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Hello all, The Samvera MODS and RDF Descriptive Metadata Subgroup is pleased to announce that the initial draft of our MODS to RDF Mapping Recommendations is now available for review and comment: https://goo.gl/SGCfev This application profile provides recommendations for mapping MODS XML metadata for digital objects to RDF Linked Data classes and properties using a range of widely-adopted RDF namespaces. The result of a 30-month collaborative process involving participants from more than a dozen academic and public libraries, this document includes a comprehensive mapping of MODS elements to RDF using real-world metadata use cases and hundreds of examples. Rather than pursuing a straight XML-to-RDF approach using the MODS RDF Ontology v.1 or proposing (yet another) new formal ontology, the mappings include properties from existing vocabularies that are already extensively used, such as Schema.org, Dublin Core, BIBFRAME, BIBO, RDA, FOAF, EDM, and LC Linked Data Service datasets. The re-use of these vocabularies provides greater value to records in a Linked Data context. A straightforward "direct" mapping (which does not require creating or maintaining local objects for concepts such as subjects, people, events, or places) and a more thorough "minted object" mapping are provided for most MODS elements. Although this work was conducted under the umbrella of the Samvera digital repository framework, the mapping is system-agnostic and intended to be applicable in a wide range of contexts. All comments and feedback are welcome. Feedback may be submitted via: - Comments added directly to the Google Doc - An online comment form (submissions are anonymous): https://goo.gl/forms/dpqxGWotqShB4Y0U2 - Via email to [log in to unmask] Comments will be accepted until August 1, 2018. Thanks for your consideration! Julie Hardesty (Indiana University) on behalf of The Samvera MODS and RDF Descriptive Metadata Subgroup https://wiki.duraspace.org/display/samvera/MODS+and+RDF+Descriptive+Metadata+Subgroup ######################################################################## to manage your DLF-ANNOUNCE subscription, visit diglib.org/announce