RML and FnO: Shaping DBpedia Declaratively

Abstract

Abstract. dbpedia data is largely generated from extracting and parsing the wikitext from the infoboxes of Wikipedia. This generation process is handled by the dbpedia Extraction Framework (dbpedia ef). This framework currently consists of data transformations, a series of custom hard-coded steps which parse the wikitext, and schema transformations, which model the resulting rdf data. Therefore, applying changes to the resulting rdf data needs both Semantic Web expertise and development within the dbpedia ef. As such, the current dbpedia data is being shaped by a small amount of core developers. However, by describing both schema and data transformations declaratively, we shape and generate dbpedia data using solely declarations, splitting the concerns between implementation and modeling. The parsing functions development is decoupled from the dbpedia ef, and other data transformation functions can easily be integrated during dbpedia data generation. This demo showcases an interactive Web application that allows non-technical users to (re-)shape the dbpedia data and use external data transformation functions, solely by editing a mapping document via html controls.

LinkedDataOps:quality oriented end-to-end geospatial linked data production governance

“…In contrast, there are not a large amount of dedicated geospatial data quality tools implemented per se, especially for Linked Data. Existing tools are focused on the traditional data and business products such as ArcGis, 13 GeoToolkit. 14 The tools which are employed in the OSi data pipeline are 1Spatial 1Integrate and Luzzu tools.…”

“…There are number of open research tools for geospatial data conversion from traditional data to Linked Data such as Geometry2RDF, 18 TripleGeo 19 [34], GeoTriples 20 [29] and Ontop-Spatial [3] which are used either to materialize the geospatial data or create an ontology-based database access (OBDA) over traditional data. Moreover, there are other tools using RML/R2RML approach to materialize the data such as RML+FnO [13], FunMap [26] or Morph-KGC [2]. However, in this study R2RML-F tool 21 of Debruyne et al was used to produce Linked Data which allows domain-specific data transformations -such as transforming geospatial coordinates [18].…”

ShExML: improving the usability of heterogeneous data mapping languages for first-time users

“…Transformations: The possibility of transforming the output to another value by means of a function is something very useful for different purposes when building a knowledge graph. Therefore, in YARRRML this is supported through the FnO mechanism (Meester et al, 2017) which offers a way to define functions inside mapping languages in a declarative fashion. SPARQL-Generate offers some functions for strings embedded inside the SPARQL binding functions mechanism; however, it is possible to extend the language through the SPARQL 1.1 extension mechanism.…”