Änderungen an „FAIRification framework Alpaca“

https://www.leiza.de

Konsortial-Dienst

Software-Anwendungs-Dienste

Semantic Modelling, Linked Open Data, RDF graph data, rule-based Semantic Modelling

The FAIRification Framework Alpaca combines several related tools, creating a pipeline/workflow. The main components are the Academic Meta Tool (AMT) and the Alligator tool, which LEIZA has provided and maintained since 2019, as indicated in the NFDI4Objects project application. Data in Alligator is processed using algorithms based on statistical outputs, e.g., correspondence analysis results, to generate a small-scale knowledge graph. AMT uses this data to enable advanced rule-based semantic reasoning and to generate multiple graph outputs for processing in downstream research software or knowledge graph infrastructures.

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+The Academic Meta Tool (AMT) enables modelling of vagueness in RDF graph data and supports reasoning-based automated inference, e.g., for determining relative chronological sequences. The results can be made available as Linked Open Data (LOD) in RDF, adhering to FAIR principles, and visualised as graphs. In recent years, graph databases and triple stores have increasingly been used to address humanities research questions. In these cases, relevant data are modelled as graphs or as collections of triples. Compared to relational databases, which rely on table structures, this approach offers the advantage of more easily expressing networks and connections to the Semantic Web and LOD Cloud.

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+The Alligator tool transforms data using mathematical algorithms into a semantic graph structure. Examples are (a) using correspondence analysis to solve missing dating and create a relative chronology according to Allens’ interval algebra; (b) using quantitative confidence scoring via dispersion metrics to create implicit dating with uncertainty values; (c) use cases are e.g. based on 14C or dendrochronological analysis pipelines, in which handling of chronologies is pivotal, (d) using archaeometric / natural sciences analysis results is part of the functionalities portfolio to yield semantically modelled graphs.

Under development in TRAIL 2.8

MIT

https://tools.leiza.de/alligator; https://leiza-rse.github.io/amt-playground/

Department of Scientific IT, LEIZA

End of project

Under development in TRAIL 2.8

Under development in TRAIL 2.8

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N4O Homepage

Mees, A. W., & Thiery, F. (2026). Bridging Archaeological Samian Ware Data and the Knowledge Graph: Potentials and Challenges of Using Wikidata as a Linking Hub. Journal of Open Humanities Data, 12(16), 1–17. https://doi.org/10.5334/johd.427

+Thiery, F., & Mees, A. W. (2025). Dating Dated Sites: Using Correspondence Analysis to handle Chronologies as Graphs. Journal of Historical Network Research, 12(1). https://doi.org/10.25517/jhnr.v12i1.105

+Unold, M., Thiery, F., & Mees, A. (2019). Academic Meta Tool. Ein Web-Tool zur Modellierung von Vagheit. ZfdG - Zeitschrift Für Digitale Geisteswissenschaften, Die Modellierung des Zweifels – Schlüsselideen und-konzepte zur graphbasierten Modellierung von Unsicherheiten.(Sonderband 4). https://doi.org/10.17175/SB004_004

+Thiery, F., & Mees, A. (2023). Taming Ambiguity—Dealing with doubts in archaeological datasets using LOD. Proceedings of the Computer Applications and Quantitative Methods in Archeology, CAA 2018: Human History and Digital Future(2018). https://doi.org/10.15496/PUBLIKATION-87762

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Pre-Alpha | Erster Entwurf