Behavioural Interoperability to Support Model-Driven Systems Integration
A Model-Driven Approach to Interoperability and Integration in Systems of Systems
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Transcript of A Model-Driven Approach to Interoperability and Integration in Systems of Systems
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A Model-Driven Approach to Interoperabilityand Integration in Systems of Systems
Gareth TysonAdel Taweel
Steffen ZschalerTjeerd Van Staa
Brendan Delaney
King's College LondonGeneral Practice Research Database
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Overview
Focus on Systems of Systems (SoS)– Interoperability Issues
• Integrating services and data Present a case-study: ePCRN-IDEA
– Real-time recruitment system for clinical trials– Model-driven development
Discuss research challenges and issues Present conceptual model-driven architecture
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Background
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Systems of Systems (SoS)
“A collection of systems both technical and socio-technical which pool their abilities to present a more complex system, whilst retaining their individual autonomy.” [Lock'10]
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Interoperability
Technical Interoperability This refers to the compatibility of the underlying
technologies used to perform interactions (e.g. protocols).
Semantic Interoperability This refers to the ability of each party to understand
and interpret the data of others (e.g. data formats). – Process Interoperability This refers to the compatibility of the different
processes undertaken by each party (e.g. Task A should be performed after Task B).
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Case-Study: ePCRN-IDEA
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Overview of ePCRN-IDEA
Aim Intends to improve patient recruitment
Approach Enables real-time identification of eligible patients Presents practitioners (e.g. GPs) with pop-ups during
consultations Recruitment can be performed instantly via the web
Technology Requires a number of systems to cooperate Share data, services...
Use of models– Data within this system is all formally modelled
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Clinical Trials
What is a clinical trial? “Set of procedures in medical research conducted to
allow safety and efficacy data to be collected for health interventions”
Recruitment Process Patient databases Newspaper and radio advertisements Posters Personal recruitment
Problems Slow Costly
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Systems in ePCRN-IDEA
Vision Electric Healthcare Record System (EHR) Database used to store health records Managed by company, InPS
General Practice Research Database (GPRD) Data repository for health records Managed by governmental body
Local Eligible Patient Identification Service (LEPIS)
Software agent co-located with Vision Managed by KCL
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Systems in ePCRN-IDEA
Central Control Service (CCS) Stores and manages trials centrally Managed by KCL
Random Clinical Trial Website Web interface used to register interested patients Managed by private company
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Systems in ePCRN-IDEA
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Models within ePCRN-IDEA
All systems must exchange data– E.g. Trial information must be passed from the
CCS to LEPIS instances All data adheres to shared data models
– These are distributed to all systems• Via email as XML schemas
– Generally used to generate code Allows each party to interpret data correctly
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Models within ePCRN-IDEA
Trial Description– Description of the trial
Eligibility Criteria– Computable criteria for patient eligibility
Recruitment Model– Information regarding the recruitment process
Consultation Model– Information about patient consultations
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Example: Eligibility Criteria
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Issues and Research Challenges
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Issues and Research Challenges
Data Integration and Heterogeneous Sources– Necessary to bridge multiple data formats– Often not possible to convert data stored in
different systems into single standard• Difficult to optimise underlying storage• Difficult to place in shared repository
– Difficult to extend system to include new systems• Due to design-time model definition
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Issues and Research Challenges
Sub-System Process Changes– Changes within one system can affect other
systems– Interactions might need to be modified
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Issues and Research Challenges
Model Evolution– Changes to models can be required after
deployment– Performing translations between different versions
of the model– Need to version control models– Need to distribute models to appropriate parties
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Issues and Research Challenges
System-wide Consistency– Possible for sub-systems to hold inconsistent
views of the system as whole– Especially difficult for handling semantic
inconsistencies
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A Conceptual Architecture
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Requirements
All interactions must be formally captured and understandable by all parties– Not just at the data-layer
Models should also exist during runtime with the ability to evolve and change
Secure infrastructure must be available to handle these processes
Systems using different model versions must remain compatible
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A Dynamic Model-Driven Framework
Service Repository– Each system must register its offered services as
well as the data models it consumes and produces
Model Repository– All models must be centrally registered and
accessible– This can be separated into local and central
repositories Terminology Service
– Different terminologies must be mappable
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A Dynamic Model-Driven Framework
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A Dynamic Model-Driven Framework
All systems register the service and data models they support– Inc. versions
During runtime each system then retrieves its required models– Either from LMR or CMR
Models can then be reified into code If incompatible models are interconnected
– Mappings must be acquired
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Conclusion
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Conclusion
Investigated the use of model-driven engineering in designing Systems of Systems (SoS)
A model-driven case-study has been examined Key outcomes
– Complexity and cost of data mappings– Problems during process change– Difficulties of model evolution– Risks of system-wide
A conceptual architecture has been outlined– Future work is realising this