We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.

In this paper we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge Processing. Conceptual Knowledge Processing is based on the mathematical theory of Formal Concept Analysis which has become a successful theory for data analysis during the last two decades. CKDD aims to support a human-centered process of discovering knowledge from data by visualizing and analyzing the conceptual structure of the data. We dicuss how the management system TOSCANA for conceptual information systems supports CKDD, and illustrate it by two applications in database marketing and flight movement analysis. Finally, we present a new tool for conceptual deviation discovery, Chianti.