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The requirements listed above are derived from the following use cases in the previous section:

caEHR: The caEHR project has adopted ECCF for specifications and CDA documents for interoperability. The caEHR project requirements include, the need for an infrastructure for managing all the artifacts generated during specification process, including HL7 models and documents. The caEHR project also intends to publish these artifacts to the community and vendors. The infrastructure needs to support better discovery, making all the relevant information avaialble in the right context.

ONC and Other external EHR adopters: ONC has adopted CCD and CCR for meaninfuly 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 Trails: Clinical trails 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. 

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Better Discovery: Complex search that 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. 

The requirements listed above are derived from the following use cases in the previous section: 

caEHR: The caEHR project is developing service specifications and lacks the infrastructure to govern these services. Vendors and external implementators are expected to leverage the caEHR 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 enteprise 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. Reseach pipeline are developed by stringing services together to achieve a research objective. Example, ..

Other National Initiatives: All EHR vendors and national initiatives rely on a services paradigm for integration and interoperability. A standadized services metamodel makes it easier for participating organization to discover and reuse services.

caGRID 2.0 P/S/T: The caGRID 2.0 P/S/T 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.

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• CBIIT's adoption of ECCF: ECCF requires all specification developers to make conformance statements, the conformance testing framework leverages these conformance statements to generate validation tests
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P/S/T and Terminology Integration

The Semantic Infrastructure has to support seamless integration with the caGRID 2.0 P/S/T. The following are some high-level P/S/T and terminology requirements that either supported or addressed by the semantic infrastructure: 

Service Generation

Service generation is the ability to generate services from user defined service metadata, the semantic infrastructure provides this metadata and the P/S/T leverages this metadata for service generation. The constraints and policies specified in the semantic infrastructure are inherited by the platform and are enforced at runtime policies.

Additional platform specific and runtime information is provided by the developer for service generation.

Service Discovery & Utilization

This group of requirements focuses on enabling developers of composite services and applications to discover, compose, and invoke services. This includes the discovery of published services based on service metadata and the generation of client APIs in multiple languages to provide cross-platform access to existing services. This also includes the ability to use an "analytical" service locally in the case where the data to be processed is too large to move to a remote serviceclient APIs in multiple languages to provide cross-platform access to existing services.

Discovery includes service discovery, data discovery, and policy discovery. Service discovery allows primary users as well as secondary users to locate a service specification and instances based on attributes in the service metadata (for example, via a search for specific micro-array analysis services). Data discovery enables secondary users to find the types of data available in the ecosystem as well as summary-level information about available data sets. Policy discovery allows application developers to find and retrieve policies on services.

The platform will use the semantic infrastructure service metadata to address all the service discovery requirements. The semantic infrastructure relies on metadata about services and artifacts.

Link to use caseuse case satisfied from P/S/T roadmap: As institutions share de-identified glioblastoma data sets, they are available to others via data discovery. The treatment recommendation service used by the oncologist is able to discover these new data sets and their corresponding information models, and include that data for subsequent use in recommendation of treatment.

Link to use case satisfied from P/S/T roadmap: all of the data management and access services in the use case are utilized by application developers to build the user interfaces that the clinicians use during the course of patient care.

Service Orchestration and Choreography

Service orchestration and choreography allows both application developers and non-developers to discover service "building blocks" that can be composed dynamically to provide business capabilities. Special cases include the orchestration of multiple services for a distributed query, or for a transactional workflow. Service orchestration and choreography will leverage static and behavioral semantics from the Semantic Infrastructure v2.

The semantic infrastructure provides the behavioral semantics required for dynamic composibility of services or generation of distributed queries. This includes runtime contract discovery/negotiation to determinine composibility of services based on service capabilities and constraints.

Link to use case satisfied from P/S/T roadmap: Federated query over the TCGA data and other data sets is performed using a service orchestration.

Policy and Rules Management

Policy and Rules Management allow non-developer secondary users to create policies and rules and apply them to services. The scope of policies includes, but is not limited to, definition and configuration of business processing policy and related rules, compliance policies, quality of service policies, and security policies. Some key functional requirements to manage policies include capabilities to author policies and store policies, and for approval, validation, and run-time execution of policies.

