CIEL aims at integrating tools and scenarios for open types of learning in which learners engage in larger, realistic tasks, such as scientific inquiry or engineering. In these kinds of learning, a pivotal place is taken by the products that learners create during their work, such as artifacts, models, hypotheses, sets of data etc. By redefining the concept of learning object to also include these kinds of products, and by defining standards and an ontology for these kinds of learning objects, CIEL enables semantic and technical integration of different learning environments, opening the possibility for supporting larger, more realistic scenarios for Collaborative Inquiry and Experiential learning. A first proof of concept in the domain of sampling is described.