{"id":14879,"date":"2026-06-04T18:38:46","date_gmt":"2026-06-04T16:38:46","guid":{"rendered":"https:\/\/www.ibisc.univ-evry.fr\/?page_id=14879"},"modified":"2026-06-06T03:46:18","modified_gmt":"2026-06-06T01:46:18","slug":"advance-2026-technical-session-2-full-papers-fp2-1","status":"publish","type":"page","link":"https:\/\/www.ibisc.univ-evry.fr\/en\/advance-2026-technical-session-2-full-papers-fp2-1\/","title":{"rendered":"ADVANCE 2026 \u2013 Technical Session 2 (Full Papers) \u2013 FP2.1"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\"  style='background-color: rgba(255,255,255,0);background-position: center center;background-repeat: no-repeat;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;'><div class=\"fusion-builder-row fusion-row \"><div  class=\"fusion-layout-column fusion_builder_column fusion_builder_column_1_4  fusion-one-fourth fusion-column-first 1_4\"  style='margin-top:0px;margin-bottom:20px;width:25%;width:calc(25% - ( ( 4% ) * 0.25 ) );margin-right: 4%;'>\n\t\t\t\t\t<div class=\"fusion-column-wrapper\" style=\"padding: 0px 0px 0px 0px;background-position:left top;background-repeat:no-repeat;-webkit-background-size:cover;-moz-background-size:cover;-o-background-size:cover;background-size:cover;\"  data-bg-url=\"\">\n\t\t\t\t\t\t<div class=\"fusion-text\"><p style=\"text-align: right;\"><span style=\"color: #ff0000;\"><strong>Upload PDF<\/strong><\/span><\/p>\n<\/div><div class=\"fusion-sep-clear\"><\/div><div class=\"fusion-separator fusion-full-width-sep sep-single sep-solid\" style=\"border-color:#e0dede;border-top-width:1px;margin-left: auto;margin-right: auto;margin-top:;\"><\/div><div class=\"fusion-text\"><p><a href=\"https:\/\/lrsm.ibisc.univ-evry.fr\/Advance2026\/index.html\"><strong>ADVANCE 2026 Web site<\/strong><\/a><\/p>\n<\/div><div class=\"fusion-text\"><p><a href=\"https:\/\/www.ibisc.univ-evry.fr\/en\/advance-2026-13th-international-workshop-on-advances-in-ict-infrastructures-and-services\/\"><strong>ADVANCE 2026 Proceedings<\/strong><\/a><\/p>\n<\/div><div class=\"fusion-clearfix\"><\/div>\n\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div><div  class=\"fusion-layout-column fusion_builder_column fusion_builder_column_3_4  fusion-three-fourth fusion-column-last 3_4\"  style='margin-top:0px;margin-bottom:20px;width:75%;width:calc(75% - ( ( 4% ) * 0.75 ) );'>\n\t\t\t\t\t<div class=\"fusion-column-wrapper\" style=\"padding: 0px 0px 0px 0px;background-position:left top;background-repeat:no-repeat;-webkit-background-size:cover;-moz-background-size:cover;-o-background-size:cover;background-size:cover;\"  data-bg-url=\"\">\n\t\t\t\t\t\t<div class=\"fusion-text\"><h2 style=\"text-align: center;\"><strong>Towards Automatic Discovery of Correlations between Unstructured and Structured Data in Automotive Data Lakes<\/strong><\/h2>\n<p style=\"text-align: center;\">Rodrigo Gon\u00e7alves<sup>1<\/sup>, Jos\u00e9 Luis Conradi Hoffmann<sup>1<\/sup>, Ant\u00f4nio Augusto Fr\u00f6hlich<sup>1<\/sup> and Jo\u00e3o R. Campos<sup>2<\/sup><\/p>\n<p style=\"text-align: center;\"><sup>1<\/sup> Software-Hardware Integration Lab, Federal University of Santa Catarina, Florian\u00f3polis, SC, Brasil (Emails: <a href=\"mailto:goncalves@lisha.ufsc.br\">goncalves@lisha.ufsc.br<\/a>, <a href=\"mailto:hoffmann@lisha.ufsc.br\">hoffmann@lisha.ufsc.br<\/a>, <a href=\"mailto:guto@lisha.ufsc.br\">guto@lisha.ufsc.br<\/a>)<\/p>\n<p style=\"text-align: center;\"><sup>2<\/sup> CISUC\/LASI, DEI, University of Coimbra, Coimbra, Portugal (Email: <a href=\"mailto:jrcampos@dei.uc.pt\">jrcampos@dei.uc.pt<\/a>)<\/p>\n<p>DOI: <a href=\"https:\/\/doi.org\/10.48545\/advance2026-fullpapers-2_1\">https:\/\/doi.org\/10.48545\/advance2026-fullpapers-2_1<\/a><br \/>\n<strong>Abstract<\/strong><br \/>\nData Lakes have emerged as an architectural approach for integrating data from multiple heterogeneous sources into large-scale data processing pipelines. A key challenge lies in correlating structured, semi-structured, and unstructured data through metadata in order to transform raw data into actionable information and support automated decision-making at scale. This research paper builds upon SmartData, a self-contained data construct originally designed for structured data, to propose a Data Lake infrastructure that enables efficient integration across diverse data modalities. We introduce SmartDataContext, an intermediary semi-structured representation that encapsulates SmartData Models and supports time-series tagging. Additionally, we propose a SmartTagging framework that extracts semantic information from unstructured data and applies text relationship analysis to automatically discover correlations. The proposed approach is evaluated through an automotive case study, demonstrating the identification of relationships between sections of standards documents in PDF format and corresponding SmartDataContexts. From a data management viewpoint, SmartTagging acts as an \u201cactive metadata\u201d mechanism for automotive data lakes, allowing for automatic and continuous discovery of tags from contextual artifacts and external standards (here, ETSI C-ITS documents), thus, avoiding manual catalogs or schema-on-read and the creation of data-swamps.<br \/>\n<strong>Keywords<\/strong><br \/>\nSmartData, Automotive Systems, Cloud, Internet of Things<\/p>\n<\/div><div class=\"fusion-clearfix\"><\/div>\n\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":12,"featured_media":14872,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"class_list":["post-14879","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/pages\/14879"}],"collection":[{"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/comments?post=14879"}],"version-history":[{"count":3,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/pages\/14879\/revisions"}],"predecessor-version":[{"id":14946,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/pages\/14879\/revisions\/14946"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/media\/14872"}],"wp:attachment":[{"href":"https:\/\/www.ibisc.univ-evry.fr\/en\/wp-json\/wp\/v2\/media?parent=14879"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}