Recommender-as-a-Service with Chatbot Guided Domain-science Knowledge Discovery in a Science Gateway
Scientists in disciplines such as neuroscience and bioinformatics are increasingly
relying on science gateways for experimentation on voluminous data, as well as
analysis and visualization in multiple perspectives. Though current science gateways
provide easy access to computing resources, datasets and tools specific to
the disciplines, scientists often use slow and tedious manual efforts to perform
knowledge discovery to accomplish their research/education tasks. Recommender
systems can provide expert guidance and can help them to navigate and discover relevant
publications, tools, data sets, or even automate cloud resource configurations
suitable for a given scientific task. To realize the potential of integration of recommenders
in science gateways in order to spur research productivity,we present a novel
“OnTimeRecommend" recommender system. The OnTimeRecommend comprises
of several integrated recommender modules implemented as microservices that can
be augmented to a science gateway in the form of a recommender-as-a-service. The
guidance for use of the recommender modules in a science gateway is aided by a chatbot
plug-in viz., Vidura Advisor. To validate our OnTimeRecommend, we integrate
and show benefits for both novice and expert users in domain-specific knowledge discovery within two exemplar science gateways, one in neuroscience (CyNeuro) and
the other in bioinformatics (KBCommons).
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