A Computational Framework for Organizing and Querying Cultural Heritage Archives

Now that within the humanities more and more data sources have been created, a new opportunity is within reach: the searching of patterns spanning across data sources from archives, museums, and other cultural heritage institutes. These institutes adopt various digitization strategies based on differences in selection procedures. This results in heterogeneous data sources with a huge impact on the accessibility and interoperability of data within and between these distributed collections. We identify three interrelated challenges that researchers may encounter when querying such distributed data sources, namely query formulation, source selection, and alignment of data sources. We present a multi agent architecture to overcome these challenges and discuss a prototype implementation of the architecture by developing and integrating various technologies. In order to measure and validate the performance of integrated technologies that meet these three interrelated challenges, we propose a methodology for setting up and conducting experiments. We take an existing data source for which we can establish a baseline query result, against which we measure the precision and recall performance, and create various sets of data sources with realistic characteristics. We report on the results of a number of experiments that show the performance of the developed and integrated technologies.