The Faculty of Archaeology, Leiden University, seeks to appoint a 0,8 fte Postdoctoral Researcher for the duration of 3 years to carry out research at the intersection of Knowledge Representation, Linked Data, and Museum Collection Data. The successful candidate will join the Department of Heritage and Society.
Research will be supervised by Dr. Martin E. Berger (PI), Assistant Professor at the Faculty of Archaeology of Leiden University, as part of the ERC-funded Starting
Grant project BECACO – Between Canon and Coincidence: using data-driven approaches to understand Art Worlds.
The BECACO project will develop a novel interdisciplinary framework for studying the provenance of ethnographic and archaeological collections. The aim of the project is to create a diachronic, international, and cross-institutional understanding of the collecting of Indigenous Latin American Material in Europe between 1850 and 2000. Central to the project’s approach is a mobilization of the potential of data-driven methodologies (e.g. Linked Data, network analysis, data mining) in order to better understand the appearance and disappearance of collecting networks over time and space. The primary role of the postdoctoral research within the project will be to assess the promises and limitations of using Knowledge Graphs and embedding models to study large corpuses of museum collection data, in order to uncover hidden knowledge and study collecting processes at an unprecedented scale.
The postdoctoral researcher will work with domain experts in collections history and museum studies to develop a Linked Open Knowledge Graph out of collections data supplied by 12 museums across 9 countries in Europe. The post-doc will be responsible for developing and maintaining the data infrastructure of the project, making sure the data adhere to FAIR standards. Research will result in a Linked Open Knowledge Graph that can be used by future researchers and expanded with data from other museums, as well as at least one peer-reviewed article on methodological issues. Key tasks
- Clean and structure the data supplied by museums, in collaboration with the BECACO project team
- Convert structured data into Linked Data/Knowledge Graph
- Create a transparent and explainable Embedding Model that can provide link prediction between actors, institutions, and communities
- Publish and present research in international conferences and journals, both independently and with team members;
- Contribute to the overall aims of the BECACO project.