Traverse relation

Description

Given a Predicate or explicit Edges, traverses the graph from a set of subjects to a set of objects (Forward), or from a set of objects to a set of subjects (Backward). The same predicate/edges can be traversed multiple times (Minimum / Maximum number of steps can be specified). When multiple steps are performed, the result always includes the shortest path from the subjects in input to those reachable within the given Minimum / Maximum number of steps

Input

  • SOURCE [OBJ]: a list of objects

  • Edges [OBJ,OBJ] (optional): an explicit list of edges to traverse, in the form (subject,object)`

Output

  • FROMTO [OBJ,OBJ]: a pair representing the “from” and the “to” in the process of traversing a graph relation

  • FROM [OBJ]: the “from” column of FROMTO output. FROM objects always come from SOURCE.

  • TO [OBJ]: the “to” column of FROMTO output

Parameters

  • Predicate (unless input Edges is connected): the predicate of a graph triple (subject,predicate,object)

  • Use sub-predicates (unless input Edges is connected): when set to true, the values of all sub-predicates are also included. Sub-predicates can be defined in the data with the rdfs:subPropertyOf relation.

  • Direction: the direction to use when traversing the relation with the given Predicate and SOURCE

    • Forward: (FROM = SOURCE, Predicate, TO = ?)

    • Backward: (TO = ?, Predicate, FROM = SOURCE)

    • Either: the result contains the union of Forward and Backward results

  • Minimum number of steps: Only include results reachable in a given minimum number os steps. Setting this to 0 includes all the SOURCE nodes in the result.

  • Maximum number of steps: Only include results reachable in a given maximum number os steps.

  • Step weight: [0..1]. Weight applied at every step. When < 1, further steps are progressively penalised.

  • Normalise over entire graph. Use false (default) when data SOURCE is representative enough:

    • false: Score normalisation only considers the data in SOURCE to normalise against

    • true: Score normalisation considers all data in the dataset containing SOURCE to normalise against

Output scores can be aggregated and/or normalised.