{"version":"1.0","provider_name":"Digital Innovation and Transformation","provider_url":"https:\/\/d3.harvard.edu\/platform-digit","author_name":"David","author_url":"https:\/\/d3.harvard.edu\/platform-digit\/author\/david\/","title":"Bikes, Data and the Crowd - Digital Innovation and Transformation","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"hwJOid3ZQh\"><a href=\"https:\/\/d3.harvard.edu\/platform-digit\/submission\/bikes-data-and-the-crowd\/\">Bikes, Data and the Crowd<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/d3.harvard.edu\/platform-digit\/submission\/bikes-data-and-the-crowd\/embed\/#?secret=hwJOid3ZQh\" width=\"600\" height=\"338\" title=\"&#8220;Bikes, Data and the Crowd&#8221; &#8212; Digital Innovation and Transformation\" data-secret=\"hwJOid3ZQh\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/d3.harvard.edu\/platform-digit\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2015\/11\/Hubway1-1024x6811.jpg","thumbnail_width":1024,"thumbnail_height":681,"description":"The value of bike sharing services like Hubway heavily depends on bike availability at each of their stations. But how are they able to predict when, where, and how many bikes should be relocated to optimize their network? The solution lies in the data."}