More than 500 dates have been recorded for the prehistory of northeast Iberian peninsula. Such data have been  stored in a database which can be accessible though internet (http://www.mac.cat/eng/Recerca/Catalunya-C14). Users can download the data and query the database for relevant information on the chronology of different archaeological contexts: from Late Paleolithic to the first colonial foundations in Western Mediterranean, and distinguishing the classical key artifacts as: cardial ware (neolithic), bell beaker (calcolithic), megalithism, bronze age metallurgical types, urnfield, etc.

Although very usable as it is, the database can appear as too traditional, reduced to passive queries. In this paper we will deal with theoretical and methodological questions about how archaeological and chronological data can be transformed into knowledge. That means that the user does not ask for specific bits of data knowing all its characteristics, but the system guide the user to define the chronology of a particular context based on similarity calculations between artifacts, spatial relationships between them, and Bayesian associations between stratigraphical order, radiometric information and archaeological formation processes.

The purpose of the paper is basically theoretical, suggesting ways of enhancing ordered lists of data in order to be able to build archaeological knowledge. In too many occasions, archaeological explanation is reduced to the presentation of data. We develop new methods of relating different sources of information based on artificial intelligence to make this possible.

We present the general architecture of an expert system to help users to select the appropriate archaeological information and calculate posterior probabilities for  chronological estimates based on contextual data.

Our project addresses the concept of Telearchaeology, or “archaeology accessible on distance” as a necessary requirement to move from archaeological heritage reduced to the state of “mute stones” to a comprehensive knowledge(s) base. In the information-saturated era new methods of efficient and meaningful retrieval of relevant information and knowledge are urgent.