{"id":2503,"date":"2018-11-23T13:15:22","date_gmt":"2018-11-23T13:15:22","guid":{"rendered":"https:\/\/datamarket.at\/?post_type=tribe_events&#038;p=2503"},"modified":"2018-11-23T13:17:27","modified_gmt":"2018-11-23T13:17:27","slug":"smartdatasprint-data-is-not-a-monster","status":"publish","type":"tribe_events","link":"https:\/\/datamarket.at\/en\/event\/smartdatasprint-data-is-not-a-monster\/","title":{"rendered":"#SMARTDataSprint &#8211; Data is not a monster"},"content":{"rendered":"<div class=\"pbs-main-wrapper\"><p dir=\"ltr\">SMART Data Sprint is an intensive hands-on work, driven by online data and digital methods. For one week participants will have the chance to attend to keynote lectures, short talks, and parallel sessions of practical labs. After that, experts and scholars will invite participants to join projects and work in a collective problem.<\/p>\n<p dir=\"ltr\">We are pleased to announce that our keynote speaker is Richard Rogers (University of Amsterdam), the director of Digital Methods Initiative and the author of Digital Methods (MIT Press, 2013). An International team of senior researchers, including Richard Rogers, and several doctoral researchers will also be leading Short Talks and Practical Labs*. We also welcome Bernhard Rieder, associate professor in New Media and Digital Culture at the University of Amsterdam, with the masterclass &#8220;From Algorithms to Diagrams: How to Study Platforms?&#8221;, and a practical lab on machine learning techniques.<\/p>\n<p><iframe loading=\"lazy\" width=\"680\" height=\"383\" src=\"https:\/\/www.youtube.com\/embed\/bveMpEtAvug?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>This year, the practical labs will contemplate the following themes:<\/p>\n<p dir=\"ltr\">\u00bb Query Design<\/p>\n<p dir=\"ltr\">\u00bb Data Extraction Tools<\/p>\n<p dir=\"ltr\">\u00bb Querying App Stores<\/p>\n<p dir=\"ltr\">\u00bb Network Analysis with Gephi<\/p>\n<p dir=\"ltr\">\u00bb Image Networks<\/p>\n<p dir=\"ltr\">\u00bb YouTube Data Analysis<\/p>\n<p dir=\"ltr\">\u00bb Text Analysis with Antconc and Voyant Tools<\/p>\n<p dir=\"ltr\">\u00bb Raw Graphs<\/p>\n<p dir=\"ltr\">\u00bb Visual content analysis with Image Plot<\/p>\n<p dir=\"ltr\">\u00bb Extracting and analysing data with NodeXL Pro<\/p>\n<p dir=\"ltr\">\u00bb Hybrid Classification: Combining Grounded Theory and Machine Learning<\/p>\n<p dir=\"ltr\">Deadline for applications: 13 January 2019<\/p>\n<p dir=\"ltr\">For further information, please access the link <a target=\"_blank\" href=\"http:\/\/inovamedialab.org\/winter-institute-2019\" xlink=\"href\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=http:\/\/inovamedialab.org\/winter-institute-2019&amp;source=gmail&amp;ust=1543064718927000&amp;usg=AFQjCNH5KygTo7V7S5RSGMmm6qbulO28Ng\" rel=\"noopener\">http:\/\/inovamedialab.org\/<wbr \/>winter-institute-2019<\/a><\/p>\n<p dir=\"ltr\">Learn more about the data sprint approach in this video: <a target=\"_blank\" href=\"https:\/\/www.youtube.com\/watch?v=bveMpEtAvug&amp;index=1&amp;list=PLcGiWiKtsR0_BTLB4t_WH0iod-hXtX0eU\" xlink=\"href\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=https:\/\/www.youtube.com\/watch?v%3DbveMpEtAvug%26index%3D1%26list%3DPLcGiWiKtsR0_BTLB4t_WH0iod-hXtX0eU&amp;source=gmail&amp;ust=1543064718927000&amp;usg=AFQjCNESmWpWt0slBuM4iEd7M-eS1X4cIw\" rel=\"noopener\">#SMARTDataSprint<\/a><\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>SMART Data Sprint is an intensive hands-on work, driven by online data and digital methods. For one week participants will have the chance to attend to keynote lectures, short talks,&#8230;  <a class=\"excerpt-read-more\" href=\"https:\/\/datamarket.at\/en\/event\/smartdatasprint-data-is-not-a-monster\/\" title=\"Read #SMARTDataSprint &#8211; Data is not a monster\">Read more &raquo;<\/a><\/p>\n","protected":false},"author":3,"featured_media":2511,"comment_status":"open","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[126,125],"tribe_events_cat":[83],"class_list":["post-2503","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tag-hackathon","tag-lab","tribe_events_cat-workshop","cat_workshop"],"translation":{"provider":"WPGlobus","version":"3.0.0","language":"en","enabled_languages":["de","en"],"languages":{"de":{"title":true,"content":true,"excerpt":false},"en":{"title":false,"content":false,"excerpt":false}}},"_links":{"self":[{"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/tribe_events\/2503","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/comments?post=2503"}],"version-history":[{"count":4,"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/tribe_events\/2503\/revisions"}],"predecessor-version":[{"id":2716,"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/tribe_events\/2503\/revisions\/2716"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/media\/2511"}],"wp:attachment":[{"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/media?parent=2503"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/tags?post=2503"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/datamarket.at\/en\/wp-json\/wp\/v2\/tribe_events_cat?post=2503"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}