{"id":1296,"date":"2022-05-12T13:19:13","date_gmt":"2022-05-12T05:19:13","guid":{"rendered":"https:\/\/iswc2022.semanticweb.org\/?page_id=1296"},"modified":"2022-10-04T23:08:50","modified_gmt":"2022-10-04T15:08:50","slug":"tutorials","status":"publish","type":"page","link":"https:\/\/iswc2022.semanticweb.org\/index.php\/tutorials\/","title":{"rendered":"Tutorials"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"1296\" class=\"elementor elementor-1296\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-15d44e1 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"15d44e1\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-3e1c875\" data-id=\"3e1c875\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-adf4a10 elementor-widget elementor-widget-heading\" data-id=\"adf4a10\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.17.0 - 08-11-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Tutorials<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ad2476b elementor-widget elementor-widget-spacer\" data-id=\"ad2476b\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.17.0 - 08-11-2023 *\/\n.elementor-column .elementor-spacer-inner{height:var(--spacer-size)}.e-con{--container-widget-width:100%}.e-con-inner>.elementor-widget-spacer,.e-con>.elementor-widget-spacer{width:var(--container-widget-width,var(--spacer-size));--align-self:var(--container-widget-align-self,initial);--flex-shrink:0}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container,.e-con>.elementor-widget-spacer>.elementor-widget-container{height:100%;width:100%}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer{height:100%}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner{height:var(--container-widget-height,var(--spacer-size))}.e-con-inner>.elementor-widget-spacer.elementor-widget-empty,.e-con>.elementor-widget-spacer.elementor-widget-empty{position:relative;min-height:22px;min-width:22px}.e-con-inner>.elementor-widget-spacer.elementor-widget-empty .elementor-widget-empty-icon,.e-con>.elementor-widget-spacer.elementor-widget-empty .elementor-widget-empty-icon{position:absolute;top:0;bottom:0;left:0;right:0;margin:auto;padding:0;width:22px;height:22px}<\/style>\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5052ff7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5052ff7\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-6706e5c\" data-id=\"6706e5c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6aaee4b elementor-widget elementor-widget-heading\" data-id=\"6aaee4b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Knowledge-aware Zero-shot Learning (K-ZSL): Concepts, Methods and Resources<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b65ed30 elementor-widget elementor-widget-text-editor\" data-id=\"b65ed30\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.17.0 - 08-11-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><strong>Duration<\/strong>: Half Day<strong><br \/>Organizers<\/strong>: Jiaoyan Chen, Yuxia Geng, Yufeng Huang and Huajun Chen<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b392f6a elementor-widget elementor-widget-text-editor\" data-id=\"b392f6a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Abstract:<\/strong> Zero-shot Learning (ZSL), which enables machine learning models to predict new targets without seeing their training samples, has attracted wide research interests in many communities such as computer vision (CV) and natural language processing (NLP). An effective solution is to use external knowledge such as text, attribute descriptions and Knowledge Graphs (KGs) to bridge the gap between the targets with training samples and the targets without training samples. This tutorial aims to introduce ZSL from the perspective of knowledge especially KG. We will first present the background of KG and ZSL, then introduce the overall picture of KG-aware ZSL and some representative paradigms with case studies, and finally provide a hands-on session on benchmarks and codes.