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The semantic requirements provide a framework for a detailed description of services in the architecture section. This section presents the requirements derived as a result of the requirements analysis of the use cases presented in previous section. The analysis includes tracing of requirements for semantic infrastructure are defined as they relate to the architecture, use cases, and stakeholders. This section presents those requirements with tracing up to the use case cases and stakeholders and down to the service capabilities specified later in this document. Note that the requirements Note this section is not complete and this section an exhaustive list of requirements and is expected to evolve as additional requirements are addedanalyzed and defined.
This section includes the following:
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Artifacts include support for different formats of models, both static and dynamic. Artifact management also includes the ability to manage content and clinical forms. A service specification is made up of service metadata, artifacts and the metadata supporting these artifacts. Artifact management primarily deals with managing artifact lifecycle and authoring of artifact metadata.
Static Models
Static models include a variety of models with different representations. Static models include but are not limited to:
- Schemas
- XML, OWL, RDF
- Information Models
- UML, HL7 MIF, 11179
- Meta Models
- HL7 RIM
- BRIDG
- LS-DAM
- Transforms
- OMG Ontology Definition Metamodel Tranforms
- Model Constraints
- OCL, Schematron
- Data Types
- ISO 21090/HL7 R2
- HL7 R1
- Primitives
Behavioral Models
In the context of this paper, behavioral dynamic models capture the behavior of services. Behavior of services provides an unambiguous definition of the service constraints, capabilities, dependencies and interactions. The metadata and grammar required to realize service behavior is called behavioral semantics. Behavioral semantics provide a mechanism for better service discovery and enforcing the constraints at design and runtime.
Dynamic models include but are not limited to:
- HL7 SAIF behavioral model (which provides a formal model and grammar for service contracts)
- Orchestrations and Workflows
- Business Rules
Content
Content includes all unstructured text and other forms of content that make up a service specification. Examples include storyboards, and scope. Content is an integral part of service specification, and content is leveraged across the enterprise for documentation and communicaitons. Content includes:
- Service specification content, primarily unstructured text
- Images and other representations of static content
Forms
Forms include CDISC Operational Data Model (ODM), HL7 Clinical Document Architecture (CDA) documents, and HL7 Version 3 RIM derived forms. This includes all aspects of the document including the style, definitions and semantics.
- Form Templates
- Reusable Form Sections
- Form Definitions
Specification Content
The National Cancer Institute has created many specification documents which include extended datatype flavors for the iso-21090 datatypes as well as the ECCF specifications for the behavioral framework, information framework, and governance framework. The specifications are an integral part of the semantic infrastructure, allowing the user to fully understand and appropriately apply the many artifacts stored in the ECCF registry.
Artifact Management Functions
Artifact lifecycle management and metadata requirements include the ability to:
- Manage lifecycle, governance and versioning of the models, content and forms
- Establish relationships and dependencies between models, content and forms
- Determine provenance, jurisdiction, authority and intellectual property
- Create representation and views of the information, realized through the appropriate transforms
- Provide access control and other security constraints
- Create annotations for better discovery and searching of artifacts
- Develop usage scenarios and context for the information
- Provide terminology and value set binding
- Provide rules and algorithms for the use of the artifacts in a particular service
The artifacts are bound to the services via the service metadata. The service metadata combined with the artifacts and supporting metadata provide a comprehensive service specification.
The artifact management requirements listed above are derived from the following use cases:
Electronic Health Records: The caBIG® Clinical Information Suite project has adopted ECCF for specifications and CDA documents for interoperability. Project requirements include the need for an infrastructure for managing all the artifacts generated during specification process, including HL7 models and documents. The project also intends to publish these artifacts for the community and vendors. The infrastructure must support better discovery, making all the relevant information available in the right context.
ONC and other external EHR adopters: ONC has adopted CCD and CCR for meaningful use. All national EHR implementations are expected to support forms and the semantics of these forms play a critical role in interoperability. The semantic infrastructure must provide a mechanism to create, store and manage these forms.
