FAIRification Tool for graph-based modelling of vagueness in research data

FAIRification Tool for graph-based modeling of vagueness in research data

Responsible persons: Florian Thiery (LEIZA) / Allard W. Mees (LEIZA)

With the Academic Meta Tool (AMT), vagueness in RDF graph data can be modeled and automatic conclusions, e.g. on relative temporal sequences, can be drawn with the help of reasoning. The results can be made available as linked open data in RDF format as FAIR data and visualized in graphs.In recent years, graph databases and so-called triple stores have been increasingly used to answer research questions in the humanities.In these cases, the relevant data is modeled as a graph or as a collection of triples. Compared to relational databases, in which table structures play a role, this has the advantage that networks and connections to the Semantic Web and the Linked Data Cloud can be expressed much more easily.In these networks, connections are represented as relationships between entities.

For example, a trading relationship “trades with” between person A and person B can be modeled. Such a link between two entities via a relationship thus also corresponds to the basic concept of the triple structure of linked data.Both the two entities (person A and B) and the relationship (“trades with”) are stored as terms with a unique address (URI) on the WWW. This enables software to interpret the triple, making it machine-readable. A problem that frequently arises is the vagueness of edges or statements. This means that a connection between two nodes or resources only exists to a certain degree.This should not be confused with uncertainty, where it is unknown whether the connection exists at all.

A problem that frequently arises is the vagueness of edges or statements. This means that a connection between two nodes or resources only exists to a certain degree.This should not be confused with uncertainty, where it is unknown whether the connection exists at all.

In the above example, this would mean that the trade relationship was not particularly intensive, i.e. it was more a case of sporadic trade contacts. If there are many friendship relationships in a dataset, but the intensity of the relationship varies, you would either have to link them all in the same way or invent many different links that essentially mean the same thing.The Academic Meta Tool (AMT) addresses this problem and offers the possibility of inserting edge weights (“degree of connection”) and making inferences based on them, taking vagueness into account.

The AMT has already been tested and used in many different contexts by NFDI4Objects:

The tool is being further developed as part of the work program. It is available as a so-called Playground.

The source code is available on GitHub. The ontology is published on Zenodo.

The AMT was developed in 2017 as a cooperation project of the Mainz Center for Digitality in the Humanities and Cultural Studies (mainzed) as a research tool by Martin Unold (i3mainz - Institute for Spatial Information and Measurement Technology at the Department of Technology at Mainz University of Applied Sciences) and Florian Thiery (former i3mainz and Roman-Germanic Central Museum). AMT is now being further developed by Allard Mees and Florian Thiery at the Leibniz Center for Archaeology (LEIZA) in the work area “Scientific IT, digital platforms and tools”, as well as in the permanent research area “Explorative research and method development” as part of the field of action “Digital methodology in archaeoinformatics” in the projects “Semantic modeling and knowledge graphs” and NFDI4Objects.