About EKGFEnterprise Knowledge Graph FoundationEKGF_df55553a-22f9-11eb-b0dc-a5fb1383ea00The EKG Foundation is a non-profit trade association established as a coordination body for the knowledge graph community. Knowledge Graph CommunityEXECUTIVESExecutives who seek to realize the benefits (and minimize the risks) of semantic standards and EKG by having access to proven methods, best practices and a community of experts.VENDORSVendors who want to make it easier for organizations across information-intensive industry sectors to understand and successfully adopt their products and services.ARCHITECTSArchitects who want access to reusable components, deployable models, ontologies and interfaces that can be assembled and deployed within their environment.MODELERSModelers who want access to reusable components, deployable models, ontologies and interfaces that can be assembled and deployed within their environment.CONSULTANTSConsultants who are looking for access to EKG-related best practices as well as a community of potential customers and skilled practitioners.ACADEMICSAcademics who are making a meaningful and recognized contribution that builds upon existing frameworks to address pressing business needs.EKGF ORGANIZING TEAMDennis Wisnoskyformer CTO, US Department of DefenseJacobus GelukChief Technology Officer, agnos.aiPete RivettMember, Architecture Board, Object Management GroupMichael AtkinFounder, EDM Council and faculty, Columbia UniversityJeremy PosnerPrincipal, Head of services, agnos.aiSustainable data management in complex and interconnected business environments_df5556d4-22f9-11eb-b0dc-a5fb1383ea00To define best practice and mature the marketplace for EKG adoption_df55579c-22f9-11eb-b0dc-a5fb1383ea00PrinciplesEnterprise Knowledge Graph Foundation Principles -- These guiding principles are intended to provide guidelines for the development and deployment of an enterprise knowledge graph. The principles emphasize shared meaning and content reuse that are the cornerstone of operating in complex and interconnected environments.IdentityPrinciple 1: Identity -- Any given object is identified with at least one universally unique, opaque, permanent, and web-resolvable identifier.MeaningPrinciple 2: Meaning -- The meaning of every data point must be directly resolvable to a machine-readable mathematical definition.DistributionPrinciple 3: Distributed -- An EKG can incorporate any number of datasets of any number of data sources that can be hosted by any number of independent EKG Platforms. Any given access point provides connectivity to the EKG regardless of where it resides.OpennessPrinciple 4: Open World -- Information can vary over time, come from many internal and external sources, and be based on different identities and models. These “multiple versions of the truth” need to be reconciled on access by context.Self-DescriptionPrinciple 5: Self-Describing -- An EKG is composed of a set of self-describing datasets that provide information about lineage, provenance, pedigree, maturity, quality, and governance. The EKG Platform has policy enforcement services that are driven by these self-describing datasets.MeasurementPrinciple 6: Measurement -- The quality and characteristics of the managed knowledge must be measurable and measured. Measurement criteria are used to designate fitness-for-defined-purpose and must be actionable.Use CasesPrinciple 7: Use Cases -- All artifacts around and information in the EKG are linked to defined and prioritized use cases. Nothing in the EKG exists without a known business justification and purpose.ControlPrinciple 8: Control -- Entitlement, privacy, and business policies will be modeled in the EKG and automatically executed, enforced, and audited at the data point level.EcosystemsPrinciple 9: Ecosystem -- An enterprise will use a heterogeneous set of technologies and data sources that will be incorporated into the EKG over time. All components of the ecosystem are subject to service level agreements.StandardsPrinciple 10: Standards -- Both the EKG Platform and knowledge content should be based on open standards. Where necessary, the EKG Foundation will work to expand those standards. STANDARDS Adopt semantic standards to solve the challenges of data management_df5558a0-22f9-11eb-b0dc-a5fb1383ea001PrinciplesDefine guiding principles for the development and deployment of enterprise knowledge graphs_df555968-22f9-11eb-b0dc-a5fb1383ea001.1Principles -- The EKG Foundation has defined a set of guiding principles for the development and deployment of an enterprise knowledge graph. These principles are designed to promote sustainable data management in complex and interconnected business environments. METHOD Develop best practices for accelerated EKG deployment_df555a30-22f9-11eb-b0dc-a5fb1383ea002CatalogEstablish a catalog of best practices for sustainable knowledge graph deployment_df555af8-22f9-11eb-b0dc-a5fb1383ea002.1Maturity Model -- The EKG Foundation is establishing the catalog of best practices for sustainable knowledge graph deployment based on the EKG Maturity Model – a set of criteria for evaluating readiness in EKG environments.ARTIFACTSCurate a repository of reusable models and resources_df555c88-22f9-11eb-b0dc-a5fb1383ea003EKG Portal -- The EKG Foundation will offer curated access to published ontologies, tools, use cases and other resources needed for sustainable knowledge graph operations.OntologiesPublish ontologies_df555d5a-22f9-11eb-b0dc-a5fb1383ea003.1ToolsMake available tools for knowledge graph operations_df555e2c-22f9-11eb-b0dc-a5fb1383ea003.2Use CasesPublish use cases_df555ef4-22f9-11eb-b0dc-a5fb1383ea003.3Other ResourcesShare other resources for knowledge graph operations_df555fd0-22f9-11eb-b0dc-a5fb1383ea003.4COMMUNITYBuild the mechanism for engagement and shared knowledge_df5560ac-22f9-11eb-b0dc-a5fb1383ea004_df556188-22f9-11eb-b0dc-a5fb1383ea00ADVOCACYAdvance the business cases for EKG adoption_df556264-22f9-11eb-b0dc-a5fb1383ea005_df55634a-22f9-11eb-b0dc-a5fb1383ea002020-11-09https://www.ekgf.org/OwenAmburOwen.Ambur@verizon.net