Creative Commons has officially launched a search engine allowing for the easy exploration of more than 300 million images that are free to use within certain conditions.
The database comprises images from 19 collections, among them Flickr, Rawpixel, and a number of museums including New York City’s Metropolitan Museum of Art, and the U.K.’s Science Museum.
Creative Commons launched in 2001 and offers copyright licenses that give the public permission to share and use artists’ work for free provided they follow the guidelines set by the creator. The images are accessible to everyone and are often used by media outlets, educational institutions, and creatives with an online presence.
“Aesthetically, you’ll see some key changes — a cleaner home page, better navigation and filters, design alignment with creativecommons.org, streamlined attribution options, and clear channels for providing feedback on both the overall function of the site and on specific image reuses,” the non-profit wrote in a blog post announcing the search engine’s launch.
It added: “Under the hood, we improved search loading times and search phrase relevance, implemented analytics to better understand when and how the tools are used, and fixed many critical bugs our community helped us to identify.”
Going forward, the team will work on increasing the number of available images in its catalog, and, later in 2019, will index additional types of CC-licensed works, such as open textbooks and audio.
More immediately, over the coming months, it wants to add more advanced filters to the search engine’s home page, as well as the ability to browse collections without entering search terms. It also plans to offer students the chance to contribute to the development of the search engine via Google’s Summer of Code initiative that aims to encourage young people to get involved with open source software development.
Creative Commons says that while its main ambition is to offer access via its search engine to all 1.4 billion works in the commons, for now it’s focusing on images “that creators desire to reuse in meaningful ways, learning about how these images are reused in the wild, and incorporating that learning back into CC Search.”
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