{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:34:31Z","timestamp":1754156071804,"version":"3.41.2"},"reference-count":28,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2016,8,15]],"date-time":"2016-08-15T00:00:00Z","timestamp":1471219200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJWIS"],"published-print":{"date-parts":[[2016,8,15]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>Linked data (LD) has promoted publishing information, and links published information. There are increasing number of LD datasets containing numerical data such as statistics. For this reason, analyzing numerical facts on LD has attracted attentions from diverse domains. This paper aims to support analytical processing for LD data.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>This paper proposes a framework called H-SPOOL which provides series of SPARQL (SPARQL Protocol and RDF Query Language) queries extracting objects and attributes from LD data sets, converts them into star\/snowflake schemas and materializes relevant triples as fact and dimension tables for online analytical processing (OLAP).<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>\nThe applicability of H-SPOOL is evaluated using exiting LD data sets on the Web, and H-SPOOL successfully processes the LD data sets to ETL (Extract, Transform, and Load) for OLAP. Besides, experiments show that H-SPOOL reduces the number of downloaded triples comparing with existing approach.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>H-SPOOL is the first work for extracting OLAP-related information from SPARQL endpoints, and H-SPOOL drastically reduces the amount of downloaded triples.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ijwis-03-2016-0014","type":"journal-article","created":{"date-parts":[[2016,8,16]],"date-time":"2016-08-16T05:38:07Z","timestamp":1471325887000},"page":"359-378","source":"Crossref","is-referenced-by-count":3,"title":["H-SPOOL"],"prefix":"10.1108","volume":"12","author":[{"given":"Takahiro","family":"Komamizu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Toshiyuki","family":"Amagasa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroyuki","family":"Kitagawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"issue":"2","key":"key2020121321392145200_ref007","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1109\/TKDE.2014.2330822","article-title":"Using semantic web technologies for exploratory OLAP: a survey","volume":"27","year":"2015","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"3","key":"key2020121321392145200_ref008","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/jswis.2009081901","article-title":"Linked data \u2013 the story so far","volume":"5","year":"2009","journal-title":"Journal on Semantic Web and Information Systems"},{"key":"key2020121321392145200_ref009","first-page":"705","article-title":"Fast lowest common ancestor computations in dags","volume":"4698","year":"2007","journal-title":"In ESA"},{"first-page":"45","article-title":"Modeling and querying data warehouses on the semantic web using QB4OLAP","year":"2014","key":"key2020121321392145200_ref012"},{"first-page":"469","article-title":"Enhancing OLAP analysis with web cubes","year":"2012","key":"key2020121321392145200_ref010"},{"year":"2012","key":"key2020121321392145200_ref011","article-title":"QB4OLAP: a vocabulary for OLAP cubes on the semantic web"},{"key":"key2020121321392145200_ref001","unstructured":"Fuseki: serving RDF data over HTTP (2016), available at: http:\/\/jena.apache.org\/documentation\/serving_data\/?"},{"key":"key2020121321392145200_ref013","first-page":"114","article-title":"Enabling real-time business intelligence","year":"2015","journal-title":"Towards Exploratory OLAP over Linked Open Data \u2013 A Case Study"},{"first-page":"111","article-title":"An ETL framework for online analytical processing of linked open data","year":"2013","key":"key2020121321392145200_ref014"},{"first-page":"33","article-title":"Transforming statistical linked data for use in OLAP systems","year":"2011","key":"key2020121321392145200_ref015"},{"first-page":"87","article-title":"Interacting with statistical linked data via OLAP operations","year":"2012","key":"key2020121321392145200_ref017"},{"first-page":"389","article-title":"OLAP4LD - 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