{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T18:58:06Z","timestamp":1768071486780,"version":"3.49.0"},"reference-count":6,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,2,18]],"date-time":"2019-02-18T00:00:00Z","timestamp":1550448000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>In recent years, a great deal of interest has been shown toward big data. Much of the work on big data has focused on volume and velocity in order to consider dataset size. Indeed, the problems of variety, velocity, and veracity are equally important in dealing with the heterogeneity, diversity, and complexity of data, where semantic technologies can be explored to deal with these issues. This Special Issue aims at discussing emerging approaches from academic and industrial stakeholders for disseminating innovative solutions that explore how big data can leverage semantics, for example, by examining the challenges and opportunities arising from adapting and transferring semantic technologies to the big data context.<\/jats:p>","DOI":"10.3390\/info10020068","type":"journal-article","created":{"date-parts":[[2019,2,19]],"date-time":"2019-02-19T04:08:20Z","timestamp":1550549300000},"page":"68","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Foreword to the Special Issue: \u201cSemantics for Big Data Integration\u201d"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6616-1753","authenticated-orcid":false,"given":"Domenico","family":"Beneventano","sequence":"first","affiliation":[{"name":"Dipartimento di Ingegneria \"Enzo Ferrari\", Universit\u00e0 di Modena e Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9262-2939","authenticated-orcid":false,"given":"Maurizio","family":"Vincini","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria \"Enzo Ferrari\", Universit\u00e0 di Modena e Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,18]]},"reference":[{"key":"ref_1","first-page":"4","article-title":"Analyzing mappings and properties in Data Warehouse integration","volume":"7","author":"Vincini","year":"2017","journal-title":"Int. J. Eng. Technol. Innov."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Pasanisi, S., and Paiano, R. (2018). A Hybrid Information Mining Approach for Knowledge Discovery in Cardiovascular Disease (CVD). Information, 9.","DOI":"10.3390\/info9040090"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Mountantonakis, M., and Tzitzikas, Y. (2018). High Performance Methods for Linked Open Data Connectivity Analytics. Information, 9.","DOI":"10.3390\/info9060134"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Khouri, S., and Bellatreche, L. (2018). LOD for Data Warehouses: Managing the Ecosystem Co-Evolution. Information, 9.","DOI":"10.3390\/info9070174"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Ding, L., Sun, B., and Shi, P. (2018). Chinese Microblog Topic Detection through POS-Based Semantic Expansion. Information, 9.","DOI":"10.3390\/info9080203"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Michel, F., Faron Zucker, C., Gargominy, O., and Gandon, F. (2018). Integration of Web APIs and Linked Data Using SPARQL Micro-Services\u2014Application to Biodiversity Use Cases. Information, 9.","DOI":"10.20944\/preprints201811.0337.v1"}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/10\/2\/68\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:32:56Z","timestamp":1760185976000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/10\/2\/68"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,18]]},"references-count":6,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2019,2]]}},"alternative-id":["info10020068"],"URL":"https:\/\/doi.org\/10.3390\/info10020068","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,2,18]]}}}