Semantic Modeling for Information Federation
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The document discusses the importance of conceptual modeling and semantic mediation in integrating various information representations across different contexts. It emphasizes the need for common concepts, mapping rules, and an understanding of how diverse syntaxes represent those concepts, which enables automation and effective communication among stakeholders. Furthermore, it explores the necessity of frameworks like SMIF for semantic interoperability and the challenges posed by different representations in the realm of data and technology.
![What is a threat actor? (FBI)
The Federal Bureau of Investigation has identified three categories
of cyber threat actors:
“ [1] organized crime groups that are primarily threatening the
financial services sector, and they are expanding the scope of their
attacks; [2] state sponsors — foreign governments that are
interested in pilfering data, including intellectual property and
research and development data from major manufacturers,
government agencies, and defense contractors; and [3] increasingly
there are terrorist groups who want to impact this country the
same way they did on 9/11 by flying planes into buildings.They are
seeking to use the network to challenge the United States by
looking at critical infrastructure to disrupt or harm the viability of
our way of life.[1]](https://image.slidesharecdn.com/semanticmodelingforfederation-171011222434/85/Semantic-Modeling-for-Information-Federation-15-320.jpg)
![Last years Ontology Summit focused on “Ontologies within Semantic
Interoperability Ecosystems ”. Full document: http://tiny.cc/Ontolog2016
Supports the value proposition of SMIF
• “The United States spent nearly $3.0 trillion on healthcare in 2014 [ . . . ] the efficient
use of health information technology will result in considerable cost savings, in addition
to saving thousands of lives per year”.
Supports the need for capabilities not currently provided, focused on
semantic interoperability
• "More mature conceptual modeling & knowledge engineering tools are required to
support the design, development and storage of ontologies and vocabularies. [ . . .
] these should be integrated into software development and data management tools
that provide support across the IT lifecycle and related operations.“
• "There was broad consensus within the Summit that improved software tools and
environments are required to support the integration of concepts and data."
Ontology Summit: Semantic
Interoperability Communique](https://image.slidesharecdn.com/semanticmodelingforfederation-171011222434/85/Semantic-Modeling-for-Information-Federation-22-320.jpg)
Semantic Modeling for Information Federation
- 1. Cory Casanave Copyright © 2017 Model Driven Solutions Licensed as creative commons, share-alike https://creativecommons.org/licenses/by-sa/4.0/legalcode
- 2. To relate different representations of the same things, we need to understand • What are the common concepts • How do the various information syntaxes represent those concepts • What are the rules for translating between them in various context Semantic Mediation Reference Concepts Information Syntax RepresentsInformation Syntax Information Syntax Conceptual Model Mapping Rules Information Model
- 3. Leveraging Federated Information T Reference Concepts Information Syntax RepresentsInformation Syntax Information Syntax Conceptual Model Mapping Rules Information Model
- 4. Modeling Concepts are the meta-concepts we use to build our models Raising the level of abstraction Conceptual models need not be limited to computational paradigms • E.g. OWL-DL is limited by FOL, DL and unary “properties” (no relations) Examples of modeling concepts (more detail below) • Context • First-class n-ary relationships • Roles and phases • Temporal friendly “situations” and relationships Note: Ontology does not mean “OWL-DL”, Ontology is about conception of the world(s). Note also that the above can be “painted over” OWL and UML with patterns. High-Level Modeling Concepts
- 5. • Linked Data • Ontologies (e.g. OWL) • Rules • Traditional DBMS / SQL • Big Data • NoSQL • Traditional APIs and applications (e.g. Java) • Functional Programming • ETL / Data Wearhouse • Publish/Subscribe • SOA • Application and web servers Multiple technologies can be leveraged, integrated and combined based on the same conceptual models using model driven architecture MultipleTechnologies
- 7. What are the requirements for conceptual modeling in support of federation?
- 8. Role of the interpreter
- 9. Retention of meaning across languages, communities and cultures Communicate what is said without judging, coloring or filtering it Interpreters have substantial preparation, learning syntax, grammar, vocabulary and cultural idioms. Interpreters can only communicate what they understand and what can be understood in the languages they deal with – the common concepts They then communicate what other people said based on how those concepts are expressed in different languages – they communicate the provenance Interpreters are preforming semantic mediation What we expect of interpreters Common concepts
- 10. Understandable and precise Capture, disambiguate and precisely describe stakeholder concepts such that they can enable automation. Represent these concepts so stakeholders can understand and validate them.
