{"id":729,"date":"2020-10-01T11:44:43","date_gmt":"2020-10-01T11:44:43","guid":{"rendered":"https:\/\/meteoceanics.org\/icss\/?page_id=729"},"modified":"2023-02-13T07:22:13","modified_gmt":"2023-02-13T07:22:13","slug":"interdisciplinary-data-analytics-and-model-design","status":"publish","type":"page","link":"https:\/\/meteoceanics.org\/icss\/publications\/interdisciplinary-data-analytics-and-model-design\/","title":{"rendered":"Interdisciplinary Data Analytics and Model Design"},"content":{"rendered":"\r\n<p><em>From Theory to Operation, Empowering Innovation; From Local to Global, Empowering Life Choices; With Frontier Science, Technology&#8230;\u00a0and Wisdom!<\/em><\/p>\r\n\r\n\r\n\r\n<p id=\"block-6c857716-6340-48b9-91e5-3deaf964d7b3\"><strong>Publication briefs<\/strong><\/p>\r\n\r\n\r\n\r\n<p id=\"block-92df66b6-3f91-4192-8024-876c4916103d\">Publication type: Pedagogic<br \/>Author: Rui A. Pita Perdig\u00e3o (R.A.P. Perdig\u00e3o)<br \/>Date: 2020<br \/>Title: Interdisciplinary Data Analytics and Model Design<br \/>DOI: <a href=\"https:\/\/doi.org\/10.46337\/mdsc.5364\">https:\/\/doi.org\/10.46337\/mdsc.5455<\/a><br \/>Indexed: Yes (Crossref)<\/p>\r\n\r\n\r\n\r\n<p>Cite as: Perdig\u00e3o, Rui A. P. (2020): <em>Interdisciplinary Data Analytics and Model Design<\/em>. <a href=\"https:\/\/doi.org\/10.46337\/mdsc.5364\">https:\/\/doi.org\/10.46337\/mdsc.5455<\/a><\/p>\r\n\r\n\r\n\r\n<p id=\"block-8e8a82e7-940b-49d1-a6e4-eec774f4f3ae\">Methodological Keywords: Information Physics, Information Theory, Complex Systems, Dynamical Systems, Mathematical Physics, Non-Ergodic, Chaos, Entropy, Emergence, Synergy, Coevolution, Quantum Information, Post-Quantum Theory.<br \/>Applied Keywords: Big Data Analytics, Artificial Intelligence, Machine Learning, Earth System Dynamics, Socio-Environmental Systems, Climate Change, Sustainability.<\/p>\r\n\r\n\r\n\r\n<p><strong>Full Document<\/strong><\/p>\r\n<p>Restricted Access: <a href=\"https:\/\/meteoceanics.org\/icss\/publications\/login\">Login here<\/a><\/p>\r\n<p id=\"block-9199ebc5-3cee-4bb1-beaa-ad04c803a75a\"><strong>Synopsis<\/strong><\/p>\r\n\r\n\r\n\r\n<p id=\"block-df3e32e5-7a2e-441e-8f17-2154a86a1024\">Rui Perdig\u00e3o\u2019s doctoral course on\u00a0<strong>Interdisciplinary Data Analytics and Model Design<\/strong> is headquartered and primarily delivered at the Meteoceanics Institute for Complex System Science and partner institutions.<\/p>\r\n\r\n\r\n\r\n<p id=\"block-df3e32e5-7a2e-441e-8f17-2154a86a1024\">Moreover, since 2019 it is also available as a semester doctoral course at the University of Lisbon (offering 6 ECTS for students enrolled in partner programs). The course is specially tailored to a wide-spectrum interdisciplinary audience spanning across natural, social, technical and exact sciences.<\/p>\r\n\r\n\r\n\r\n<p id=\"block-c431341e-fa47-4564-8cd4-869d6cf919d9\">The associated pedagogic materials emerge as a natural guide for graduate students, researchers and practitioners alike, matching the structure of the course as follows:<\/p>\r\n\r\n\r\n\r\n<h5 id=\"block-628bace0-a77d-4bab-a319-dad3ca10b8a2\">TAKE-HOME<\/h5>\r\n\r\n\r\n\r\n<ul id=\"block-7f12c140-767c-4a24-af76-03c85a071085\">\r\n<li>Acquisition of fundamental competences in data analysis, its relevance and implementation in the conceptualization and formal analysis of systems in an interdisciplinary perspective;<\/li>\r\n<li>Learning fundamental techniques for information retrieval, analysis and treatment along with its uncertainties, from data acquisition to model design;<\/li>\r\n<li>Acquisition of new competences in scientific research, development and<\/li>\r\n<li>communication at the interface between natural and social sciences;<\/li>\r\n<li>Special emphasis on interdisciplinary challenges of climate change and decision<\/li>\r\n<li>support towards sustainable development.