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Linked Open Data Knowledge Organization Systems (LOD-KOS) are defined by Dr. Zeng and Dr. Mayr in their 2018 paper Knowledge Organization Systems (KOS) in the Semantic Web: a multi-dimensional review as ‘value vocabularies and lightweight ontologies within the Semantic Web framework’. The paper surveys open data examples in the sciences and humanities and describes a community movement to convert and make sharable ‘thesauri, classification schemes, name authorities and lists of codes and terms, produced before the arrival of the ontology-wave’ into the ‘Semantic Web mainstream’. This session will review several examples of open data LOD-KOS, and then contrast them with examples of how commercial enterprises are currently using the Linked Data model to manage commercially sensitive enterprise data. The session will explore the practical challenges faced by any enterprise that has the requirement to manage a mixture of both public open data KOS resources and commercially sensitive KOS resources. The need emerges to support both collaboration and compartmentalization, and to do so flexibly. In order to do this KOS management systems need to support flexible and extensible access level controls (ACLs) and also assign ACL-Metadata to entities, predicates and data values. Both the public open data community and the private enterprise data community stand to benefit from a shared framework for curating KOS, and from mechanisms that will easily allow the selective sharing of some resources while protecting the confidentiality of others.