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My little Linked Open Data Ogham Minion: Visualising graph data connections using SPARQL endpoints

Authors: Thiery, Florian;

My little Linked Open Data Ogham Minion: Visualising graph data connections using SPARQL endpoints

Abstract

In addition to relational data structures other data modelling structures such as graphs are entering archaeology. Modelling in graphs allows for adding semantic information to relations and creating interoperability using standards, e. g. the Resource Description Framework (RDF). This is a good requisite for creating interlinked RDF data; which is called Linked Open Data (LOD). LOD, published in community hubs, e.g. Wikidata or custom triplestores are published more and more in cultural heritage research. But there is a lack of user-friendly and easy to use Free/Libre Open Source Software (FOSS) tools for LOD technologies. In order to address this issue, the SPARQL Unicorn comes into play: a user-friendly tool series that was initiated in order to assist researchers who are working with Wikidata and other related Linked Data repositories. SPARQL Unicorn’s aim is to help researchers from the humanities or geospatial domain to use community data to make the data accessible to those without expertise in SPARQL or LOD. The SPARQL Unicorn principles were envisioned and are brought to life by the Research Squirrel Engineers network (Thiery et al. 2020), a group of LOD enthusiasts who aim to create tools for researchers without any prior knowledge of Semantic Web technologies. In our minion talk we will introduce a SPARQLing Unicorn minion that queries distributed SPARQL endpoints and visualises the data and their connections using JavaScript libraries as a map (Leaflet) and a graph (vis.js). This approach can then be transferred to specific use cases. For our talk we will be presenting the use case example of Celtic Ogham stones, a group of monoliths inscribed with the Ogham (ᚑᚌᚆᚐᚋ) script, erected in Ireland and the western part of Britain (Wales, Scotland, Cornwall, Devon, Isle of Man) between the 4th and 6th century. These stones contain several inscriptions which are an important source for archaic or proto-Irish language and society. The findspots are not well documented. Different sources show several ambiguous locations, which makes mapping challenging. The standard work on Ogham inscriptions is the Corpus Inscriptionum Insularum Celticarum (Macálister 1945), which indexes the stones in the widely used CIIC numbering scheme. Next to the Corpus Inscriptionum Insularum Celticarum (CIIC) catalogue, a number of print publications and online databases from different Ogham research projects exist; they are all using their own numbering systems and do not always reference each other bidirectionally. Ogi Ogham is a project that was created in 2019 by members of the Research Squirrel Network in order to create LOD from distributed sources and interlink them to create an Ogham knowledge graph in the Linked Open Data Cloud. The project is currently funded by the Wikimedia Deutschland Open Science Fellows 2020/2021 Program within the Irish ᚑᚌᚆᚐᚋ Stones in the Wikimedia Universe project. For the Squirrel Ogham projects, the CIIC, the Celtic Inscribed Stones Project (CISP) and the 3D Ogham Project are especially important. These distributed data sources are available but not published in a semantically modelled standardised format, e. g. RDF, and not interlinked with each other. This is where the Irish ᚑᚌᚆᚐᚋ Stones in the Wikimedia Universe project comes in. Within this project, the data will be imported into Wikidata, as well as transformed into RDF triples, according to a custom ontology (Thiery 2021), and stored in a custom triplestore. This minion talk focuses on a little web-based Ogham Minion, which visualises connections between distributed Ogham sources and different numbering systems as an interactive graph, as well as displaying them on an interactive map to show the distribution and different information on findspots.

Keywords

Wikidata, Ogham, Linked Data, Little Minions

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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