Seminars & Workshops


SIG/CR Workshop:  Big Data, Linked Data:  Classification Research at the Junction

This workshop will bring classification research to bear on the complex relationship between linked data and big data. Researchers will use fundamental classification principles to articulate the junction between practices of extracting data from large, unstructured datasets and practices of constructing deliberate syntheses of linked data drawn from existing datasets structured according to Semantic Web standards. 

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. 

Speaker:  D. Grant Campbell


Early-bird:  SIG CR Members $150, Members $160, Non-members $175
Regular:  SIG CR Members $165, Members $175, Non-members $190