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We advertise our Searches as being 'extensions', but in reality it is very difficult (or impossible) for a use to create a plug-in type Search.

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The *purpose of this document* is to collect, analyze, and define high-level needs for and designed features of the \[Product or Component Name x.x\]. The focus is on the functionalities proposed by the stakeholders and target users to make a better product. The use case documents show in detail how the features meet these needs.
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Design Scope

GForge items

Please visit the LexEVS 5.1 Scope document found at:  https://wiki.nci.nih.gov/display/EVS/LexEVS+5.1+Scope+document

Solution Architecture

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The purpose of this document is to collect, analyze, and define high-level needs for and designed features of the National Cancer Institute Center for Biomedical Informatics and Information Technology (NCI CBIIT) caCORE LexEVS Release 5.1. The focus is on the functionalities proposed by the stakeholders and target users to make a better product. The use case documents show in detail how the features meet these needs.

Design Scope

The scope of this release of the LexEVS 5.1 is to support the Metathesaurus Browser project by enhancing search and sorting performance as well as RRF loader changes to more accurately reflect the data. In addition we will explore enhancements to the loader framework and provide a recommendation/implementation for value set/domain support.

Please view the LexEVS 5.1 Scope document.

GForge items

Please view the LexEVS 5.1 GForge items.

Solution Architecture

Proposed technical solution to satisfy the following requirements:

• Query Performance and Behavior Enhancements - Improve the API to support the needs of the Metathesaurus Browser's query response.
• Metathesauraus Content (RRF) - Improve the loader to support full loading of RRF data as necessary for proper operation of the Methathesaurus Browser.
• Value Domain Support - Address an important part of the Semantic Infrastructure that is needed in caBIG.
• Improved Loader Framework - Improve the loading capability and allow loaders to be modular.
• BDA Support - Deployment of LexEVS Project Artifacts to Remote Servers

High Level Architecture

The LexEVS 5.1 infrastructure exhibits an n-tiered architecture with client interfaces, server components, domain objects, data sources, and back-end systems (Figure 1.1). This n-tiered system divides tasks or requests among different servers and data stores. This isolates the client from the details of where and how data is retrieved from different data stores.

The system also performs common tasks such as logging and provides a level of security for protected content. Clients (browsers, applications) receive information through designated application programming interfaces (APIs). Java applications communicate with back-end objects via domain objects packaged within the client.jar. Non-Java applications can communicate via SOAP (Simple Object Access Protocol) or REST (Representational State Transfer) services.

Most of the LexEVS API infrastructure is written in the Java programming language and leverages reusable, third-party components.  The service infrastructure is composed of the following layers:

Application Service layer - accepts incoming requests from all public interfaces and translates them, as required, to Java calls in terms of the native LexEVS API. Non-SDK queries are invoked against the Distributed LexEVS API, which handles client authentication and acts as proxy to invoke the equivalent function against the LexEVS core Java API. The caGrid and SDK-generated services are optionally run in an application server separate from the Distributed LexEVS API.
The LexEVS caCORE SDK services work directly against the database, via Hibernate bindings, to resolve stored objects without intermediate translation of calls in terms of the LexEVS API. However, the LexEVS SDK services do still require access to metadata and security information stored by the Distributed and Core LexEVS API environment to resolve the specific database location for requested objects and to verify access to protected resources, respectively.
From the client prospective, the LexEVS services will function as "ports" accessible through the caGrid 1.3 service architectural model. LexEVS services will follow the caGrid architecture for analytical and data services. See the caGrid 1.3 documentation for architectural details: https://cabig.nci.nih.gov/workspaces/Architecture/caGrid/

Core API layer - underpins all LexEVS API requests. Search of pre-populated Lucene index files is used to evaluate query results before incurring cost of database access. Access to the LexGrid database is performed as required to populate returned objects using pooled connections.

Data Source layer--- is responsible for storage and access to all data required to represent the objects returned through API invocation.

High Level Design Diagram
Image Modified

Figure 1.1 - High Level Diagram

Query Performance and Behavior Enhancements

Lucene - Lazy Document Loading

Lucene is very fast as a search engine. Given a text string, Lucene can find matching documents in huge indexes very fast. This is the purpose and strength of Lucene. Lucene is not, however, a database. Retrieving information from the documents that the search found as 'hits' is slow.

