FactMiners.org is pleased to announce adoption of the Conceptual Reference Model (CRM) of the International Committee for Documentation (CIDOC) of the International Council of Museums (ICOM). The CIDOC-CRM is an 'ontology' for cultural heritage information, in other words it describes in a formal language the concepts and relations relevant to the documentation of cultural heritage. This ISO standard will be used as the reference model for the development of the FactMiners Fact Cloud metamodel that will logically organize the 'facts' to be 'mined' out of our initial project — the digital archive of Softalk magazine — respecting both the elements of its editorial content and the complex document structure of a magazine.

Okay, the headline's unnamed scientists did not specifically say that the idea for the FactMiners social-game ecosystem we're developing in support of The Softalk Apple Project is a great idea. What they are saying is that game-powered crowdsourcing methods are a tremendous resource for doing real and important science research.

Fei-Fei Li is the director of the Computer and Human Vision Lab within the legendary Stanford Artificial Intelligence Laboratory. While her research interests and breakthrough contributions to the field are wide-ranging, I want to focus briefly on a 2009 study she and her colleagues did at Princeton, before Dr. Li's selection to head the prestigious Stanford Vision Lab.

The 'Seeing Eye Child' Robot Adoption Agency is similar to the 'Tamagotchi' or 'digital pet' gaming phenomena that hit in the mid-1990's and is still going strong. The difference here is that we harness our little cognitive learning machines – AKA FactMiners game players – to 'adopt' a robot (AKA a machine-learning program with some form of vision – image intake and analysis – capability) and help it to learn to see and understand its world. As an adoptive 'Seeing Eye Child', players take on the roles of coach and referee for training sessions where adopted robots learn to see what's in the British Library images.

Our goal is to create a crowdsource-powered social gaming community that "comes to play" in museum and archive on-line repositories with the intensity of the multitudes who play Candy Crush or Words With Friends. And by playing FactMiners, this rabid game-playing community will produce two results.

In short, both the means – FactMiner exploratory-learning game-playing – and the ends – the "by-product" generation of the host collection's Fact Cloud – have value in their own right.