NFDI4Objects Service Type
  • Software Application Services (SAS)
  • Interoperability Services (IntS)
NFDI Service Category
  • tools/Applications
Task Areas
Trails

Metadata as .ttl

Verantwortliche: Florian Thiery (LEIZA) / Karsten Tolle (Uni Frankfurt) / Lutz Schubert (CAA-DE)

The Research Software Engineering (RSE) Toolkits for Knowledge Modelling describe a collection of RSE Research/FAIRification Tools, whitepapers such as Good Practices, Recommendations or Community Standards, training material, bluepapers such as format descriptions, implementation guidelines or ontologies, including the subject of fuzzy and wobbly semantics. This service comprises RSE Tools maintained by NFDI4Objects Co-Applicants and Participants and FLOSS entities developed and maintained by a community. These knowledge modelling tools include, e.g.,

  • The Alligator (Allen Transformer) research tool calculates relative time sequences based on correspondence analyses using Allen’s Interval Algebra. The results are available as Linked Open Data in RDF format as FAIR data and visualised with time bars and graphs.
  • Based on the correspondence analysis results, the TiGeR (Time Geospatial RDF) research Tool implements the TiGeR method. It uses the normalised first CA dimension and converts it into gradient colours using a JavaScript library called rainbow.js.
  • The Academic Meta Tool can be used to model vagueness in graph data and draw automatic conclusions, e.g. on relative temporal sequences, with the help of “reasoning”. The results are available as Linked Open Data in RDF format as FAIR data and visualised in graphs.
  • The LEIZA’s LEIZA Archaeological Data Processing Web Service includes self-developed solutions for special archaeological problems based on archaeological expertise and existing RSE standards.
  • RDFier (open source tool based on a Master Thesis at Uni Frankfurt) that can also be used online. The tool allows the generation of RDF based on CSV input files and supports different existing modelling alternatives for uncertain data.
  • Guidelines for Artificial Intelligence (AI) in Archaeology: Developments in the field of AI are rapid and offer many opportunities but also pitfalls. Guidelines help to avoid those pitfalls. For example, this guide collects the lessons learned in the ClaReNet project regarding the data basis and acquisition, to what extent difficulties can arise, and possible solutions. At the same time, the topic of explainability is addressed. Another important aspect is the communication between the IT team and the domain experts.
  • Famous tools from the broader community that are also developed and maintained by the community themself are, e.g., QGIS Plugins such as the SPARQLing Unicorn QGIS Plugin or the CRS Guesser by the Research Squirrel Engineers Network. This service collects these RSE toolkits and provides information on how and in which process step they can be used. It is supported by the Community Cluster Research Software Engineering. It is in dialogue with the humanities MoU consortia NFDI4Culture, NFDI4Memory and Text+, as well as the Section Common Infrastructures and Working Group Research Software Engineering within the NFDI e.V. This service is being maintained by LEIZA (Florian Thiery), the University of Frankfurt (Karsten Tolle) and the Computer Applications and Quantitative Methods in Archaeology (CAA) Section Germany (CAA-DE) (Lutz Schubert).