A Brain Tumor in silico use case consists of determining genetic, gene expression and outcome correlates of high resolution nuclear morphometry in the diffuse gliomas and their relation to MR features using Rembardt and TCGA datasets. This involves integrative analysis involving Pathology, Radiology and molecular data. The following semantic infrastructure use cases fall out of these requirements:
Init6pm23.1 - Agile Metadata Management
Use Case Number |
Init6pm23.1 |
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Brief Description |
Specific scientific data elements will be shared amongst collaborators, requiring the need for a way to semantically describe the data. However, through the course of the study, new data elements will be added and some data element may change. Therefore, there is a need for an agile modeling approach that does not require significant effort to modify the information model and register the semantic metadata. |
Actor(s) for this particular use case |
Information Modeler |
Pre-condition |
An information model is represented in UML, registered in the metadata repository, and in active use. |
Post condition |
The information model is updated and able to be used in production. |
Steps to take |
|
Alternate Flow |
None. |
Priority |
High |
Associated Links |
|
Fit criterion/Acceptance Criterion |
The modeling must be able to be performed and updated in a light-weight, Agile environment. Minimally, updates may be made monthly on an iterative basis. They should take no longer than days to define and propagate to the metadata repository. |
Init6pm23.2 - Modeling and Sharing Analytical Algorithms
Use Case Number |
Init6pm23.2 |
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Brief Description |
Data elements are generated using specific algorithms. There needs to be a way to model the features of the algorithm itself and tie it back to the original data. One of the features of the algorithm could be the code of the algorithm itself. It would be ideal if this type of model could be generalized for use in the caBIG analytical community. |
Actor(s) for this particular use case |
Information Modeler, Software Engineer |
Pre-condition |
An algorithm exists, it is coded, and its features are known. Outputs from the analytical routine are modeled and registered. |
Post condition |
A semantically sound description of the algorithm is defined, able to be shared with others, and able to be associated with data that the algorithm created. |
Steps to take |
|
Alternate Flow |
None. |
Priority |
Medium |
Associated Links |
|
Fit criterion/Acceptance Criterion |
A common standard model is highly desirable, though it is necessary for different Information Modelers to extend it. |
Init6pm23.3 - Modeling Lab and Research Methodology
Use Case Number |
Init6pm23.3 |
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Brief Description |
Metadata describing analytical results should link to the methodology used to generate the input data, such as the way that the biological specimens are analyzed and treated. In some cases, there can be clear overlap between the research methodology and the study design, which should be linked if possible. |
Actor(s) for this particular use case |
Information Modeler, Software Engineer |
Pre-condition |
Input data to analytical services has been generated using a particular set of steps, which is termed the methodology. A UML model exists for modeling the input parameter data. |
Post condition |
Research methodology metadata is modeled and associated to input parameter metadata. |
Steps to take |
|
Alternate Flow |
Researcher enters the research methodology data when the input parameter data is entered into the system. |
Priority |
Medium |
Associated Links |
|
Fit criterion/Acceptance Criterion |
A common standard model is highly desirable, though it is necessary for different Information Modelers to extend it. |
Init6pm23.4 - Analytical Provenance Tracking
Use Case Number |
Init6pm23.4 |
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Brief Description |
The ultimate result of the scientific use case is to design a classifier that predicts outcome. It will be necessary to describe the classifier, as well as have that description link back to the data that is used to generate it. In other words, the provenance of the data must be captured. |
Actor(s) for this particular use case |
Information Modeler |
Pre-condition |
Information models exist and are registered for analytical input data, output data, analytical algorithm, and research methodology. |
Post condition |
The inputs, analytical service, and outputs are linked through standard provenance data. |
Steps to take |
|
Alternate Flow |
A Researcher uses provenance to backtrack an analytical flow. |
Priority |
High |
Associated Links |
|
Fit criterion/Acceptance Criterion |
A common standard model is highly desirable, though it is necessary for different Information Modelers to extend it. |