faq.html

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layout: faq
title: Elog.io - FAQ
root: "../"
---

<div class="faq">
<a name="general"></a><h2>General questions</h2>
<p><strong>What does Elog.io do?</strong></p>
<p>
Elog.io sits alongside your browser and gives you an opportunity to
explore the photos that you encounter while browsing. For any of the
photographs that are part of the Elog.io catalog, it can tell you
information about the author of the photo, where it's from, and what
permissions you could have to use it.
</p>

<p><strong>What photos do you store information about?</strong></p>
<p>
 We currently have information about photographs from
 <a href="http://commons.wikipedia.org">Wikimedia Commons</a>, a collection
 of approximately 23 million photographs (November 2014). The photographs on
 Wikimedia Commons in turn come from a wide variety of sources: the authors
 themselves, imported from <a href="http://flickr.com">Flickr</a>, or other
 sources.
</p>
<p>
 Elog.io is constantly expanding on the number of photographs we have in
 our database, and the aim is to include as much as possible of all openly
 licensed photos.
</p>

<p><strong>So only openly licensed photos then?</strong></p>
<p>
 Yes. We strongly believe in the open ecosystem and believe that answering
 the basic question: is this openly licensed? for any photograph is important to
 facilitate the ecosystem. For photographs that you can identify through 
 Elog.io, you can be reasonably certain that they are indeed licensed in the
 way indicated (public domain, a Creative Commons license or similar).
</p>

<p><strong>Can I include my own photos?</strong></p>
<p>
 We'd love to include your photos, or any collections that you're responsible
 for, so we can make them findable through Elog.io. Please
 <a href="#contact">contact us</a> for more information. Please note that at
 this time, we're primarily looking at including larger collections of openly
 licensed photographs, and the more work you're willing to do yourself on
 making them available to us - or creating a project together to do the work -
 the more likely it is that we can include them quickly.
</p>
 
<p><strong>Why is this even important?</strong></p>
<p>
 From a practical perspective, knowing who authored a photograph and what terms
 and conditions it's available under is important in order to understand how
 you may use an photograph, and what attribution you must provide when you do.
</p>
<p>
 What we believe is that having this information available also place the
 photograph in its right cultural context. Knowing where it's from and who
 authored it contributed to our understanding of a photograph, it increases
 its value, and makes us relate to it in a different way. We think that if
 people had this information available about any photograph they encountered
 online, the need to enforce and assert copyright would also be less,
 and over time, we can create an ecosystem where mutal respect and common
 sense take precedence.
</p>

<p><strong>What's your privacy policy?</strong></p>
<p>
 We take every precaution to keep your information safe, and we don't
 purposefully collect any more information than we need to do the actual
 processing on your behalf. We also remove information as soon as we're
 done with it. You can read more in our <a href="/privacy/">Privacy Policy</a>.
</p>

<a name="matching"></a><h2>Image matching</h2>
<p><strong>Why doesn't Elog.io match X?</strong></p>
<p>
 The matching algorithm that powers Elog.io is based on
 <a href="http://blockhash.io">Blockhash</a>, a free and open source software
 implementation of an photograph matching algorithm. In our research, we've found
 that this algorithm gives the best possible matches and it regularly
 outperforms many other algorithms. That doesn't mean it's perfect though!
</p>
<p>
 Blockhash is less perceptive of landscape photographs, and in
 general any photograph which includes large amounts of similar colors and
 contrasting areas. For instance, a photograph which includes the open sky
 in its upper half, and some buildings or other features in the lower half,
 has an area of very similar color (the sky) and significant contrast (between
 its upper and lower half). Such photographs, from an algorithm point of
 view, are very similar to each other, and creating good matches are almost
 impossible.
</p>
<p>
 The Blockhash algorithm also doesn't deal well with modifications to
 photographs. We've set the bar at verbatim re-use. Photographs that are
 resized or are changed from JPG to PNG or similarly, but still retain the
 same aspect ratio, and the same photograph, are the photographs that the algorithm
 is designed to match. The moment you crop the photograph, add borders, change the
 colors, or do other manipulations, you're creating a derivative work, and
 Elog.io will most likely not match this.
</p>

