Actors in Web ecosystems integrating data from multiple sources–such as in the Solid project or in thematic data spaces–must be able to express requirements over a combination of exchanged data and its associated context. Examples include assigning confidence to integrated data, tracking provenance, signing a specific set of statements, or the expression of policies for usage control. Despite earlier attempts, there is no general consensus on how to model such context associations, resulting in a lack of interoperability for exchanging combined context and data across actors. With this paper, we propose a pragmatic modeling approach for context associations, by referencing Blank Node Graphs, thereby enforcing a specific interpretation of the graph name and restricting its definition to a blank node to avoid accidental merging of graphs. We introduce the “RDF context associations” specification, which defines the data model and the interpretation. The demonstrator then showcases both the modeling of context information over given source data and the filtering of the resulting context associations using SPARQL.

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Demonstrating a Pragmatic Solution to Context Associations in RDF Using Blank Node Graphs

  • Ruben Dedecker,
  • Jos De Roo,
  • Beatriz Esteves,
  • Pieter Colpaert

摘要

Actors in Web ecosystems integrating data from multiple sources–such as in the Solid project or in thematic data spaces–must be able to express requirements over a combination of exchanged data and its associated context. Examples include assigning confidence to integrated data, tracking provenance, signing a specific set of statements, or the expression of policies for usage control. Despite earlier attempts, there is no general consensus on how to model such context associations, resulting in a lack of interoperability for exchanging combined context and data across actors. With this paper, we propose a pragmatic modeling approach for context associations, by referencing Blank Node Graphs, thereby enforcing a specific interpretation of the graph name and restricting its definition to a blank node to avoid accidental merging of graphs. We introduce the “RDF context associations” specification, which defines the data model and the interpretation. The demonstrator then showcases both the modeling of context information over given source data and the filtering of the resulting context associations using SPARQL.