anchor.diff:  
       <p>With that information organized and searchable, we can ask new kinds of questions about history. It will allow our interfaces to drop pins accurately on digital maps when you search for a forgotten place. It will allow you to explore a city's past on foot with your mobile device, 'checking in' to ghostly establishments (Empire State Building, meet Waldorf-Astoria Hotel). And it will allow us to link other historical documents to those places: archival records, old newspapers, business directories, photographs, restaurant menus, theater playbills etc., opening up new ways to research, learn, and discover the past.</p>
   
  +    <p>Building Inspector was made by <a href="http://www.nypl.org/labs">NYPL Labs</a> in collaboration with the <a href="http://www.nypl.org/locations/schwarzman/map-division"> Lionel Pincus and Princess Firyal Map Division</a> at The New York Public Library. </p>
  +
       <p>Questions? Comments? Want to stay in touch as the project develops? Contact us at <a href="mailto:buildinginspector@nypl.org">buildinginspector@nypl.org</a> or reach out to us on <a href="https://twitter.com/nypl_labs">Twitter</a>.</p>
   
  -     <h3>What Can I Do?</h3>
  -     <p>There are several kinds of inspections you and your fellow Inspectors can do. Specifically, here's what the different inspections tell us:</p>
  +     <h3 class="major">How Your Contributions Help</h3>
  +     <p>Currently, there are four different types of inspections you can perform. Each is designed to extract a particular type of data from the maps. Here's what the different inspections tell us:</p>
   
        <ul>
             <li><%= link_to(image_tag("icon-geometry.svg", :class=>"task-icon"), geometry_path, :class=>"link-task") %> <strong>Check Footprints</strong> - This establishes a baseline (literally!). We show you the buildings the computer identified, one outline at a time. You tell us whether it is right, wrong, or close but in need of fixing.</li>
  
positive.code: 
    </div>
  </div>
  
  
  
  
                  <h3>How is my work reviewed?</h3>
  
  <p>Every time you inspect a building, you’re essentially casting a vote alongside your fellow several other Inspectors. We show the same footprint and task to several people and tally up those votes to decide whether there’s agreement among inspectors.</p>
  
  <p>While each task has a different means to come to consensus, it’s useful to see an example. For Footprint Inspection, it’s coming to consensus on whether the computer-detected footprint is a Yes, No, or a Fix. We show the same footprint to at least 3 different people, and every 10 minutes we tally up the votes. If 75% or more agree, that footprint has reached “consensus” and the system removes it from the inspection queue. If the jury's still out, we keep the footprint in circulation until consensus is reached, focusing our collective efforts on the buildings most in need.</p>
  
  <p>The main takeaway here is: relax! Your fellow Inspectors have got your back. <em>It's no big deal if make a mistake once in a while, or make your best guess on an ambiguous case.</em> The community will double, triple, and quadruple check you, and you them. Go Team!</p>
  
      <h4>More background on the project</h4>
  
      <p>Building Inspector was made by <a href="http://www.nypl.org/labs">NYPL Labs</a> in collaboration with the <a href="http://www.nypl.org/locations/schwarzman/map-division"> Lionel Pincus and Princess Firyal Map Division</a> at The New York Public Library. The app uses digitized city atlases georeferenced by librarians and public volunteers on NYPL's <a href="http://maps.nypl.org">Map Warper</a>, an online tool suite for creating interactive historical maps. These rectified maps are then passed through a new computer vision process devised by NYPL Labs called the <a href="https://github.com/NYPL/map-vectorizer">Map Vectorizer</a>, which recognizes building footprints and converts them into machine-readable shape files (think of it like <a href="http://en.wikipedia.org/wiki/Optical_character_recognition">OCR</a>, but for maps).</p>
  
      <p>This is a big leap forward in the work of digitizing old maps. Until now, feature extraction has been done manually by staff and volunteers, tracing each individual building footprint painstakingly by hand. This is a difficult task, usually requiring on-site training, and so it can take months or years to complete a single atlas. The Vectorizer, however, can crunch through an entire borough map in a matter of hours. The data's not perfect, but it's good enough to start figuring out easier, crowd-friendly tasks for validating and correcting it (like the yes/no/fix process at the center of this app). And all of that public input can then be used to refine and improve the Vectorizer process. Human-computer collaboration!</p>
  
      <p>But enough yapping. Let's inspect some buildings!</p>
  
      <h4>CREDITS</h4>
      <p>
      <strong>The Lionel Pincus and Princess Firyal Map Division, NYPL</strong><br />
      Geospatial Librarian - Matt Knutzen<br />
  
negative.code: <% content_for :page_title do %>About - Building Inspector by NYPL Labs<% end %>
  <% content_for :dynamic_js do %>
    <%= stylesheet_link_tag    "home", :media => "all" %>
    <%= javascript_include_tag "about" %>
  <% end %>
  
  <%= render :partial => "partials/nav" %>
  
  <div id="main-container">
    <div id="intro" class="about">
      <h3 class="major">What's this all about?</h3>
  
      <p>For years The New York Public Library has collected maps documenting our ever-changing metropolis. Originally commissioned by insurance companies to assess property value and fire risk, these street atlases contain a wealth of detailed information about a city now largely lost to us: buildings long ago destroyed, streets renamed, whole neighborhoods redrawn or redefined. Making these lost places findable via contemporary digital maps allows us to drill down through the layers of urban change and study the city in profound new ways. But harvesting the data isn't easy.</p>
  
  