Link to use case satisfied from P/S/T: Each institution has different data sharing needs, access control needs, and business rules for processing that are defined and customized. For example, policy at the pathologist's institution may state that the patient is scheduled for a visit when the review is complete.

Event Processing and Notifications

Event Processing and Notifications enables monitoring of services in the ecosystem and provides for asynchronous updates by services, effectively allowing a loose coordination of services that both provide and respond to conditions (possibly defined in business rules).

Link to use case satisfied from P/S/T: As patient care proceeds, the system notifies the designated clinicians that data (for example, images) are ready for review. Similarly, when notifications are received, event processing logic allows the appropriate parties to assign clinicians for care. In order to facilitate better treatment (a learning healthcare system), as new de-identified glioblastoma data is made available, notifications are sent that could indicate a recommended change in the treatment plan.

Data Requirements

This section includes the following requirements:

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Data

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Representation and Information Models

This set of requirements includes providing an application developer with the ability to define application-specific data elements and attributes (for example., defined using ISO 21090 healthcare datatypes) and an information model that defines the relationships between these data elements and attributes and other data elements and attributes in the broader ecosystem. In particular, the last requirement suggests linked datasets, where application developers can connect data in disparate repositories as if the repositories are part of a larger federated data ecosystem. Additional requirements include the ability to publish and discover information models. Support is needed for forms data and common clinical document standards, such as HL7 CDA. To support the use of binary data throughout the system, the binary data must be typed and semantically annotated.

Link to use case satisfied from P/S/T: The pathology, radiology and other data have various data formats which must be described, and the information model for the patient record must link between these various datatypes. The complete information model includes semantic links between datasets to build a comprehensive electronic medical record. Annotations on data are defined and included in the information model.

Data Management

Data management includes linking of disparate data sets and updates of data across the ecosystem. Data updates may include updates to multiple data sources, necessitating the need for transactions.

Link to use case satisfied from P/S/T: the patient has an electronic medical record that spans multiple institutions. The clinical workup data (for example, genomics and proteomics data) is linked to the clinical care record; similarly pathology and radiology findings must be attached to the patient's electronic medical record.

Data Exploration and Query

The wealth of data must be accessible, resulting in the need for exploration of available datasets. This includes the ability to view seamlessly across independent data sets, allowing a secondary user to integrate data from multiple sources. In addition, the query capability must support sophisticated queries such as temporal queries and spatial queries.

Link to use case satisfied from P/S/T: The oncologist must be able to quickly find glioblastoma data sets, indicating the fields that he is interested in comparing from his clinical data in order to find similar disease conditions and associated treatment plans. Temporal queries allow clinicians to identify changes in patient condition and treatment over time.

Provenance

Provenance encompasses the origin and traceability of data throughout an ecosystem. This is a clear requirement directly from the use case in order to ensure that all steps of patient care and research are clearly linked via the patient record.

Link to use case satisfied from P/S/T: The origin of data is tied to the data creator, allowing the oncologist performing the match against TCGA data and other datasets to include and exclude data sets based on their origin.-         Semantic Infrastructure Users and Roles
-         Functional Requirements
   Artifact Management
§  Static Models §  Behavioral Models
§  Forms

Data Semantics

In a diverse information environment, semantics must be used to clearly indicate the meaning of data. This requirement is expected to be addressed by the Semantics Infrastructure, although there will be a touchpoint between the caGrid 2.0 and the semantics infrastructure to annotate data with semantics. Integration with the semantics infrastructure will enable reasoning, semantic query, data mediation (for example, ad hoc data transformation) and other powerful capabilities.

Link to use case satisfied from P/S/T: The oncologist accesses the TCGA database to search for de-identified glioblastoma tumor data that is similar to the patient data exported from the hospital medical record. During this search, the semantics of the data fields are leveraged to indicate matches between TCGA data fields and the hospital medical record data fields.

External Data Repositories

There are numerous data repositories on the web today. These data repositories contain essential information that must be accessible to services in the ecosystem. As a result, caGrid 2.0 must provide capabilities to integrate these external repositories into the Grid with the assumption that the remote service cannot be changed.

Link to use case satisfied from P/S/T: The oncologist searches both TCGA glioblastoma data as well as de-identified data that has been added by care providers around the country. The additional data sets are external data repositories.

Terminology Integration