Clinical Trials: Clinical trials use forms to capture clinical information, and the semantics captured by these forms are critical for interoperability and reporting. The semantic infrastructure must provide a mechanism to manage the lifecycle of these forms.
Service Discovery and Governance
Service discovery and governance allows service developers to specify rich metadata about services. This enables better discovery, and governance of services. Service discovery and governance help to accomplish the following.
Promote Service Reuse: The use of well defined service metadata promotes better discovery and reuse of services during design and run time. Service metadata includes information about service interactions and dependencies. It also includes a classification scheme for organizing services based on business objectives, domain, and usage. It also links services to all the supporting artifacts in the specification and provides a placeholder for conformance statements. This enables better reuse across the enterprise and eliminates redundancy.
Establish Service policies: Service policies help establish constraints on the service specifications and mandate an approach. Policies can be specified around governance, access control and other design and runtime constraints.
Provide Governance: This includes predefined templates, workflows, and governance policies for governing the service lifecycle as well as an approval and review process for service specifications and the ability to promote services through the stages of the service lifecycle.
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Improve visibility through publication. By providing a service which can be integrated into the development/testing/production cycle, artifacts become available for review and discussion, as well as reference for supporting development. This helps insure proper understanding of applications and services being developed, and provides a standard and controlled method of access.
Annotated artifacts to expand understanding. To further improve the understanding of artifacts, the management service provides the ability to add annotations to both the parts of an artifact (depending on artifact type) and the artifact as a whole. Adding additional semantic definitions to an artifact allows for the searching and location of elements across artifact type, as well as make clear the intent of a given artifact.
Support for Governance. By allowing for artifact versioning, along with state representation, artifact elements which require governance can be located and interacted with. This functional aspect of the artifact management provides a change history as well as links to external change control systems.
Types of Artifacts
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Static Models
...
Static models include a variety of models with different representations. Static models include but are not limited to:
- Schemas
- XML, OWL, RDF
- Information Models
- UML, HL7 MIF, 11179
- Meta Models
- HL7 RIM
- BRIDG
- LS-DAM
- Transforms
- OMG Ontology Definition Metamodel Tranforms
- Model Constraints
- OCL, Schematron
- Data Types
- ISO 21090/HL7 R2
- HL7 R1
- Primitives
...
Behavioral Models
...
In the context of this paper, behavioral dynamic models capture the behavior of services. Behavior of services provides an unambiguous definition of the service constraints, capabilities, dependencies and interactions. The metadata and grammar required to realize service behavior is called behavioral semantics. Behavioral semantics provide a mechanism for better service discovery and enforcing the constraints at design and runtime.
Dynamic models include but are not limited to:
- HL7 SAIF behavioral model (which provides a formal model and grammar for service contracts)
- Orchestrations and Workflows
- Business Rules
...
Content
...
Content includes all unstructured text and other forms of content that make up a service specification. Examples include storyboards, and scope. Content is an integral part of service specification, and content is leveraged across the enterprise for documentation and communicaitons. Content includes:
- Service specification content, primarily unstructured text
- Images and other representations of static content
...
Forms
...
Forms include CDISC Operational Data Model (ODM), HL7 Clinical Document Architecture (CDA) documents, and HL7 Version 3 RIM derived forms. This includes all aspects of the document including the style, definitions and semantics.
- Form Templates
- Reusable Form Sections
- Form Definitions
...
Specification Content
...
The National Cancer Institute has created many specification documents which include extended datatype flavors for the iso-21090 datatypes as well as the ECCF specifications for the behavioral framework, information framework, and governance framework. The specifications are an integral part of the semantic infrastructure, allowing the user to fully understand and appropriately apply the many artifacts stored in the ECCF registry.
Artifact Management Functions
Artifact lifecycle management and metadata requirements include the ability to:
- Manage lifecycle, governance and versioning of the models, content and forms
- Establish relationships and dependencies between models, content and forms
- Determine provenance, jurisdiction, authority and intellectual property
- Create representation and views of the information, realized through the appropriate transforms
- Provide access control and other security constraints
- Create annotations for better discovery and searching of artifacts
- Develop usage scenarios and context for the information
- Provide terminology and value set binding
- Provide rules and algorithms for the use of the artifacts in a particular service
The artifacts are bound to the services via the service metadata. The service metadata combined with the artifacts and supporting metadata provide a comprehensive service specification.