<br \/><strong>Webpage<\/strong>:\u00a0<a href=\"https:\/\/china-uk-zsl.github.io\/kg-zsl-tutorial-iswc-2022\/\">https:\/\/china-uk-zsl.github.io\/kg-zsl-tutorial-iswc-2022\/<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6e61e4b elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"6e61e4b\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.17.0 - 08-11-2023 *\/\n.elementor-widget-divider{--divider-border-style:none;--divider-border-width:1px;--divider-color:#0c0d0e;--divider-icon-size:20px;--divider-element-spacing:10px;--divider-pattern-height:24px;--divider-pattern-size:20px;--divider-pattern-url:none;--divider-pattern-repeat:repeat-x}.elementor-widget-divider .elementor-divider{display:flex}.elementor-widget-divider .elementor-divider__text{font-size:15px;line-height:1;max-width:95%}.elementor-widget-divider .elementor-divider__element{margin:0 var(--divider-element-spacing);flex-shrink:0}.elementor-widget-divider .elementor-icon{font-size:var(--divider-icon-size)}.elementor-widget-divider .elementor-divider-separator{display:flex;margin:0;direction:ltr}.elementor-widget-divider--view-line_icon .elementor-divider-separator,.elementor-widget-divider--view-line_text .elementor-divider-separator{align-items:center}.elementor-widget-divider--view-line_icon .elementor-divider-separator:after,.elementor-widget-divider--view-line_icon 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.elementor-divider__element{margin-right:0}.elementor-widget-divider:not(.elementor-widget-divider--view-line_text):not(.elementor-widget-divider--view-line_icon) .elementor-divider-separator{border-top:var(--divider-border-width) var(--divider-border-style) var(--divider-color)}.elementor-widget-divider--separator-type-pattern{--divider-border-style:none}.elementor-widget-divider--separator-type-pattern.elementor-widget-divider--view-line .elementor-divider-separator,.elementor-widget-divider--separator-type-pattern:not(.elementor-widget-divider--view-line) .elementor-divider-separator:after,.elementor-widget-divider--separator-type-pattern:not(.elementor-widget-divider--view-line) .elementor-divider-separator:before,.elementor-widget-divider--separator-type-pattern:not([class*=elementor-widget-divider--view]) .elementor-divider-separator{width:100%;min-height:var(--divider-pattern-height);-webkit-mask-size:var(--divider-pattern-size) 100%;mask-size:var(--divider-pattern-size) 100%;-webkit-mask-repeat:var(--divider-pattern-repeat);mask-repeat:var(--divider-pattern-repeat);background-color:var(--divider-color);-webkit-mask-image:var(--divider-pattern-url);mask-image:var(--divider-pattern-url)}.elementor-widget-divider--no-spacing{--divider-pattern-size:auto}.elementor-widget-divider--bg-round{--divider-pattern-repeat:round}.rtl .elementor-widget-divider .elementor-divider__text{direction:rtl}.e-con-inner>.elementor-widget-divider,.e-con>.elementor-widget-divider{width:var(--container-widget-width,100%);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8f6b856 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8f6b856\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-72bcb75\" data-id=\"72bcb75\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-90764ad elementor-widget elementor-widget-heading\" data-id=\"90764ad\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Tutorial on Semantic Schema Discovery: Principles, Methods and Future Research Directions<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-573a576 elementor-widget elementor-widget-text-editor\" data-id=\"573a576\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Duration<\/strong>: Half Day<strong><br \/>Organizers<\/strong>: Kenza Kellou-Menouer, Nikolaos Kardoulakis, Georgia Troullinou, Zoubida Kedad, Dimitris Plexousakis and Haridimos Kondylakis<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c8044c2 elementor-widget elementor-widget-text-editor\" data-id=\"c8044c2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Abstract:<\/strong> The explosion of the data on the semantic web has led to many weakly structured, and irregular data sources, becoming available every day. The schema of these sources is useful for a number of tasks, such as source selection, query answering, exploration and summariza- tion. However, although semantic web data might contain schema in- formation, in many cases this is completely missing or partially defined. Schema discovery consists in extracting schema-related information from the original semantic graph, which some applications can exploit instead of or along with the original graph, to perform some tasks more efficiently. This tutorial presents a structured analysis and comparison of existing works in the area of semantic schema discovery helping researchers and practitioners to understand the challenges in the area; it is based upon a recent survey we authored.