[sigCR] CFP: SIG/CR Classification Research Workshop, November 2, 2013

[Grant Campbell]

Please excuse cross-postings.


Call for Proposals:

“Big Data, Linked Data: Classification Research at the Junction”

SIG/CR Classification Research Workshop




Saturday, November 2, 2013




ASIST Annual Meeting

Montreal, Canada

(http://sigcr.wordpress.com/2013/06/11/cfp-pdf/" target="_blank">http://sigcr.wordpress.com/2013/06/11/cfp-pdf/




ASIST’s Special Interest Group in Classification Research will hold its annual Classification Research Workshop as part of the ASIST Annual Meeting in Montreal, Canada, on November 2, 2013. The Workshop Program Committee is currently inviting proposals for papers to be presented at the workshop.




THEME




The growing ubiquity of cloud computing, mobile technology and large data collections has given fresh currency to two important information phenomena: big data and linked data. “Big data” refers to the rise of ambitious projects which cultivate both large datasets and massive quantities of unstructured data existing in the long tail of the Web. These projects, in their very reach and size, can yield suggestive patterns and significant predictive value. “Linked data” refers to the emergence of data which has been deliberately structured according to Semantic Web standards of resource description and linked through a complex network of relationships defined through formal ontologies.




While big data and linked data are often considered separately, classification research stands at the juncture between these two approaches, and can therefore provide a context in which researchers in each domain can benefit from the insights of the other. Classification forms the bedrock of the analysis of big data sets. Natural language processing, detection of linguistic behaviour, and the design of translation systems all rely on the painstaking definition of synonymies, genus-species relationships, whole-part relationships, and facet structures to extract meaning from data from vastly different sources with different degrees of definition and structure. Linked data projects employ the same classification principles in their formal definitions of domains and namespaces, their use of ontologies to reconcile and combine data from different namespaces, and the use of inferential logic to form reasonable inferences from data that has been linked together.




Classification research, therefore, has a key role to play in the emergence of new tools and functionalities that will determine how human communities adopt both big data and linked data into their information systems and behaviour. This workshop will bring classification researchers together with those exploring linked data and big data, thereby providing researchers and practitioners with the theoretical vocabulary to forge meaningful connections between these two phenomena.




FORMAT OF PROPOSALS:




Authors wishing to present a paper may submit a 500-word extended abstract. Extended abstracts should contain citations (not included in the word count). Presentations will be a maximum of 20 minutes long, followed by 10 minutes of discussion. Authors must present a draft of the paper to their session chair by October 25, 2013.




OTHER FORMS OF CONTRIBUTION:




The workshop will also feature a poster session (details to follow in a separate Call for Proposals), as well as a final session of discussion devoted to making connections between issues raised during the day, and suggesting ideas for the 2014 workshop.




PROPOSAL SUBMISSION AND EVALUATION:




Please submit your extended abstract to the following address by August 5, 2013:

D. Grant Campbell

Faculty of Information and Media Studies

University of Western Ontario

gcampbel at uwo.ca




The abstracts will be submitted to a double-blind review process, and authors will receive notification by August 30, 3013.




After the workshop, full papers will be published online in

Advances in Classification Research Online, http://journals.lib.washington.edu/index.php/acro





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D. Grant Campbell
Associate Professor
Faculty of Information and Media Studies
University of Western Ontario
London, Ontario
N6A 5B7
519-661-2111 ext.88483