Open Attribute, “a suite of tools that makes it ridiculously simple for anyone to copy and paste the correct attribution for any CC licensed work,” launched today with browser add-ons for Mozilla Firefox and Google Chrome. The add-ons “query the metadata around a CC-licensed object and produce a properly formatted attribution that users can copy and paste wherever they need to.”
If you use our license chooser and copy and paste the resulting HTML code into your website, then you’re pretty much good to go. Anyone who uses the Open Attribute browser add-on to query your site will automatically receive a formatted HTML or plain text attribution that they can copy and paste to give you the proper credit.
Open Attribute uses CC REL metadata found in the pages to generate the attribution metadata. You might remember that we developed a guide with real examples to make CC REL metadata much easier to implement: CC REL by Example contains example HTML pages, as well as explanations and links to more information. If you’re curious to see how Open Attribute pulls the metadata, the guide includes a specific section on Attributing Reuses.
Open Attribute is a direct result of the Mozilla Drumbeat Festival held last year in Barcelona on Learning, Freedom and the Web. See Molly Kleinman’s post for a more comprehensive run-down of the origins and team behind Open Attribute.6 Comments »
The following is cross-posted from the CC Labs blog. Creative Commons technical team blogs at CC Labs about metadata, emerging standards, demos, prototypes, and Creative Commons’ technical infrastructure.
You may have noticed that the copy-and-paste HTML you get from the CC license chooser includes some strange attributes you’re probably not familiar with. That is RDFa metadata, and it allows for the CC license deeds, search engines, Open Attribute, and other tools to discover metadata about your work and generate attribution HTML. Many platforms have implemented CC REL metadata in their CC license marks, such as Connexions and Flickr, and it’s our recommended way to mark works with a CC license.
In an effort to make CC license metadata (or CC REL metadata) much easier to implement, we’ve created CC REL by Example. It includes many example HTML pages, as well as explanations and links to more information.
We’re hoping this guide will serve as a useful set of examples for developers and publishers who want to publish metadata for CC licensed works. Even if you just use CC licenses for your own content, now is a great time to take a first step into structured data and include information about how you’d like to be attributed.No Comments »
Last week in the vuDAT building at Michigan State University, a group of developers interested in educational search and discovery got together to contribute code (in what’s commonly called a code sprint) to Creative Commons’ DiscoverEd project. Readers interested in the technical details about our work last week can find daily posts on CC Labs — Day 1, Day 2, and Day 3.
DiscoverEd is a semantic enhanced search prototype. What does that mean practically? Let’s say you’re a ninth grade biology teacher interested in finding education resources about cell organelles to hand out to students. How would you go about that?
If you’re web savvy, you might open up a search engine like Google, Yahoo, or Bing and search for “cell organelles”. You’d find a lot of resources (Google alone finds over 11 million pages!), but which do you choose to investigate further? It’s time consuming and difficult to sift through search results for resources that have certain properties you might be interested in, like being appropriate for 9th graders, being under a CC license that allows you to modify the resource and share changes, or being written in English or Spanish, for example. As you throw up your hands in dismay, you might think “Can’t someone do this for me?!”
DiscoverEd is an educational search prototype that does exactly that, by searching metadata about educational resources. It provides a way to sift through search results based on specific qualities like what license it’s under, the education level, or subject.
Compare search results for “cell organelles” in Google, Yahoo, Bing, and now in DiscoverEd. You can see that finding CC licensed educational resources is friendlier because of the available metadata accompanying each result.
While most search engines rely solely on algorithmic analyses of resources, DiscoverEd can incorporate data provided by the resource publisher or curator. As long as curators and publishers follow some basic standards, metadata can be consumed and displayed by DiscoverEd. These formats (e.g. RDFa) allow otherwise unrelated educational projects, curators, and repositories to express facts about their resources in the same format so that tools (like DiscoverEd) can use that data for useful purposes (like search and discovery).
Creative Commons believes an open web following open standards leads to better outcomes for everyone. Our vision for the web is that everyone following interoperable standards, whether they be legal standards like the CC licenses or technical standards like CC REL and RDFa, will result in a platform that enables social and technical innovation in the same way that HTTP and HTML enabled change. DiscoverEd is a project that allows us to explore ways to improve search for OER, and simultaneously demonstrate the utility of structured data.
Continued development of DiscoverEd is supported by the AgShare project, funded by a grant from The Gates Foundation. Creative Commons thanks MSU, vuDAT, MSU Global, and the participants in the DiscoverEd sprint last week for their support.1 Comment »