Categories of Vocabulary Compatibility Dmitry Lenkov Oracle.

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Categories of Vocabulary Compatibility Dmitry Lenkov Oracle

Interoperability  Ability of two or more parties to Exchange information about metadata Establish metadata equivalency Exchange and understand metadata (or data about asset) Exchange data (information) or provide service (car delivery) Delivery protocols Messaging protocols Content – syntax and semantics  Interoperability layers

Metadata interoperability  Fundamental for accessing data and services on the Internet Relationships between multiple descriptions in terms of Interoperable (common semantics) vocabularies Single query meaning over descriptions expressed in multiple descriptive formats (vocabularies) Communities of interest based on a set of interoperable vocabularies

Topic subscriptio n generate Subscriptio n metadata valid?validate confirm validate validate store Info valid?valid?generate Info metadat a validaterequestvalid? deliver Use and / or distribute Info yes yes yes no no no no SourceDestination yes Data / Metadata exchange

Interoperability Challenges  Explosion of Standards and Standard Organizations Dozens of standard organizations and standards No coordination No consistency  High cost of multi-end, multi-standard interoperability Development Testing Maintenance Vertical - on the deployment platform Horizontal - on multiple client/server/peer systems  Interoperability dependencies

Interoperability categories  Language level SQL, XML schema and query languages, ontologies Each language provides means to build vocabularies with Syntax to communicate data and Form queries about data  Compatibility of vocabularies Within one language – same XML schema Across languages – DM schema to XML Levels of compatibility – equality, equivalence, comparability

Entity / Data / Asset  Entity Generic term to items such as Cars, applications, books, scientific articles  Entity can be data Online book, document, Information item Digital asset Car, DVD with music or film  Entity can be non-digital asset  Entity has associated metadata in one or more vocabularies

 Distinction between description, query, and filter is purely functional Metadata / Data  Metadata is data about an asset or data It is a set of statements about an asset in one or more vocabularies If an asset is data (information), these vocabularies usually are different from vocabularies expressing data  Metadata can be of three kinds: Description – specifics of an asset or data Query – short term expression of interest Filter (subscription) – long term expression of interest

Vocabularies  Vocabulary Set of terms representing classes of entities, or instances Includes data types model, if any  Taxonomy Set of relations between classes of entities Relations - Subsumption, instantiation, equivalence Is a vocabulary with non-empty taxonomy and a set of constraints in the associated constraint language  Ontology

Data and Metadata Hierarchy Entity (asset) Descriptions / QueriesVocabulary Descriptions / QueriesVocabulary describe for describe data/metadata

Vocabulary Equivalence - Example  Example: Equal vocabularies (A & B) Same terms, same data type model, same taxonomy Is it enough to say that they are equal? – NO!  Evaluate vocabulary metadata Is the same vocabulary C used for A’s and B’s metadata? Yes, evaluate A’s and B’s metadata – same constraints, conversion (XSLT: A to B), set of synonyms, etc. - ? Recursion – apply the process to A’s & B’s metadata vocabularies  No, different vocabularies - for A’s & B’s metadata

Vocabulary Equivalence  Vocabularies A and B are equivalent if A’s and B’s metadata are specified in the same vocabulary C and A’s and B’s metadata specify same set of constraints and/or a conversion (XSLT A to B, taxonomy mapping, etc.) and/or a set of synonyms, etc.  else if for A’s and B’s metadata vocabularies C and D correspondingly are used and  Vocabularies C and D are equivalent and A’s and B’s metadata satisfy condition

Comparable vocabularies  Vocabularies with equivalent subsets How to deal with it Default values or instances Optional fields and partial evaluation  Examples Vocabulary evolution and versioning Independent creation for the same purpose and the same semantics

Mediation vs. Pear-to-pear  Mediation There is a set of (standard) vocabularies supported by a mediator Vocabularies of all communicating parties should be equivalent to one or more vocabularies in the mediator set  Pear-to-pear Vocabulary equivalence is on a pear-to-pear basis Greater effort for each pear Higher degree of flexibility, independence, and trust

A Q & Q U E S T I O N S A N S W E R S