@prefix this: <http://purl.org/np/RANmrsh6ayW2Zi_pM88i09a4ShFpG9_mswC9WESn6bJJg> .
@prefix sub: <http://purl.org/np/RANmrsh6ayW2Zi_pM88i09a4ShFpG9_mswC9WESn6bJJg#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix dc: <http://purl.org/dc/terms/> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix pav: <http://purl.org/pav/> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix doco: <http://purl.org/spar/doco/> .
@prefix c4o: <http://purl.org/spar/c4o/> .

sub:Head {
  this: np:hasAssertion sub:assertion;
    np:hasProvenance sub:provenance;
    np:hasPublicationInfo sub:pubinfo;
    a np:Nanopublication .
}

sub:assertion {
  sub:paragraph c4o:hasContent "SPARQL Inferencing Notation (SPIN) 22 is a W3C submission aiming at representing rules and constraints on Semantic Web models using SPARQL. The approach described in [13] advocates the use of SPARQL and SPIN for RDF data quality assessment. In a similar way, Fürber et al. [12] define a set of generic SPARQL queries to identify missing or illegal literal values and datatypes and functional dependency violations. Another related approach is the Pellet Integrity Constraint Validator ICV 23 . Pellet ICV translates OWL integrity constraints into SPARQL queries. A more lightweight RDF constraint syntax, decoupled from SPARQL, is offered from Shape Expressions (ShEx) [31] and IBM Resource Shapes 24 .";
    a doco:Paragraph .
}

sub:provenance {
  sub:assertion prov:hadPrimarySource <http://dx.doi.org/10.3233/SW-160239>;
    prov:wasAttributedTo <https://orcid.org/0000-0003-0530-4305> .
}

sub:pubinfo {
  this: dc:created "2019-09-20T18:05:11+01:00"^^xsd:dateTime;
    pav:createdBy <https://orcid.org/0000-0002-7114-6459> .
}