Consider this scenario: A user searches for 'heart' in the NCI MetaThesaurus. When Lucene does its search, it will return probably 50,000+ 'hits'. This search is done very fast. LexEVS previously would retrieve all of those documents to populate the ResolvedConceptReference. Retrieving this many documents from Lucene is slow.

The solution is to is lazy load the documents as needed. After the Lucene search is complete, we only store the Document Id. Then, when information from the document is needed, it is retrieved from the document. This is helpful in Iterator-type scenarios, where retrieval can be done one at a time.

Update to Lucene 2.4 Code

As we move forward, it is important to keep current with the latest Lucene API. Not only is this important for performance reasons -- it will limit our ability to upgrade our Lucene dependencies if we rely on
deprecated methods.

Searching - Plug-in Search Framework

We advertise our Searches as being 'extensions', but in reality it is very difficult (or impossible) for a use to create a plug-in type Search.

The Interface org.LexGrid.LexBIG.Extensions.Query.Search will be introduced. The purpose of this interface is to give users a plug-in type Interface to implement different search strategies. This interface will accept
a text query string and output a Lucene Query.

Sorting - Plug-in Sort Framework

As with Searching, Sort algorithms are not currently easily extended. A well defined and 'Extension-ready' interface would allow users to add additional search functionality on demand, without rebuilding or recompiling.

The existing Interface org.LexGrid.LexBIG.Extensions.Query.Search will be expanded to allow for easy implementation and flexibility, allowing rapid creation of new Sort Algorithms and techniques.

SQL - SQL query optimizations to increase database performance

Join EntityDescription when building AssociatedConcepts
The 'EntityDescription' field of 'Entity' is being retrieved with a separate SQL call. This will allow the building of AssociatedConcepts with minimal calls
to the database.

Furthermore, this will allow the 'EntityDescription' to be available without requiring the actual 'CodedEntry' to be resolved. For most usescases, this should enable users to resolve Graphs with 'CodedEntryDepth=0'. Avoiding any resolving of the CodedEntry will keep resolve times to a minimum.

Join EntryState when building CodedEntry
The EntryState is now populated with a seperate SQL SELECT query to the database. This results in one SELECT statement per CodedEntry returned - and there is potential for a large number of CodedEntries to be resolved at once. Populating this with a JOIN instead of a SELECT will be more efficient and not require additional unnecessary SELECT queries to the database.

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NCI MetaThesauraus Content (RRF)

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Loads of the NCI MetaThesaurus RRF formatted data into the LexGrid model require a number of loader adjustments in order to accurately reflect the state of the data as it exists in the current RRF files. No model or API changes will be necessary to accommodate the data; changes will be made directly to to the loader.

Value Domain Support

Overview 

The LexEVS Value Domain and Pick List service will provide ability to load Value Domain and Pick List Definitions into LexGrid repository and provides ability to apply user restrictions and dynamically resolve the definitions during run time. Both Value Domain and Pick List service are integrated part of LexEVS core API.

The LexEVS Value Domain and Pick List service will provide programmatic access to load Value Domain and Pick List Definitions using the domain objects that are available via the LexGrid logical model. The LexEVS Value Domain and Pick List service will provide ability to apply certain user restrictions (ex: pickListId, valueDomain URI etc) and dynamically resolve the Value Domain and Pick List definitions during the run time

The LexEVS Value Domain and Pick List Service meant to expose the API particularly for the Value Domain and Pick List elements of the LexGrid Logical Model. For more information on LexGrid model see http://informatics.mayo.edu\\

Improved Loader Framework

LexEVS already provides a set of loaders within an existing legacy framework which has served LexEVS developers well over the years. But as LexEVS has gained users, and requests for new loaders has grown , it was decided that a new Loader Framework should be developed. The new framework: provides classes and interfaces that are more modular and easier to extend; improved loader performance; allows dynamic loading of new loaders; is built upon proven open source technologies such as SpringBatch and Hibernate, and finally, the new Loader Framework code is completely independent of the current loader code in LexEVS so there will be no impact to current loaders.

BDA Support

LexEVS uses the BDA (Build and Deployment Automation) system to build and deploy artifacts. This build script that produces these artifacts and deploys them is kicked off via a build server (an instance of Anthill pro).

Cross product dependencies

Include a link to the Core Product Dependency Matrix.

Changes in technology

Include any new dependencies in the Core Product Dependency Matrix and summarize them here.

• No new dependencies exist.

Assumptions

List any assumptions.

