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This representation in RuleML allows the rule base to be platform\u2010independent, flexibly extensible and executable.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>The RuleML source representation is easily converted to other XML\u2010based languages (such as RDF, OWL and XMI) as well as incorporated into, and extracted from, existing XML\u2010based repositories (such as IEEE LOM and CanLOM) using XSL Transformations (XSLT).<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>The RuleML facts and rules represented in the positional slotted language are used by the OO jDREW reasoning engine to detect and map between semantically equivalent components of course outlines as the key step in their interoperation. In particular, this will enable the precise delivery of learning objects (e.g. course outlines) from repositories to a specific learner's context.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>Although the particular scenario is discussed in the present paper, the proposed approach can be applied to other tasks related to enabling semantic interoperability.<\/jats:p><\/jats:sec>","DOI":"10.1108\/17415650810871574","type":"journal-article","created":{"date-parts":[[2008,5,4]],"date-time":"2008-05-04T19:59:04Z","timestamp":1209931144000},"page":"39-58","source":"Crossref","is-referenced-by-count":3,"title":["RuleML\u2010based learning object interoperability on the Semantic Web"],"prefix":"10.1108","volume":"5","author":[{"given":"Yevgen","family":"Biletskiy","sequence":"first","affiliation":[]},{"given":"Harold","family":"Boley","sequence":"additional","affiliation":[]},{"given":"Girish R.","family":"Ranganathan","sequence":"additional","affiliation":[]},{"given":"Harold","family":"Boley","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2021010423181638800_b1","unstructured":"Aroyo, L., Dolog, P., Houben, G.J., Kravcik, M., Naeve, A., Nilsson, M. and Wild, F. 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