- 11. Semantic mediation does • Capture shared concepts, this includes types, relationships, individuals and other concept kinds • Define a relationship between patterns of these concepts and patterns of data representations – it is not a word for word translation • Respect the context of the concepts and rules • Maintain the provenance of information Semantic mediation does not • Define applications that produce or consume information • Assert policy about what is “right”, “common” or “legal” • Structure information for an application perspective • Filter for “data quality” Implications for the role of semantic mediation (conceptual reference models)
- 12. Conceptual models and mappings, intended for the federation role • Should use stakeholder relevant terms and concepts presented in an understandable way • Should have minimal commitment – only committing to what is necessary to understand and “map” information. E.g. specific units or data representations • Should keep application specifics out of the concepts – how the information is developed is not our concern. • Should contain both the “most generic” sense of a concept as well as any specialization required (and named appropriately) for precise communications • Mappings should be able to be “mixed and matched” with multiple concept modules based on context • Should only contain semantics that have a “ROI” for federation. • E.g. should not be implementing “application rules”, it is up to the “end applications” to enforce rules prior to mediation Conclusion: Conceptual models for federation may be a subset of (simpler than) conceptual models or operational ontologies intended for applications.Their semantics only need to support the mapping rules for representations. Implications for SMIF
- 14. Is this a threat actor? (STIX) STIX is a large XML Schema
- 15. What is a threat actor? (FBI) The Federal Bureau of Investigation has identified three categories of cyber threat actors: “ [1] organized crime groups that are primarily threatening the financial services sector, and they are expanding the scope of their attacks; [2] state sponsors — foreign governments that are interested in pilfering data, including intellectual property and research and development data from major manufacturers, government agencies, and defense contractors; and [3] increasingly there are terrorist groups who want to impact this country the same way they did on 9/11 by flying planes into buildings.They are seeking to use the network to challenge the United States by looking at critical infrastructure to disrupt or harm the viability of our way of life.[1]
- 16. Is this a threat actor? Threat Actor? Our conclusion:Only the “real world” perspective can provide a pivot point between different representations. Instances of a conceptual “threat actor” are real threat actors, not data about them as data is structured for its application purpose.
- 17. What is a threat actor? (Threat Model)
- 18. Data represents concepts Represents Model Representation
- 19. Example of Mapping Pattern (UML Profile)
- 20. SMIF Components – conceptual models and mappings to schema Conceptual Modeling UML Profile Mapping UML Profile Schema ProfileDependsOn MapTo SMIF Conceptual Metamodel Mapping Metamodel SMIF Information Metamodel DependsOn MapTo Represents SMIF Conceptual Meta Model UML Representation Represents Represents
- 21. As easy as possible for domain stakeholders to understand the models as diagrams, tables or text “First class” n-ary relationships that may have properties and participate in other relationships Recognition and representation of time and context – most relationships are only true for a limited time and in specific situations Roles, phases and other “non rigid” classifications that also may be time or situationally dependent Hierarchies of types, relationship types and properties Business values as represented by various systems of units Patterns as a basis for real-world situations as well as mapping rules Note that while some of these features may be difficult for generic FOL reasoners, they are practical for specific conceptual model and mapping rules Important conceptual modeling and mapping capabilities
- 22. Last years Ontology Summit focused on “Ontologies within Semantic Interoperability Ecosystems ”. Full document: http://tiny.cc/Ontolog2016 Supports the value proposition of SMIF • “The United States spent nearly $3.0 trillion on healthcare in 2014 [ . . . ] the efficient use of health information technology will result in considerable cost savings, in addition to saving thousands of lives per year”. Supports the need for capabilities not currently provided, focused on semantic interoperability • "More mature conceptual modeling & knowledge engineering tools are required to support the design, development and storage of ontologies and vocabularies. [ . . . ] these should be integrated into software development and data management tools that provide support across the IT lifecycle and related operations.“ • "There was broad consensus within the Summit that improved software tools and environments are required to support the integration of concepts and data." Ontology Summit: Semantic Interoperability Communique