<\/li>\r\n<\/ul>\r\n\r\n\r\n\r\n<h5 id=\"block-610d4c30-8bc2-4bfd-a43f-f7493feb53d7\">PROGRAM<\/h5>\r\n\r\n\r\n\r\n<ul id=\"block-8b9ac5b1-3480-4230-97de-a9433f99a3ae\">\r\n<li>Beneath Data, there is a Story: Fundamental principles behind the nature, geometry and dynamics of information across natural, social and joint systems;<\/li>\r\n<li>Retrieving the Story: Fundamental methods for data analytics and model design. From spatiotemporal geostatistics to broader dynamic information tools for data mining, pattern recognition, causal analysis and model design;<\/li>\r\n<li>Quality-checking the Story: Techniques for quality check, uncertainty assessment and data processing towards strengthening information reliability;<\/li>\r\n<li>Sharing the Story: Techniques for data visualization, information sharing and overall communication of scientific results;<\/li>\r\n<li>GeoSys Operation: Operational real-world examples for a) data mining and machine learning in large satellite datasets; b) nonlinear analytics and model design for earth system dynamics; c) early warning and automated decision support systems in natural (e.g. hydro-meteorological, geophysical) hazards;<\/li>\r\n<li>Frontier Operation: early warning detection and adaptive decision support of critical transitions and extremes in the earth system under climate change;<\/li>\r\n<li>Hands-On: Simple analytical and computational examples on the prior points.<\/li>\r\n<\/ul>\r\n\r\n\r\n\r\n<p id=\"block-9ef966cd-ab70-4689-9273-f69872b3396e\">\u00a0<\/p>\r\n","protected":false},"excerpt":{"rendered":"<p>From Theory to Operation, Empowering Innovation; From Local to Global, Empowering Life Choices; With Frontier Science, Technology&#8230;\u00a0and Wisdom! Publication briefs Publication type: PedagogicAuthor: Rui A. Pita Perdig\u00e3o (R.A.P. Perdig\u00e3o)Date: 2020Title: Interdisciplinary Data Analytics and Model DesignDOI: https:\/\/doi.org\/10.46337\/mdsc.5455Indexed: Yes (Crossref) Cite as: Perdig\u00e3o, Rui A. P. (2020): Interdisciplinary Data Analytics and Model Design. https:\/\/doi.org\/10.46337\/mdsc.5455 Methodological Keywords: &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/meteoceanics.org\/icss\/publications\/interdisciplinary-data-analytics-and-model-design\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Interdisciplinary Data Analytics and Model Design&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":311,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/meteoceanics.org\/icss\/wp-json\/wp\/v2\/pages\/729"}],"collection":[{"href":"https:\/\/meteoceanics.org\/icss\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/meteoceanics.org\/icss\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/meteoceanics.org\/icss\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/meteoceanics.org\/icss\/wp-json\/wp\/v2\/comments?post=729"}],"version-history":[{"count":4,"href":"https:\/\/meteoceanics.org\/icss\/wp-json\/wp\/v2\/pages\/729\/revisions"}],"predecessor-version":[{"id":1132,"href":"https:\/\/meteoceanics.org\/icss\/wp-json\/wp\/v2\/pages\/729\/revisions\/1132"}],"up":[{"embeddable":true,"href":"https:\/\/meteoceanics.org\/icss\/wp-json\/wp\/v2\/pages\/311"}],"wp:attachment":[{"href":"https:\/\/meteoceanics.org\/icss\/wp-json\/wp\/v2\/media?parent=729"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}