@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix orcid: <https://orcid.org/> .
@prefix this: <http://purl.org/np/RA4fmbyks95hlE2HDLaNjETJ0ozGTQliA_cVuFpNGihS8> .
@prefix sub: <http://purl.org/np/RA4fmbyks95hlE2HDLaNjETJ0ozGTQliA_cVuFpNGihS8#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@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 "Our analysis of Linked Data quality issues focuses on DBpedia as a representative data set for the broader Web of Data due to the diversity of the types of er- rors exhibited and the vast domain and scope of the data set. In our previous work [44], we compiled a list of data quality dimensions (criteria) applica- ble to Linked Data quality assessment. Afterwards, we mapped these dimensions to DBpedia [43]. A sub-set of four dimensions of the original framework were found particularly relevant in this setting: Ac- curacy, Relevancy, Representational-Consistency and Interlinking. To provide a comprehensive analysis of DBpedia quality, we further divided these four cate- gories of problems into sub-categories. For the purpose of this paper, from these categories we chose the fol- lowing three triple-level quality issues.";
    a doco:Paragraph .
}

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

sub:pubinfo {
  this: dcterms:created "2019-11-10T12:34:11+01:00"^^xsd:dateTime;
    pav:createdBy orcid:0000-0002-7114-6459 .
}