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CFP: SWJ Special Issue on Human Computation and Crowdsourcing (HC&C) in the Context of the Semantic Web

From: Marta Sabou <marta.sabou@modul.ac.at>
Date: Sat, 31 Jan 2015 19:59:04 +0100
Message-Id: <6FF45F71-C5D8-4EAB-8319-D8DCBAEA91B5@modul.ac.at>
To: semantic-web@w3.org, public-lod@w3.org
 CFP  Semantic Web Journal: 
Special Issue on Human Computation and Crowdsourcing (HC&C) in the Context of the Semantic Web

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.
Received on Saturday, 31 January 2015 18:59:32 UTC

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