1) The document discusses using semantic web and linked data technologies to help assess the quality of scientific output by answering questions about workshops, conferences, publications, and data. 2) It proposes connecting bibliographic metadata, citations, full text, social networks and research data using initiatives like schema.org to provide machine support for quality assessment. 3) The goal is to provide complementary metrics to human peer review and impact factors by enabling multidimensional, context-sensitive analysis of trends, topics, citations and more.