- 23. SMIF Implementation for information federation, sharing and analytics Status: PoC Federation Engine tm
- 24. Prototype model & semantics implementation preview “SMIF Full” RDF Repository SMIF UML Models SMIF Java API UML Facet Eclipse UML Java Facet RDF/OWL Facet Rules SW Rules Facet SQL Facet XML Facet “Flat” Facet Planned API Generated from SMIF Model CL/IKL Facet Each facet provides an adapter between external data and a SMIF counterpart at any meta-level. A SMIFObject may have multiple facets. Mappings & federations are (conceptually) between SMIF objects. Analytics Implements SMIF Semantics as Java code XMI Facet
- 25. Java API for any SMIF model (Including those imported from other sources) Production of “SMIF Full” RDF/OWL and rules Bi-directional data mapping – SQL, XML, OWL Semantic mapping between data repositories User definable rules in SMIF or Java Projection to “tabular” data formats for analytics engines Full support for multiple inheritance and multiple classification All of the above for FIBO, Concept Library and Threat/Risk Capabilities (In Progress)
- 26. Using the SMIF UML profile – one projection of the SMIF model
- 27. Entities & Facets Propositions FoundationalConceptualTools (Meta-Concepts) Characteristics Associations (Always true between entities) Relationships (Independent/Contextual) Rigid (Entity)Types Roles Phases
- 28. • Reference models are conceptual, information models are application specific • Multiple inheritance & multiple (instance) classification is required • A type can have multiple Supertypes • A thing may have multiple types, these types may change over time and in differing context • Everything has metadata – source (including derivations), provenance & timeframe • Things change – time matters (the world is not static or a snapshot) • E.G. Relationships, situations and characteristics are temporal • Information is contextual (the world is not first order) • Statements are not “deleted”, they go in and out of context (Allows functional) • The world is open, conclusions (computations) are contextual • Trust in information varies, not everything that can be inferenced should be • Independence from representation (e.g. schema) and processing technologies (including inference engines) • But, we can bind to any of these technologies Type Based ModelTheory
- 29. Roles define what something is for or how it behaves in a certain context, not “what it is”. A role is a <<Facet Of>> what it can be a role of. An entity can play any number of roles and these roles may change over time. Roles can be contextual and specialize other roles Roles are usually established by relationships Roles
- 30. Phases (or states) are classifications of objects over their lifetime. A “Relative thing” Examples: Child,Teenager, Adult or Invoiced, Late, Paid May be combined with other types using unions and intersection (e.g. teenage driver) Phases
- 31. Relationships are meaningful atomic concepts involving a set of other entities or relationships. A “Mediating thing”. There can be any number of related “ends”, but two ends is most common Relationships are atomic & static “Situations”, the involved ends do not change over the lifetime of the relationship. The context and “truth value” of the relationship may change. Relationships are temporal – exist for a timeframe. The timeframe of a relationship may or may not match the timeframe of the “ends” Relationships may be involved in other relationships and may have characteristics We refer to these independent relationships as “first class” relationships. Relationships
- 32. Modeling with first class roles & relationships (Note that relationships can be temporal – be “true” only for a time period)
- 33. Associations are similar to relationships but: • Not “first class” • Not temporal – they exist for the lifetime of the related “ends” • Limited to binary • Also known as “Formal Relations” • Map most directly to simple properties (e.g. OWL or Java) Associations
- 34. Characteristics are features inherent in another type Most like “properties” in many languages Usually have a value type as their range John has a weight of 60 KG Characteristics are temporal (have a timeframe) & identifiable John weighed 60kg on March 3rd, 2011 In conceptual reference models quantity kinds (e.g. Mass) are preferred over specific units (e.g. kg) or data types (e.g. “Real”) as the types of characteristics Characteristics
- 35. Properties encompass the “ends” of associations and relationships, and characteristics Like everything else – properties have types (property types) and instances (called bindings) Properties can be specialized and restricted Models typically define property types Specialized properties may be “virtually derived”, not define a new concept but restrict an existing one. These have no name or the same name as their super-property Property specialization is either a “subset” or redefines (equivalent set) Specializing properties