The artifact management requirements listed above are derived from the following use cases:
Electronic Health Records: The caBIG® Clinical Information Suite project has adopted ECCF for specifications and CDA documents for interoperability. Project requirements include the need for an infrastructure for managing all the artifacts generated during specification process, including HL7 models and documents. The project also intends to publish these artifacts for the community and vendors. The infrastructure must support better discovery, making all the relevant information available in the right context.
ONC and other external EHR adopters: ONC has adopted CCD and CCR for meaningful use. All national EHR implementations are expected to support forms and the semantics of these forms play a critical role in interoperability. The semantic infrastructure must provide a mechanism to create, store and manage these forms.
Clinical Trials: Clinical trials use forms to capture clinical information, and the semantics captured by these forms are critical for interoperability and reporting. The semantic infrastructure must provide a mechanism to manage the lifecycle of these forms.
Service Discovery and Governance
Service discovery and governance allows service developers to specify rich metadata about services. This enables better discovery, and governance of services. Service discovery and governance help to accomplish the following.
Promote Service Reuse: The use of well defined service metadata promotes better discovery and reuse of services during design and run time. Service metadata includes information about service interactions and dependencies. It also includes a classification scheme for organizing services based on business objectives, domain, and usage. It also links services to all the supporting artifacts in the specification and provides a placeholder for conformance statements. This enables better reuse across the enterprise and eliminates redundancy.
Establish Service policies: Service policies help establish constraints on the service specifications and mandate an approach. Policies can be specified around governance, access control and other design and runtime constraints.
Provide Governance: This includes predefined templates, workflows, and governance policies for governing the service lifecycle as well as an approval and review process for service specifications and the ability to promote services through the stages of the service lifecycle.
Enable Better Discovery: Complex search offers a natural and user-friendly way to find services by progressively refining search results using a variety of criteria including attributes, artifacts, classification, usage scenarios, and dependencies. This includes runtime contract discovery, a powerful query mechanism that allows either the service orchestrator or a program to find the services that best fit the requirements of a given process. This increases both runtime and design time flexibility by enabling selection of services based on computable metadata.
Service Discovery Functions
- Identify service endpoint for analysis
- Identify service directory endpoint for analysis
- Extract service interface
- Annotate service interface providing undiscovered features or behaviors
- Manage lifecycle, governance and versioning of the service Interfaces
The requirements listed above are derived from the following use cases:
Electronic Health Records: The caBIG® Clinical Information Suite project is developing service specifications and lacks the infrastructure to govern these services. Vendors and external implementations are expected to leverage the caBIG® Clinical Information Suite service specifications and there is currently no infrastructure that allows easy discovery and consumption of this information.
CBIIT Projects: CBIIT has adopted SOA. Service lifecycle management and governance are industry best practices for all organizations adopting SOA. Better service discovery and reuse improves productivity, avoids redundancy and makes it easier for the CBIIT enterprise architecture governance team to manage NCI's enterprise services portfolio.
Life Sciences: Service discovery based on a rich metadata and semantics of the underlying data play a critical role in developing research pipelines. Research pipelines are developed by connecting data and analytical services together to achieve a research objective.
Other National Initiatives: All EHR vendors and national initiatives rely on a services paradigm for integration and interoperability. A standardized services metamodel makes it easier for participating organization to discover and reuse services.
caGRID 2.0 Platform: The caGRID 2.0 Platform provides a runtime registry for service discovery. This service registry relies on a small subset of information for discovery. The semantic infrastructure provides a mechanism to leverage rich service and artifact metadata to extend this capability.
Clinical Data Forms Definition and Modeling
Clinical Data Forms are the primary channel for capturing information in the healthcare and clinical domain. Forms also play a key role in information exchange and are critical to supporting interoperability in healthcare.
