How to move from Relational to Linked Open Data 5 Star – a numismatic example
Channel: Recording Archaeology
Date: 30/05/2015

Authors: Karsten Tolle, David Wigg-Wolf
Abstract: In our database solution Antike Fundmünzen Europa (AFE), where we record finds of ancient coins, we want to preserve as much information as possible. This also includes containments of possible coin types, or marking attributes of a coin as uncertain if the exact value can not be assured. As many others our backend-system is based on a traditional relational database (MySQL). In order to become a Linked Open Data 5 Star, we mapped our data to different ontologies from Nomisma.org, Dublin Core, SKOS and others. Besides providing these data to others, we also benefit from the new ability to view our relational data in a totally different way, by loading the data back to a graph database. We will present how we mapped our data based on an existing mapping language called D2RQ Mapping Language, without the need for changing the underlying database. In our case this was less problematic due to the fact that internally we had already set AFE up based on Nomisma.org thesauri. However, the thesaurus mapping can also be part of the mapping. With this mapping established, one can for example provide a SPARQL endpoint to others in order to allow them to access the data in an ontological way. However, for full interoperability there are still barriers that need to be overcome. Even if the same  vocabulary is used, different modelling approaches might hinder full interoperability – this will be the focus or our talk, explaining what we mean by this. This problem does of course not occur when the modelling is identical. We are currently planning to combine different databases instances that are all build on top of AFE (such as Germany and Poland, as well as Romania which is under construction) based on the same mapping in order to demonstrate the potential. We will further report about benefits we see from the ability to use graph visualizations of the data. We will report on our experiences with AllegroGraph as a graph database allowing reasoning for some standard properties, and Gruff as a visualization and query interface on top of it.