- 36. Subset properties define subtypes of other property types (ends of associations or relationships, characteristics, etc). Extent of subset property is a subset of super-property May tighten constraints – multiplicity, type, etc. Subset properties
- 37. Redefined properties define subtypes of other property types (ends of associations or relationships, characteristics, etc) and replace the super- property in the given context. Extent of redefined property is the same as the extent of super-property May tighten constraints – multiplicity, type, etc. Redefined Properties Restriction Example
- 38. Disjoint defines a set of classifications that can never be combined in the same thing. • e.g. you can’t have a cat/dog Complete defines that a set of things can’t have any more members. Incomplete says there can be more in a set. • Certainly there are more kinds of animals than cats and dogs. Incomplete and Disjoint Note: Disjoint may also use a dependency
- 39. It is essential that we understand what quantities represent . For numeric characteristics, we want to know what it means (e.g.Temperature), not the kind of number (Real). <<Quantity Kind>> is an aspect common to mutually comparable quantities represented by one or more units. A “unit value” represents a quantity kind, there are multiple units representing temperature. A physical representation would then represent the unit as some kind of number in a specified unit. Quantity Kinds & Units
- 40. Situations contextualize one or more propositions – relationships, associations, characteristics or rules Situations are “mediating things” Situations are temporal Relationships are atomic situations Situations types / patterns and individuals may be defined Situations may be • Static or dynamic • Past, present or possible future Situations
- 42. Situations capture “truth” in context (any such truth is subject to trust and likelihood)
- 43. Models may be organized into packages (sub-graphs) and reference or assert other packages Model Organization
- 44. Expressions • Define computations Patterns • Define sets of entities and relationships with variables, acts as a type. • May be asserted for a type or context • Used as the basis for mapping • In UML, uses structured classifiers Rules • Define constraints or implications for a context. E.g. Multiplicity. Mapping Rules • Defines how an information model relates to a conceptual reference model • Based on pattern matching • Multiple mappings are combined to federate or translate information AdditionalCapabilities, not detailed here
- 45. SMIF provides a framework for defining a semantic model In the general sense of the word, this is an “Ontology” Tools can generate ontologies in various languages, such as OWL As the focus of SMIF is federation and integration, not general inference, there are some differences • SMIF allows things some ontology languages do not – context, “second order” relationships and time. • It includes higher level concepts such as first-class relationships, roles and phases • It does not include some capabilities of first order logic, it does not provide for general inferencing based on arbitrary expressions SMIF is a good match for the “semantic web” and linked data Semantics and SMIF
- 47. The concept library is defined in and specializes SMIF, it is not defined as part of SMIF. Concept libraries are open source. These are candidate concept – refinements and alternatives are welcome. https://github.com/ModelDriven/ConceptLibraries/ SMIF Concept Library DefinedUsing Extends Domain Concept Models Extends Application Model References
- 48. To facilitate cross domain and cross system interaction, we must have concepts common across those domains and systems We know they will be represented differently and may have different purposes, but we must understand what things mean We should be reusing concepts rather then building new stovepipes There will never be “one true” concept set, but we can define concepts for broad use and acceptance Concepts are introduced as: • They are needed in a domain of interest • They are an abstraction of one or more concepts needed to fully define another concept Concept Library Principles
- 50. Identifiers
- 51. Values Meta
- 53. SocialAgents
- 54. Persons
- 55. PhysicalEntities
- 56. Places
- 57. Organizations
- 61. Occurrences
- 62. Process(Base)
- 63. Containment
- 66. Control
- 67. Resource
- 69. Corporations
- 70. Objectives
- 71. Assessments
- 72. Policy
- 73. Quantity Kinds
- 75. Common Units (2)
- 76. The above models were done with two “profiles” of UML. Profiles specialize UML for a specific purpose.
- 77. Any UML tool can be used with the SMIF profile Our preferred tool is Magicdraw® The “Concept modeler” can produce and consume OWL ontologies based on conceptual models ModelingTools
- 80. http://www.modeldriven.com https://github.com/ModelDriven/SIMF/ https://github.com/ModelDriven/ConceptLibraries/ SMIF is an “standard in progress” in the Object Management Group (omg.org) It is currently being used and implemented