{"id":271,"date":"2022-02-19T08:30:59","date_gmt":"2022-02-19T13:30:59","guid":{"rendered":"https:\/\/pressbooks.library.ryerson.ca\/criticaldataliteracy\/?post_type=chapter&#038;p=271"},"modified":"2022-02-28T12:21:42","modified_gmt":"2022-02-28T17:21:42","slug":"start-with-good-quality-data","status":"publish","type":"chapter","link":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/chapter\/start-with-good-quality-data\/","title":{"raw":"Start With Good Quality Data","rendered":"Start With Good Quality Data"},"content":{"raw":"When creating a data visualization, you need to ensure that your data source is legitimate and credible.\u00a0 Choosing your data source is critical.\u00a0 Given the glut of information available online, it is important to sift through it to find high quality information.\u00a0 Ask yourself the following questions:\r\n<ul>\r\n \t<li style=\"font-weight: 400\">Is this source trustworthy? Is the data verifiable?<\/li>\r\n \t<li style=\"font-weight: 400\">Can I share this data? Are there privacy concerns or other harms to be aware of?<\/li>\r\n \t<li style=\"font-weight: 400\">Is this data or information appropriate for the story and message?<\/li>\r\n \t<li style=\"font-weight: 400\">Does it reveal something that makes me uncomfortable? How will I make sure unconscious biases are not affecting my interpretation of it?<\/li>\r\n<\/ul>\r\n<div class=\"textbox\">\r\n<h2>Deeper Dive<\/h2>\r\nA good lens to use is the <a href=\"https:\/\/learn.library.ryerson.ca\/Research\/evaluate\" target=\"_blank\" rel=\"noopener\">CRAAP test<\/a>. Watch this video, <a href=\"https:\/\/www.youtube.com\/watch?v=EyMT08mD7Ds\" target=\"_blank\" rel=\"noopener\">Evaluating Sources<\/a>, to learn more.\r\n\r\nThe CRAAP test asks you to consider: currency, relevance, accuracy, authority and purpose. Browse through the list below for a definition of each.\r\n\r\n[h5p id=\"6\"]\r\n\r\n<\/div>","rendered":"<p>When creating a data visualization, you need to ensure that your data source is legitimate and credible.\u00a0 Choosing your data source is critical.\u00a0 Given the glut of information available online, it is important to sift through it to find high quality information.\u00a0 Ask yourself the following questions:<\/p>\n<ul>\n<li style=\"font-weight: 400\">Is this source trustworthy? Is the data verifiable?<\/li>\n<li style=\"font-weight: 400\">Can I share this data? Are there privacy concerns or other harms to be aware of?<\/li>\n<li style=\"font-weight: 400\">Is this data or information appropriate for the story and message?<\/li>\n<li style=\"font-weight: 400\">Does it reveal something that makes me uncomfortable? How will I make sure unconscious biases are not affecting my interpretation of it?<\/li>\n<\/ul>\n<div class=\"textbox\">\n<h2>Deeper Dive<\/h2>\n<p>A good lens to use is the <a href=\"https:\/\/learn.library.ryerson.ca\/Research\/evaluate\" target=\"_blank\" rel=\"noopener\">CRAAP test<\/a>. Watch this video, <a href=\"https:\/\/www.youtube.com\/watch?v=EyMT08mD7Ds\" target=\"_blank\" rel=\"noopener\">Evaluating Sources<\/a>, to learn more.<\/p>\n<p>The CRAAP test asks you to consider: currency, relevance, accuracy, authority and purpose. Browse through the list below for a definition of each.<\/p>\n<div id=\"h5p-6\">\n<div class=\"h5p-iframe-wrapper\"><iframe id=\"h5p-iframe-6\" class=\"h5p-iframe\" data-content-id=\"6\" style=\"height:1px\" src=\"about:blank\" frameBorder=\"0\" scrolling=\"no\" title=\"CRAAP Test\"><\/iframe><\/div>\n<\/div>\n<\/div>\n","protected":false},"author":388,"menu_order":3,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-271","chapter","type-chapter","status-publish","hentry"],"part":247,"_links":{"self":[{"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/pressbooks\/v2\/chapters\/271","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/wp\/v2\/users\/388"}],"version-history":[{"count":5,"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/pressbooks\/v2\/chapters\/271\/revisions"}],"predecessor-version":[{"id":771,"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/pressbooks\/v2\/chapters\/271\/revisions\/771"}],"part":[{"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/pressbooks\/v2\/parts\/247"}],"metadata":[{"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/pressbooks\/v2\/chapters\/271\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/wp\/v2\/media?parent=271"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/pressbooks\/v2\/chapter-type?post=271"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/wp\/v2\/contributor?post=271"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/pressbooks.library.torontomu.ca\/criticaldataliteracy\/wp-json\/wp\/v2\/license?post=271"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}