<br \/><strong>Webpage<\/strong>: <a href=\"https:\/\/users.ics.forth.gr\/~kondylak\/iswc_2022_tutorial\/\">https:\/\/users.ics.forth.gr\/~kondylak\/iswc_2022_tutorial\/<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-06a3698 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"06a3698\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5f60526 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5f60526\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5f435ed\" data-id=\"5f435ed\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-dc7d11b elementor-widget elementor-widget-heading\" data-id=\"dc7d11b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">A Beginner\u2019s Guide to Reasoning: How to reason your way to better data<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d19028a elementor-widget elementor-widget-text-editor\" data-id=\"d19028a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Duration<\/strong>: Half Day<strong><br \/>Organizers<\/strong>: Valerio Cocchi<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-17516e0 elementor-widget elementor-widget-text-editor\" data-id=\"17516e0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Abstract:<\/strong> Reasoning has become an increasingly valued tool in the semantic web space, and yet to many it&#8217;s still a black box solution. Perhaps more tragically, despite the explosion of its development in recent years, many in the space still perceive it as a slow, cumbersome, and ultimately impractical technology, which is far from true today. Whether you\u2019re looking to harness reasoning for your own goals, or to peek behind the curtains of someone else\u2019s solution, now is your time to learn. Get hands on with a reasoning engine in this interactive walkthrough: A Beginner\u2019s Guide to Reasoning. You\u2019ll come away understanding the power of reasoning, what it can add to your data, and the fundamentals of how to apply it yourself. With technology in this space running away, there\u2019s never been a better time to learn! This tutorial will touch on the basics of SPARQL, OWL, and Datalog, before diving into reasoning at a technical level. Each participant will come away having built a reasoning solution for themselves, guided along the way by knowledge engineers and subject experts. No prior knowledge is required.<br \/><strong>Webpage<\/strong>: <a href=\"https:\/\/www.oxfordsemantic.tech\/events\/iswc-2022-a-beginners-guide-to-reasoning-how-to-reason-your-way-to-better-data\">https:\/\/www.oxfordsemantic.tech\/events\/iswc-2022-a-beginners-guide-to-reasoning-how-to-reason-your-way-to-better-data<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-39aeb66 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"39aeb66\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-0482455 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0482455\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a892ae7\" data-id=\"a892ae7\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-9dfa6e6 elementor-widget elementor-widget-heading\" data-id=\"9dfa6e6\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Knowledge-infused Learning for Autonomous Driving (KL4AD)<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f33b238 elementor-widget elementor-widget-text-editor\" data-id=\"f33b238\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Duration<\/strong>: Half Day<strong><br \/>Organizers<\/strong>: Ruwan Wickramarachchi, Cory Henson, Sebastian Monka, Daria Stepanova and Amit Sheth<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b3b78a9 elementor-widget elementor-widget-text-editor\" data-id=\"b3b78a9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Abstract:<\/strong> Autonomous Driving (AD) is considered as a testbed for tackling many hard AI problems. Despite the recent advancements in the field, AD is still far from achieving full autonomy due to core technical problems inherent in AD. The emerging field of neuro-symbolic AI and the methods for knowledge-infused learning are showing exciting ways of leveraging external knowledge within machine\/deep learning solutions, with the potential benefits for interpretability, explainability, robustness, and transferability. In this tutorial, we will examine the use of knowledge-infused learning for three core state-of-the-art technical achievements within the AD domain. With a collaborative team from both academia and industry, we will demonstrate recent innovations using real-world datasets.