KMi professor Stefan Rueger gave the closing keynote of this year’s i-KNOW conference at Graz’s congress hall.
i-KNOW is the premier conference on knowledge management and knowledge technologies in Europe and has a tradition of bringing together more than 500 leading researchers and practitioners involved in knowledge management.
Rueger’s talk “Knowledge discovery in the web: potential, automation and limits” reflected on the value and potential of social networks, interlinked data, semantic web and data-mining. At the same time he elicited new research directions, which are only enabled by the sheer mass of data, sensors, facts, reports, opinions and inter-linkage of people.
Rueger presented the hypothesis that scale, linked open data, social networks, open educational resources and new modes of human information interactions provide for a rich and rewarding environment for knowledge discovery in the web. He looked at these ingredients in turn and mixed them to envisage killer applications: The combination of linked open data, open educational resources, learner networks such as SocialLearn, are potent ingredients for learning, teaching and competence building in a “e” type of university out of the box (the only missing elements being student administration, examination and accreditation). Another application of linked open data together with open algorithms is the truly reproducible science experiment, where labs share data and analysis for everyone to check with their own methods and data. Rueger also made the case for analysis with a view to automatically annotating documents for sensemaking and for citizen science, where social networks around nature observations contribute to extensive biodiversity surveys and beyond.
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