Define data entry forms using robust data representation. Ultimately the data that is captured on a form is used in many ways, but that data must provide a high level of meaningful use to insure the consumer knows how the data was capture and what context it represents. In this way even a simple question on a form may result in a much more complex representation in the data. As an example, a Yes or No question on a form may result in a codified representation of an observation.
Reuse of contextual representation. Since a given form my collect data for a context that might be common to many forms, being able to reuse these elements in a way that insures contextual consistency is a must. Forms created with the form definition tool, must retrieve access from well defined metadata sources that provide common contexts, default values, and coded representations including value set binding.
Reuse of form elements. When defining a form element which is bound to a specific contextual representation, it should be easy to reuse that element with minimal reconfiguration.
Provide Governance support. Forms and the supporting schemas need to be versioned as well as support the governance workflows. This insures that documentation follows a consistent and planed use.
A form differs from a document, in that a document is used to capture information, while a form defines skip patterns, validation rules, and other aspects required to capture or render information for a document.
A document in this context is specifically a clinical document which represents information about a clinical activity. The document contains the specific information gained during that clinical activity and supports the broader definitions of a document. Documents can be transformed into human readable forms, and be transferred or transmitted for use across different systems.
Clinical Data Forms Functions
- Define CMET or CMET like objects for reuse
- Define form
- Bind value set to data element
- Provide default form delivery
- Provide form data transformation
- Manage lifecycle, governance and version of forms and document schemas.
Based on the use cases the key forms requirements include:
- Tools and services for defining form templates
- Ability to leverage models and reusable segments for defining these forms
- Ability to bind terminology in the form of value sets to form controls
- User friendly tools that hide the complexity of the underlying semantics
The requirements listed above are derived from the following use cases:
Electronic Health Records: The caBIG® Clinical Information Suite project is developing service specifications and lacks the infrastructure to govern these services. Vendors and external implementations are expected to leverage the caBIG® Clinical Information Suite service specifications and there is currently no infrastructure that allows easy discovery and consumption of this information.
CBIIT Projects: CBIIT has adopted SOA. Service lifecycle management and governance are industry best practices for all organizations adopting SOA. Better service discovery and reuse improves productivity, avoids redundancy and makes it easier for the CBIIT enterprise architecture governance team to manage NCI's enterprise services portfolio.
Life Sciences: Service discovery based on a rich metadata and semantics of the underlying data play a critical role in developing research pipelines. Research pipelines are developed by connecting data and analytical services together to achieve a research objective.
Other National Initiatives: All EHR vendors and national initiatives rely on a services paradigm for integration and interoperability. A standardized services metamodel makes it easier for participating organization to discover and reuse services.
caGRID 2.0 Platform: The caGRID 2.0 Platform provides a runtime registry for service discovery. This service registry relies on a small subset of information for discovery. The semantic infrastructure provides a mechanism to leverage rich service and artifact metadata to extend this capability.
Clinical Data Forms Definition and Modeling
Clinical Data Forms are the primary channel for capturing information in the healthcare and clinical domain. Forms also play a key role in information exchange and are critical to supporting interoperability in healthcare.
A form differs from a document, in that a document is used to capture information, while a form defines skip patterns, validation rules, and other aspects required to capture or render information for a document.
A document in this context is specifically a clinical document which represents information about a clinical activity. The document contains the specific information gained during that clinical activity and supports the broader definitions of a document. Documents can be transformed into human readable forms, and be transferred or transmitted for use across different systems.
Based on the use cases the key forms requirements include:
- Electronic Health Records
- ONC and Other external EHR adopters
- Clinical Trails
Decision Support and Reasoning
One of the primary reasons for having structured data is to provide the ability to automate decision support and reasoning across information models, data types, and the terminology associated with the attributes of each data type. For the ECCF registry to provide maximal value to end users, it is necessary to support common decision support functions across the enterprise and to extend that through services to the end users. In effect the semantic infrastructure must provide the tools to support Decision Support solutions.