<br \/><strong>Webpage<\/strong>: <a href=\"https:\/\/kl4ad.github.io\/2022\/\">https:\/\/kl4ad.github.io\/2022\/<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5badd86 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"5badd86\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-fffe018 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fffe018\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8031223\" data-id=\"8031223\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5c310c4 elementor-widget elementor-widget-heading\" data-id=\"5c310c4\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Artificial Intelligence Techniques for Earth Observation Data (AI4EO)<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2ecce7e elementor-widget elementor-widget-text-editor\" data-id=\"2ecce7e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Duration<\/strong>: Full Day<strong><br \/>Organizers<\/strong>: Manolis Koubarakis, Beg\u00fcm Demir, Dimitris Bilidas, Theofilos Ioannidis, Despina-Athanasia Pantazi, Dharmen Punjani, George Papadakis, George Stamoulis and Eleni Tsalapati<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-64b2e04 elementor-widget elementor-widget-text-editor\" data-id=\"64b2e04\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Abstract:<\/strong> In the last few years, there has been a lot of research in applying Artificial Intelligence techniques to Earth observation data. The subareas of Artificial Intelligence that contributed the most to the science of satellite data. are Deep Learning and Semantic Technologies (Ontologies and Linked Data). This tutorial will survey the latest state of the art in this area. It will start by explaining what satellite data is and why satellite data is a paradigmatic case of big spatiotemporal data amenable to Artificial Intelligence techniques. Examples of big satellite data, information and knowledge will be given for the case of the Copernicus program of the European Union. We will teach the tutorial participants how to \u201cbreak satellite data silos open\u201d by publishing the metadata of satellite datasets as microformats to enable their discovery by modern search engines through services like Dataset Search of Google, how to extract important geospatial information from satellite datasets using deep learning technologies, how to interlink this information with other relevant information available on the Web, and how to make this wealth of data and information freely available on the Web to enable the easy development of geospatial applications. We will present a complete pipeline that starts with satellite datasets in various formats that are made freely available in the archives of space agencies and ends with the deployment of an interactive visual application that uses satellite data utilizing linked data technologies. We will also present a query answering system over geospatial knowledge graphs, that allows non-experts to access linked geospatial data using natural language. The tutorial will give an in-depth coverage of the relevant techniques, systems and some applications developed by the presenters in the last 12 years in the context of 1 ERC grant (BigEarth), 12 European projects (TELEIOS, LEO, Melodies, Optique, BigDataEurope, Copernicus App Lab, WDAQUA, ExtremeEarth, AI4Copernicus and DeepCube), 1 ESA project (Prod-Trees), 3 projects funded by the German government (BIFOLD, TreeSatAI, IDEAL-VGI) and 2 projects funded by the Greek government (SCARE and GeoQA). The two teams presenting the tutorial (from the National and Kapodistrian University of Athens and the Technische Universit\u00e4t Berlin) come from different disciplines (Computer Science and Satellite Remote Sensing) and will offer an interdisciplinary presentation of the relevant theoretical and practical issues.<br \/><strong>Webpage<\/strong>: <a href=\"https:\/\/ai.di.uoa.gr\/#iswc22-tutorial\">https:\/\/ai.di.uoa.gr\/#iswc22-tutorial<\/a>\u00a0<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Tutorials Knowledge-aware Zero-shot Learning (K-ZSL): Concepts, Methods and Resources Duration: Half DayOrganizers: Jiaoyan Chen, Yuxia Geng, Yufeng Huang and Huajun Chen Abstract: Zero-shot Learning (ZSL), which enables machine learning models to predict new targets without seeing their training samples, has attracted wide research interests in many communities such as computer vision (CV) and natural language [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/iswc2022.semanticweb.org\/index.php\/wp-json\/wp\/v2\/pages\/1296"}],"collection":[{"href":"https:\/\/iswc2022.semanticweb.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/iswc2022.semanticweb.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/iswc2022.semanticweb.org\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/iswc2022.semanticweb.org\/index.php\/wp-json\/wp\/v2\/comments?post=1296"}],"version-history":[{"count":19,"href":"https:\/\/iswc2022.semanticweb.org\/index.php\/wp-json\/wp\/v2\/pages\/1296\/revisions"}],"predecessor-version":[{"id":1936,"href":"https:\/\/iswc2022.semanticweb.org\/index.php\/wp-json\/wp\/v2\/pages\/1296\/revisions\/1936"}],"wp:attachment":[{"href":"https:\/\/iswc2022.semanticweb.org\/index.php\/wp-json\/wp\/v2\/media?parent=1296"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}