1. How can CROC be useful?

    CROC may provide interoperability between different systems. Classified data, provided by RDF (and OWL), XML or relational databases, can be represented using the lexical representations of CROC. (Classifications are in fact based on concepts; entities in classifications correspond to concepts in the conceptuology.)

  2. What is the use of such representations using concepts?

    First, systems using CROC can interoperate and share any information using such representations. Second, human user interfaces may be simplified because users do not need to understand the underlying classification of the system. Third, a system may use different classifications internally and still reason in a unified way using the conceptuology.

  3. How intelligent can we make a conceptuology?

    Reidentification has been recognized as the most central job of cognition [Millikan, 2000]. Representations based on concepts are therefore quite important for the development of intelligent systems.

    CROC covers the whole scope of concepts (happening concepts, subject concepts, property concepts). It uses natural-language like representations (which are richer than the languages of propositional or predicate logic). Reasoning may therefore extend to, e.g., temporal reasoning and higher order reasoning (reasoning about other reasoning systems).

    Reasoning using natural language seems to have no restrictions qua intelligence. In philosophy, the dependence between language (representation) and thought has been regarded as going both ways.