Topic Maps are representational models of knowledge that take advantage of features and advances in previous methods such as thesaurus, glossaries, data bases, and conceptual maps. Topic Maps normalize the elements and notation used to structure information through the design and development of networks semantic links that connect several informational resources.
In spite the fact that Topic Maps were originally created to handle the construction of indexes, content tables, and thesaurus, now they are employed in different domains. For instance, and along with the Resource Description Framework (RDF), they can provide the sound foundations for the so-called semantic Web, thanks to their functionalities for the representation of information stored in relational databases. Another important application is the use of Topic Maps in the representation of complex systems through the marking of the relationships among the different agents and elements that give rise to specific complex systems. Topic Maps have a clear advantage over systems such as databases, due to the fact that whereas relations are represented in databases as “objects of information”, Topic Maps allow the association of these objects to both the concepts and resources under which they are created.Topic Maps are based on the representation of the concepts in a specific domain of reality (e.g., 17th-century art works, or Toronto’s cultural events), the different cases relevant to the domain and concepts (clusters of informational objects around those concepts), the associations among them and the set of available external resources of information that are relevant for the map that is being built. Topic Maps are powerful and flexible tool that can be applied to a wide range of domain and purposes, from the mapping of semantic networks associated to knowledge areas (e.g., the baroque culture, Canadian contemporary culture) to the structure and dynamic representation of informational networks based on Internet, social networks, or ontologies.
Our research team has been studying the field of Topic Maps software tools for a while and has pioneered the use and application of these tools to the study of cultural phenomena. In particular, the team has been using and adapting Wandora (a distributed under GNU PL) to the study of the evolution of the baroque system of culture. Wandora is a general purpose knowledge extraction, management, and publishing environment based on Topic Maps. By using Wandora and developing the ability to adapt the software to cultural, textual, and social analysis we are able to extract information from extremely complex cultural settings (by temporal frameworks and geographic areas) and represent it taking into account social relations, different cultural and artistic domains, objects and actors, and even semantic representations of the set of metaphors that the cultural system uses to represent the world. Once the researcher introduces an element of evolution to the emerging picture, she is able to track the survival and adaptation of cultural units over time, the conceptual maps associated to the formation and interpretation of the founding literary texts of cultures, or the connections between social aspects and artistic production in different societies.