Welcome at the website of the project LeoLOD - Learning and Evolving Ontologies from Linked Open Data (2013-2015). The LeoLOD project is realized within the POMOST (PARENT-BRIDGE) programme of Foundation for Polish Science, cofinanced from European Union, Regional Development Fund. The overall vision of the LeoLOD project is: To study the problem of learning and evolving ontologies from massive, structured, interlinked, and distributed Linked Open Data datasets, where data is accessed using queries to SPARQL endpoints of RDF stores. To provide a suite of methods that addresses this problem. To implement the proposed methods within a popular ontology engineering environment. To evaluate the proposed framework on real-world datasets. The project will develop a number of algorithms for ontology learning and evolution. In order to efficiently manage the process of knowledge acquisition and facilitate introducing the proposed changes into an ontology, the project will re-use and extend ontology change vocabulary and develop a provenance model for learnt ontology axioms. Another outcome of the project will be the LeoLOD plug-in to open source ontology editor and knowledge acquisition environment Protégé , that will contain the implementation of the proposed methods and models. We will experimentally test developed methods on Linked Datasets coming from DBpedia project. We will also apply a user driven exploitation strategy, and will conduct a user study in order to evaluate the results of the project.