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
rocessing. Conceptual Knowledge
rocessing is based on the mathematical theory of Formal Concept
nalysis which has become a successful theory for data analysis during
he last two decades. CKDD aims to support a human-centered process
discovering knowledge from data by visualizing and analyzing
e conceptual structure of the data. We dicuss how the
nagement system TOSCANA for conceptual information systems
pports CKDD, and illustrate it by two applications in database
rketing and flight movement analysis. Finally, we present a
w tool for conceptual deviation discovery, Chianti.