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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (12): 89-97    DOI: 10.11925/infotech.2096-3467.2018.0423
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Converting STKOS Metathesaurus to RDF Triples with R2RML
Wang Ying1, Wu Sizhu2()
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China
2Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing 100020, China
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[Objective] This paper aims to convert STKOS Metathesaurus from records of relational database to RDF triples. [Methods] First, we defined the semantic schema of the STKOS based on their storage features and data characteristics. Then, we mapped the scientific terms, standard concepts, categories, as well as source concepts and terms with the help of R2RML. Finally, we converted the documents stored in relational database to RDF datasets with the R2RML parser. [Results] The proposed method could process STKOS metathesaurus automatically and generated 190 million RDF triples. All new records were stored in the Virtuoso database and could be queried with SPARQL. [Limitations] Predicates in the R2RML lacks flexibily, therefore, more complex data sets need to be splited and transformed first. [Conclusions] The proposed model shed light on future research on converting other relational database records or thesaurus to RDF datasets.

Key wordsR2RML      STKOS Metathesaurus      RDF     
Received: 20 April 2018      Published: 16 January 2019
ZTFLH:  TP393  

Cite this article:

Wang Ying,Wu Sizhu. Converting STKOS Metathesaurus to RDF Triples with R2RML. Data Analysis and Knowledge Discovery, 2018, 2(12): 89-97.

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数据表 字段 logicalTable rr:subjectMap rr:predicate rr:objectMap
stkos_concept AUI [rr:tableName “stkos_concept”] [rr:template “
rr:class stkos:concept;]
[rr:column “http://www.nstl.{AUI}”]
TUI stkos:LinktoCategory
[rr:column “http://www.nstl.{TUI}”]
stkos_concept_def DEF [rr:sqlQuery “““select CUI,
DEF, ISPREF from stkos_
concept_def where ISPREF=’
YES’ “““]
[rr:template “
[rr:column “DEF”]
stkos_concept_def DEF [rr:sqlQuery “““ select CUI,
DEF, ISPREF from stkos_
concept_def where ISPREF=’
NO’ “““]
[rr:template “
iso25964:Definition [rr:column “DEF”]
数据表 字段 logicalTable rr:subjectMap rr:predicate rr:objectMap
stkos_category LABEL [rr:tableName “stkos_category”] [rr:template “
rr:class stkos:categoryClass;]
skos:prefLabel [rr:column “LABEL”; rr:language “zh”]
LABEL_T skos:altLabel [rr:column “LABEL_T”; rr:language “en”]
CSAB_ID skos:inScheme [rr:column “ thesaurus/{CSAB_ID}”]
PTUI skos:broader [rr:column “ categoryClass/{PTUI}”]
数据表 字段 logicalTable rr:subjectMap rr:predicate rr:objectMap
stkos_atom LABEL [rr:sqlQuery “““ select LABEL,
[rr:template “
term/{SAUI}”; rr:class stkos:
iso25964:lexicalValue [rr:column “LABEL”; rr:language “en”]
SAB_ID skos:inScheme [rr:column “
stkos_attribute ID [rr:sqlQuery “““select ID, SAUID,
STYPE, SAB_ID from stkos_attribute
where STYPE=’TERM “““];
[rr:template “http://www.nstl.{SA
UID}”; ]
stkos: hasAttribute [rr:column “
ATN_C [rr:sqlQuery “““ select ID, ATN_C,
AN, ATN_S, ATV from
stkos_attribute “““]
[rr:template “
attribute_{ID}”; rr:class
stkos: attribute;]
stkos: ATN_C [rr:column “ATN_C”]
ATN stkos: ATN [rr:column “ATN”]
ATN_S stkos: ATN_S [rr:column “ATN_S”]
ATV stkos: ATV [rr:column “ATV”]
stkos_hierarchies PSCUI [rr:sqlQuery “““ select ID, SCUI,
PSCUI from stkos_hierarchies “““]
[rr:template “
rr:class stkos: sourceConcept;];
skos: broader [rr:column “{PSCUI}”]
stkos_relationship SACID2 [rr:sqlQuery “““ select SACID1,
stkos_relationship where STYPE1=’
TERM’ and STYPE2=’ TERM’ and
REL=’用’ “““];
[rr:template “
stkos: rel/used [rr:column “{SACID2}”]
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