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David Kuilman | Creating a Semantic Enterprise Content model to support continuous content acquisition, coverage and utility


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David Kuilman | Creating a Semantic Enterprise Content model to support continuous content acquisition, coverage and utility

  1. 1. | Presented By Date David Kuilman 09-08-16 Creating a Semantic Enterprise Content model to support continuous content acquisition, coverage and utility at Elsevier
  2. 2. | Entity cloud to knowledge graph Researchers Institutions Articles Journals Patents Funding bodies Grants Research domains Countries Labs Projects Research data sets Publishing cluster Usage cluster Editors Reviewers Authors Inventors Funding cluster Opportunities Corporations Publishers Conferences Societies Res Eval Agencies Counter
  3. 3. | Implications for a Enterprise Content Model 3 Increase content volume and Quality •Create new content and asset types •Track license agreements •Have multiple editions of quality Expand content coverage •Add classes , add data types, add relationships into non-Journal, non Book materials •Make content management aware of extended content coverage •New content is operational in search , storage , services and discovery Increase content utility •Increase metadata properties for search and discovery •Extend content objects with features that activate interaction •Create data-driven workflows Combine content with analytics and technology •Add properties as diagnostics evolve and mature •Expose meaningful properties now locked in content Drive operational efficiency and effectivity •Empower third parties to contribute and collaborate in high-value ways •On-board content and data suppliers fast •Enable instant adoption of content supply chains
  4. 4. | Content Multiple types Flexible Standar ds- based Discover -able Accessib le Reusabl e Fine- grained Modifia ble Multiple formats Dynamics and Features of content Events Service calls Events Events Service calls Events Service calls Service calls
  5. 5. | Meta-model and content model • Modelled for variety • Two layered model: • Ontology describing a content model typology and inter-dependency • Asset-level content models for fine grained, detailed content mark-up • Realisation through OWL and XML Schema • Serialisation through JSON-LD under JSON Schema control Nodes in the graph organized to: • Support collections of nodes • Record containment to other nodes • Be typed for class membership • Edges in the graph organized to: • support loose- and tightly coupled nodes • Express roles • Capture features • Be fixed and protected • Membership • Containment • Provenance • Be extensible • Node features • Search index Content Type Content Type Content Type property property property ÁssetType ÁssetTypeÁssetType Format Format Format property property property ÁssetType ÁssetTypeÁssetType Format Format Format property property property ÁssetType ÁssetTypeÁssetType Format Format Format property property property CO-CO property CO-CO property MP4 x264 Non RDF RDF
  6. 6. | Generations capture: Grouping, Variants, Versions, Dependencies • Authority type with reference Asset • Workflow state • Provenance • Inter-dependency • Intra-dependency • Containment • Accessibility 6 evolution
  7. 7. | Content Model Ontology 7 Service Call Message AssetObj ect Content Object Generati on Content Object Content Model Asset Object hasGeneration Generation Metadata AssetMeta data hasAssetMetadata hasAsset Message ServiceCall EventNotifi cation service event about Content ObjectD Contributor /Consumer from to parentGenerati onID Content ObjectID AssetObj ectID Resource / target parent about Content ObjectD Service CallID Individual Class Property
  8. 8. | Extending Content Model using named graphs 8 Content Object Conten t Model Asset Object hasGeneration Genera tion Metada ta AssetM etadata hasAssetMetadata hasAsset Messag e Service Call EventN otificati on service event about Conte ntObj ectD Contribu tor/ Consum er from to parentGener ationI DConte nt Object ID Asset Object ID Resource / target parent about Conte ntObj ectD Servi ceCa llID DataType Content Object Literal Datatype CO property Controlled Vocabulary Object type CO property Content Object type CO property Person Institute CO property CO property Corporatio ns Adds-On-To Resear chers Funding bodies Publishing cluster Funding cluster
  9. 9. | Continuous acquisition of Adding value to Content Objects Article Object ADD-ON Object Type: “KnowledgeGraph” ADD-ON Object Type: “Document Graph” ADD-ON Object Type: “n-gram distance” ADD-ON Object Type: “Mapping” XML PDF CAR XML PDF CAR Content Object - Patent - Grant - Concept - Contract - Article - Chapter - ... Generation v1 Generation v2 Resear chers Funding bodies Publishing cluster Funding cluster Integrate and deploy into a knowledge graph JSON-LD serialisation
  10. 10. | Continuous content acquisition, coverage and utility: use cases 10 New User to the System : Add name to the consumer / contributor Class New, unknown content: Add Content type to the Content Object Class New derived asset: Add Asset type to the Asset Class New format: Add new Format type to the Asset Class New property: Add property to the Content or Asset Object Class New datatype: Create a datatype for the Data type Object Class New concept: Add a concept to the Controlled Vocabulary Class New Service: Add a Service Call to Service Call Class New event: Add to EventNotification Class New relationship to other objects: Add Add-On object to Content Object Class
  11. 11. | Versions of content models • New objects can be added • New properties on Content Objects to Content Objects (with ID control) • New properties on Content Objects to literal/CV • New Asset types can be added • New Asset formats can be added • New properties on Asset objects • New asset models can be introduced (schema/json schema) • New Add-On properties can be introduced • New Property to External Content Object (no ID control) 9/29/2016 3 4 1: . :527. Content Object + CO properties Asset Type + Asset properties CO properties Asset Format
  12. 12. | Questions towards versioning • How do I get the difference of the model that I use and the one that is available? • How do I know which Content and Asset types have ben added? • How do I know/discover which properties are available ? • How do I know what add-on types have been added? • How do I understand the impact on produced, integrated graphs? • Do I need to know the nature of the properties?; ie which ontology governs them? 9/29/2016 12
  13. 13. | 9/29/2016 13
  14. 14. | Take aways: Key elements of a dynamic, self servicing content model • Provide authority for identification of objects and assets • Understand and model core assets in context of knowledge graphs • Manage the organisation of both the content objects and the objects themselves; metadata and properties must be able to travel across content object boundaries • Devise a version and variant management system; understand implications for addressing • Extensible to allow new objects, new schemas and new semantics; ontologies with classes and properties lend themselves well for this role • Versioning of content models is expressed through feature availability on Content Objects, Asset Types and distributed properties. • Establish the connection between content model with workflow model • Use JSON-LD for serialisation as a light-weight, extensible format while being conscious of namespaces and RDF data 14