is a list of questions that may arise in determining semantic precision. correctness How can correct syntax and semantics be enforced? Are tools (such as XML Schema) readily available to validate syntax of data exchanges? adequacy/expressivity/scope Does the system represent everything that is of practical use for the purpose? Is an emphasis being placed on data that is externalized (exposed or transferred between systems)? efficiency How efficiently can the representation be searched / queried, and - possibly - reasoned on? complexity How steep is the learning curve for defining new concepts, querying for them or constraining them? are there appropriate tools for simplifying typical workflows? (See also: ontology editor) translatability Can the representation easily be transformed (e.g. by Vocabulary-based transformation) into an equivalent representation so that semantic equivalence is ensured? Determining location on the semantic spectrum Many organizations today are building a metadata registry to store their data definitions and to perform metadata publishing. The question of where they are on the semantic spectrum frequently arises. To determine where your systems are, some of the following questions are frequently useful. Is there a centralized glossary of terms for the subject matter? Does the glossary of terms include precise definitions for each terms? Is there a central repository to store data elements that includes data types information? Is there an approval process associated with the creation and changes to data elements? Are coded data elements fully enumerated? Does each enumeration have a full definition? Is there a process in place to remove duplicate or redundant data elements from the metadata registry? Is there one or more classification schemes used to classify data elements? Are document exchanges and web services created using the data elements? Can the central metadata registry be used as part of a Model-driven architecture? Are there staff members trained to extract data elements that can be reused in metadata structures? Strategic nature of semantics Today, much of the World Wide Web is stored as Hypertext Markup Language. Search engines are severely hampered by their inability to understand the meaning of published web pages. These limitations have led to the advent of the Semantic web movement. In the past, many organizations that created custom database application used isolated teams of developers that did not formally publish their data definitions. These teams frequently used internal data definitions that were incompatible with other computer systems. This made Enterprise Application Integration and