Identify sources of valued information. Using the semantic metadata as a source, reasoning systems need to be able to identify the sources of information which are key to a given decision support solution. The services, models, and annotations provide definitions which can identify candidate sources for integration.
Common representations and transformations. To make decision support services viable, it is necessary that information be consistent and provide the ability to transform data for use in various tools and reasoning solutions.
Support for classification. The system provides for data classification, discovering new knowledge about key elements. This classification process is based on description logic and business rules which process the semantic structures of artifacts. Classification information should be added to the pool of knowledge about given structures and related information
Support for expert system rule processing and choreography. Using systems such as the OWL classifiers (Pellet, Fact++, Hermit), rule based expert systems (Jess, Drools), and work with RDF choreography languages (SPIN), the decision support system should be able to applied in a choreographed layered fashion. Key to this process is a choreography engine which matches data with rules and a reasoning environment.
Integration with Service Registries. Since the artifact metadata provides definitions of data, the service registry provide the data access needed to process information. If a given artifact is a service, the decision support system determines the necessary definitions to integrate a service into decision support for the gathering of data.
Decision Support Functions
- Query artifact metadata to locate useful artifacts for decision support.
- Query service metadata to locate services matching artifacts and metadata definitions
- Create a decision support definition
- Create a decision support session
- Provide scheduling and access information to choreographer
- Selection of rules and rule system environment
- Execution of reasoning systems against gathered data providing classification and additional data
- Tools and services for defining form templates
- Ability to leverage models and reusable segments for defining these forms
- Ability to bind terminology in the form of value sets to form controls
- User friendly tools that hide the complexity of the underlying semantics
The requirements listed above are derived from the following use cases:
- Electronic Health RecordsONC and Other external EHR adoptersRecords
- Clinical Trails
Decision Support and Reasoning
One of the primary reasons for having structured data is to provide the ability to automate decision support and reasoning across information models, data types, and the terminology associated with the attributes of each data type. For the ECCF registry to provide maximal value to end users, it is necessary to support common decision support functions across the enterprise and to extend that through services to the end users.
Decision support services and the analytics that resolve to those services depend upon the metadata present in the ECCF registry and the relationships instantiated between objects in the registry.
To support the decision support functions of the ECCF registry, reusable rules are part of the artifacts that need to be stored in the registry and linked to specific services.
The requirements listed above are derived from the following use cases:
- Electronic Health Records
- Clinical Trials
Conformance Testing
Services specifications developed by NCI and the community have to be testable to ensure that the implementation conforms to the specification.
Conformance testing leverages the artifact and service metadata to validate that an implementation adequately addresses the requirements stated in the service specification. An example of service requirement is the ability to specify a response time in the specification (design time) and validate that this response time is valid for an implementation of the service. Aadditional test points include but are not limited to binding to specific terminologies and domain models.
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- Trials
Conformance Testing
Services specifications developed by NCI and the community have to be testable to ensure that the implementation conforms to the specification. Conformance testing leverages the artifact and service registries along with predefined reasoning systems to validate that an implementation adequately addresses the requirements stated in the service specification. An example of service requirement is the ability to specify a response time in the specification (design time) and validate that this response time is valid for an implementation of the service. Aadditional test points include but are not limited to binding to specific terminologies and domain models.
Conformance testing allows both CBIIT and other HL7 SAIF adopters to validate specifications.
Analyse a given artifact for it's stated ECCF purpose. Determine if a given artifact satisfies the requirements of the ECCF artifact that it declares itself to be. This analysis should look at such things as datatypes matching the appropriate level (abstract data types in a PSM).
Analyse a given artifact to verify traceability. Determine if a given artifact provides correct traceability from level to level. The analysis should look at naming conventions and stereotypes to determine correctness along with promotion of data types from different levels of abstraction.
Analysis of accessibility and interoperability. Used to determine if a given service matches it's proposed service specification. Also determine if an artifact or specification is complete as it relates to data binding and value set binding.
Conformance Testing Functions
- Analyse artifact for ECCF Conformance and traceability
- Produce non-conformancy statement
- Interact with governance systems
The requirements listed above are derived from the following use cases:
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