Data Science


Data and computer science are an essential component in cultural heritage research in order to make sense of the vast amounts of data, often heterogeneous in nature, collected in research projects.


This research area covers novel techniques for data collection, data-fusion, analysis, simulation, and visualization, or a combination of these techniques. The aim is is to facilitate date processing and make the date easier to use or interpret. Data science can either be helpful to process the vast amounts of data from the analysis of single objects, but it can also be used to analyse large data sets comprising multiple objects. Often, data sets have been assembled under very diverse conditions using various instruments, making direct comparisons difficult. Data science can investigate novel ways in which such data sets can be made comparable, and thus create more possibilities for national and international comparisons of available data sets. It can also discern new patterns in data sets that cannot be observed by individual humans. Data science can also aid in reducing the subjectivity of various types of knowledge used for conservation decisions and to help transform it from case-based observations to more general, objectified data.

Prof. dr. Rob Erdmann

Research lead