semantic
data or to link between the instances of various data sets.
Human Computation (HC) methods leverage human processing power to solve
problems that are still difficult to solve by using solely computers, and
therefore are well-suited to support Semantic Web research, for example, as
methods to create training data for advanced algorithms or as means to evaluate
the output of such algorithms. While HC methods could theoretically involve
only small numbers of contributors, crowdsourcing approaches, leverage the
"wisdom of the crowd" by engaging a high number of online contributors to
accomplish tasks that cannot yet been automated, often replacing a traditional
workforce such as employees or domain experts. As such, crowdsourcing methods
could not only support in creating research relevant data, but more importantly
they could help to solve the bottleneck of knowledge experts and annotators
needed for the large-scale deployment of Semantic Web and Linked Data
technologies.
This special issue aims to explore the current and future trends in using
methods that fall into the category of Human Computation, Crowdsourcing and the
intersection thereof (HC&C) to support Semantic Web research and the deployment
of Semantic Web technologies.
Topics of interest include but are not limited to:
• Experimental comparisons between various HC&C genres
• Best practices in decomposing large SW tasks into micro-tasks/game
units
• Best practices for presenting formal SW knowledge to non-specialists
in an easy to understand/engaging manner
• Reusable templates, task designs, and UIs
• Defensive task design
• Strategies for identifying, recruiting and engaging contributors
• Methods for task assignment and recommendation
• Methods for ensuring data quality
• Cheating detection
• Data aggregation methods
• (Semantic) Representation of HC&C workflows and data
• (Semantic) Representation of HC&C performers and task executions
• HC&C infrastructures and systems developed for SW specific tasks
• Methodologies and best practice guidelines for using HC&C in ontology
engineering
• Methods to closely combine human and machine computation
• Applications of HC&C methods in SW research and deployment
• Lessons from other research fields (e.g., NLP, databases) where HC&C
has been applied and what these lessons would mean for the Semantic Web
Guest editors:
• Marta Sabou, Technical University of Vienna
• Lora Aroyo, Vrije Universiteit Amsterdam
• Kalina Bontcheva, University of Sheffield
• Alessandro Bozzon, Delft University of Technology
Submissions shall be made through the Semantic Web journal website at
http://www.semantic-web-journal.net. Prospective authors must take notice of
the submission guidelines posted at
http://www.semantic-web-journal.net/authors. Note that you need to request an
account on the website for submitting a paper. Please indicate in the cover
letter that it is for the Ontology and Linked Data Matching special issue.
Submissions are possible in all standing paper type of the journal, see
http://www.semantic-web-journal.net/authors for descriptions: full research
papers, surveys, linked dataset descriptions, ontology descriptions,
application reports, tool/systems reports.