<p><strong>Why don't you use algorithm Y?</strong></p>
<p>
 In our work with Elog.io, we've evaluated a number of different algorithms.
 Chances are, Y is one of them, but we'd still love to hear your thoughts
 about it! If you have a compelling algorithm, we may consider switching to
 it. Here are the considerations and conditions we place on our algorithms:
</p>
<ul>
 <li>They should not be encumbered by patents, and we should be able to implement them in Free and Open Source Software, like Elog.io.</li>
 <li>They should work well in a browser, meaning that they should be reasonably fast and easy to implement in JavaScript.</li>
 <li>They should generate a hash value, with the particular characteristics that small changes to the photograph (resize, etc) should result in small changes to the hash.</li>
 <li>Over a random sample of photographs, they should generate no or very few false positives (photographs that are matched against each other despite being different) and no or few false negatives (photographs that doesn't match, despite that they are the same).</li>
 <li>In general, they should prioritise generating no false positives, since a false positive is worse than a false negative.</li>
</ul>
<p>
 When we evaluate an algorithm, we generate hashes against a
 representative set of photographs that we have on file. We do two tests. In the
 first test we transform the photographs (resize, format change, cropping,
 add borders, rotate), and we test to see how much we can transform a photograph
 while still matching the original. In the second test we generate hashes
 for a large amount of photographs and we cross compare them against each other.
 We calculate the hamming distance (number of bits that differ) between the
 hashes and find out how often we would get false positives.
</p>

<p><strong>But can you please try algorithm Y?</strong></p>
<p>
 If you've looked at our considerations and conditions and think that you
 have an algorithm that's worth trying, we would still love to test it.
 The easiest way is that you fork <a href="http://github.com/commonsmachinery/blockhash">Blockhash on Github</a> and create an implementation with your
 algorithm. You can then submit a pull request and/or create an issue with
 a reference to your fork, to allow us to pull your code to test it.
</p>

<a name="database"></a><h2>Database information</h2>
<p><strong>How many photographs are in your database?</strong></p>
<p>
As of the 18th of November 2014, we have information of 22,412,293 photographs in the
Elog.io catalog. These photographs are exclusively from Wikimedia Commons
and as such represent a very wide variety of photographs, most of which are
already used elsewhere in Wikipedia.
</p>

<p><strong>What information do you store?</strong></p>
<p>
We store information about the author, title and license information about
each photograph. In addition to this, we record the URLs of the photograph
as well as at least one thumbnail or smaller resolution photograph. This is the
information that we get from Wikimedia Commons.
</p>
<p>
We supplement the information from Wikimedia Commons with our own
calculation of a <a href="http://blockhash.io">Blockhash</a> value for each
photograph.
</p>


<a name="contact"></a><h2>Contact information</h2>
<strong><p>Who runs this?</p></strong>
<p>
 The initial work of Elog.io was provided by <a href="http://commonsmachinery.se">Commons Machinery</a>, funded by the <a href="http://shuttleworthfoundation.org">Shuttleworth Foundation</a>. The project is run as a free and open source
 project by <a href="http://about.me/jonaso">Jonas Öberg</a>. Hosting is
 currently provided Commons Machinery.
</p>

<strong><p>Can I email you?</p></strong>
<p>
 We'd love to hear from you! You can email us at hello@elog.io.
</p>

<strong><p>What other ways can I get in touch?</p></strong>
<p>
 Email is really the key to our hearts, but you can also reach out to us
 on <a href="http://twitter.com/elog_io">twitter (@elog_io)</a> or by
 sending post to us at:
</p>
<p>
 Elog.io<br />
 Åsgatan 5<br />
 646 32 Gnesta<br />
 SWEDEN
</p>

</div>