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Natural language querying of metadata
Use Case Number | Init1pm4.29.1 |
|---|---|
Brief Description | Using Natural Language Processing and integrating both the terminology service and the metadata service APIs or similar future services, create a discovery service/tool which exposes data elements not based on the Names stored in the metadata repository but by using query in a concept search and pulling associated metadata to match. This would enable construction of better search algorithms and serve as a potentially better discovery entry point for the user not familiar with the metadata standard nomenclature. The primary users that this would serve include both Cancer Researchers and Information Technologists. |
Actor(s) for this particular use case | Cancer Researcher |
Pre-condition | Metadata exists in a repository, terminologies exist in a repository, and both are discoverable. |
Post condition | Metadata of interest is discovered |
Steps to take |
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Alternate Flow | None. |
Priority | Medium. |
Associated Links | |
Fit criterion/Acceptance Criterion | The query should provide more relevant results and be easier for non-technical users to construct than simple text-based matching. |
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h2. Natural language querying of metadata
|| *Use Case Number* \\ | Init1pm4.29.1 \\ |
|| *Brief Description* | Using Natural Language Processing and integrating both the terminology service and the metadata service APIs or similar future services, create a discovery service/tool which exposes data elements not based on the Names stored in the metadata repository but by using query in a concept search and pulling associated metadata to match. This would enable construction of better search algorithms and serve as a potentially better discovery entry point for the user not familiar with the metadata standard nomenclature. The primary users that this would serve include both Cancer Researchers and Information Technologists. \\ |
|| *Actor(s)* for this particular use case | Cancer Researcher \\ |
|| *Pre-condition* \\
The state of the system before the user interacts with it \\ | Metadata exists in a repository, terminologies exist in a repository, and both are discoverable. \\ |
|| *Post condition* \\
The state of the system after the user interacts with it \\ | Metadata of interest is discovered \\ |
|| *Steps to take* \\
The step-by-step description of how users will interact with the system to achieve a specific business goal or function \\ | # The Metadata Specialist constructs a query using natural language
# The Metadata Specialist issues that query to the metadata query service
# The metadata query service utilizes natural language processing, semantic metadata, and terminology services to build a computable query
# The metadata query service issues the computable query, ranks the results, and returns them to the Metadata Specialist |
|| *Alternate Flow* \\
Things which would prevent the normal flow of the use case \\ | None. \\ |
|| *Priority* \\
The priority of implementing the use case: *High, Medium or Low* \\ | Medium. \\ |
|| *Associated Links* \\
The brief user stories, each describing the user interacts with the system for the one function only of the use case. There would potentially be a number of user stories that make up the use case. \\ | * [Cross-cutting semantic searches|https://cabig-kc.nci.nih.gov/Vocab/forums/viewtopic.php?f=43&t=157]
* [Init1pm4 - Cross-cutting semantic searches|https://wiki.nci.nih.gov/x/owRyAQ] |
|| *Fit criterion/Acceptance Criterion* \\
How would actor describe the acceptable usage scenarios for the software or service that meets the actor's requirement? \\ | The query should provide more relevant results and be easier for non-technical users to construct than simple text-based matching. \\ |
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