Japan Search

Trying grlc (git repository linked data API constructor)

Overview The GitHub repository for grlc is as follows. https://github.com/CLARIAH/grlc It is described as follows. grlc, the git repository linked data API constructor, automatically builds Web APIs using shared SPARQL queries. I tried out this tool, so here are my notes. The API endpoint created targeting the Japan Search SPARQL Endpoint is as follows. https://grlc.io/api-git/nakamura196/grlc-jps Background While researching Odeuropa, I found this tool mentioned on the following page. https://odeuropa.eu/nosebooks/ ...

July 24, 2025 · Updated: July 24, 2025 · 2 min · Nakamura

Applied Examples of Data Description Using Linked Data

Overview I have written the following articles related to RDF. I tried visualizing these together, so here are my notes. Data The following data was used this time. I described information such as: a person named “Satoru Nakamura (0000-0001-8245-7925)” is interested in “Thirty-Six Views of Mount Fuji: Fine Wind, Clear Morning (cobas-166407)” held by the Tokyo National Museum, and its creator is “Katsushika Hokusai.” The TTL description is as follows. ...

June 23, 2024 · Updated: June 23, 2024 · 3 min · Nakamura

Prototyping entity-lookup Using the Japan Search Utilization Schema

Overview This is a continuation of the following article. I will prototype a package that performs CWRC entity-lookup using the Japan Search utilization schema. Demo You can try it on the following page. https://nakamura196.github.io/nuxt3-demo/entity-lookup/ Entity-lookup is performed against JPS, Wikidata, and VIAF for each type such as Person, Place, and Organization. Library It is published at the following location. https://github.com/nakamura196/jps-entity-lookup Based on the repository https://github.com/cwrc/wikidata-entity-lookup already published by CWRC, I mainly modified the following file to match the Japan Search utilization schema. ...

May 17, 2024 · Updated: May 17, 2024 · 1 min · Nakamura

Counting Triples in an RDF Store 2: Co-occurrence Frequency

Overview I had the opportunity to count co-occurrence frequencies for RDF triples, so here are my notes. Following the previous article, I will again use the Japan Search RDF store as an example. Example 1 The following query counts the number of triples among sword-type instances that share a common creator (schema:creator). The filter avoids counting identical instances and prevents duplicate counting. select (count(*) as ?count) where { ?entity1 a type:刀剣; schema:creator ?value . ?entity2 a type:刀剣; schema:creator ?value . FILTER(?entity1 != ?entity2 && ?entity1 < ?entity2) } https://jpsearch.go.jp/rdf/sparql/easy/?query=select+(count(*)+as+%3Fcount)+where+{ ++%3Fentity1+a+type%3A刀剣%3B +++++++++++++schema%3Acreator+%3Fvalue+. ++%3Fentity2+a+type%3A刀剣%3B +++++++++++++schema%3Acreator+%3Fvalue+. ++FILTER(%3Fentity1+!%3D+%3Fentity2+%26%26+%3Fentity1+<+%3Fentity2) } ...

May 8, 2024 · Updated: May 8, 2024 · 1 min · Nakamura

Using the Japan Search SPARQL Endpoint with Yasgui

Overview Yasgui (Yet Another Sparql GUI) provides various advanced features for creating, sharing, and visualizing SPARQL queries and their results. https://github.com/TriplyDB/Yasgui This time, I attempt various visualizations using the Japan Search SPARQL endpoint with Yasgui. Results Table Display I visualize the number of items per dataset. First, here is a standard table display. Result Filtering and sorting of results is also possible. Chart Using the “Chart” tab, I attempt a chart display of the same results. ...

November 28, 2022 · Updated: November 28, 2022 · 1 min · Nakamura