- From: Marta Sabou <marta.sabou@modul.ac.at>
- Date: Sat, 31 Jan 2015 19:59:04 +0100
- 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 http://tinyurl.com/q6brzzc ================================================================================= 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 18:59:39 UTC