Risks

• Increased load time and storage requirements due to additional Meta (RRF) content.
  • Due to the additional content to load from RRF files, there is a risk of increased loading times and increased storage requirements. The new loader framework should mitigate the increased loading times (providing a faster load while increasing content to be loaded).

Detailed Design

Specify how the solution architecture will satisfy the requirements. This should include high level descriptions of program logic (for example in structured English), identifying container services to be used, and so on.

Query Performance and Behavior Enhancements Detailed Design

Lucene Lazy Loading

Backgroud - Lucene Documents
Lucene stores information in Documents, and these Documents have Fields that are used to hold information. Each Document has a unique id.

For example, an index of People may be indexed in Lucene as:

Document: id 1
First Name: John
Last Name: Doe
Sex: Male
Age: 45

Document: id 2
First Name: Jane
Last Name: Doe
Sex: Female
Age: 40

... etc.

LexEVS stores information about Entities in this way. Property names and values, as well as Qualifiers, Language, and various other information about the Entity are held in Lucene indexes.

Backgronud - Querying Lucene

Lucene provides a Query mechanism to search through the indexed documents. Given a search query, Lucene will provide the Document id and the score of the match (Lucene assigns every match a 'score', depending on the strength of the match given the query).

So, if the above index is queried for "First Name = Jane AND Last Name = Doe", the result will be the Document id of the match (2), and the score of the match (a float number, usually between 1 and 10).

Notice that none of the other information is returned, such as Sex or Age. It is useful for that extra information to be there, because if it exists in the Lucene indexes we do not have to make a database query for it. BUT, retrieving data from Lucene Documents is expensive, just as retrieving data from a database would be.

• Lazy Retrieval
  We can leverage this to increase performance in LexEVS. Consider this simplified LexEVS Entity index:

Document: id 1
Code: C12345
Name: Heart

Document: id 2
Code: C67890
Name: Foot

Document: id 3
Code: C98765
Name: Heart Attack

If a user constructs a Query (Name = Heart*), the query will return with the matching Document ids (1 and 2). Previously, LexEVS would immediately retrieve the 'Code' and 'Name' fields from the matches, and use them to construct the results that would be ultimately returned to the user. This does not scale well, especially for general queries in large ontologies. In a large ontology, a Query of (Name = Heart*) may match tens of thousands of Documents. Retrieving the information from all these Documents is a significant performance concern.

Instead of retrieving the information up front, LexEVS will simply store the Document id for later use. When this information is actually needed by the user (for example, the information needs to be displayed), it is retrieved on demand.

Searching

To allow users to plug in custom search algorithms, the LexEVS Extension framework needed to be extended to include Searches.

The org.LexGrid.LexBIG.Extensions.Extendable.Search interface consists of one method to be implemented:

This enables the user to construct any type of Query given search text. Wildcards may be added, search terms may be grouped, etc.

AND vs. OR
Previously, for most search algorithms Lucene applied an 'OR' to the terms if multiple terms were input as search text. For example, a search of 'heart attack' would match all documents containing 'heart' OR all documents containing 'attack'. This lead to non-intuitive results being returned to the user. Changing Lucene to default to an 'AND' type strategy will increase search precision and in most cases shrink the amount of results returned for a given query, which will in turn increase overall performance.

Algorithms

More precice DoubleMetaphoneQuery
DoubleMetaphoneQueries enable the user to input incorrectly spelled search text, while still returning results. Because this is a 'fuzzy' search, it is important to structure the Query in a way that the most appropriate results are returned to the user first.

For example, the Metaphone computed value for "Breast" and "Prostrate" is the same. Given the search term "Breast", both "Breast" and "Prostrate" will match with exactly the same score. Technically, this is correct behavior, but to the end user this is not desirable. To overcome this, we have introduced a new query, WeightedDoubleMetaphoneQuery.

WeightedDoubleMetaphoneQuery
This algorithm does not automatically assume that the user has spelled the terms incorrectly. Searches are also based on the actual text that the user has input, along with the Metaphone value.
Again, if the user input "Breast", the query will still match "Breast" and "Prostrate", but "Breast" will have a higher match score, because the actual user text is considered. This will add a greater precision to this fuzzy-type query.

Algorithm:

get: user text input
2: total score = 0
3: metaphone score = 0
4: actual score = 0
5: metaphone value = lucene.computeMetaphoneValue(user text input)
6: metaphone score = lucene.scoreMetaphoneValue(metaphone value)
7: actual score = lucene.score(user text input)
8: total score = metaphone score + actual score
9: halt

Case-insensitive substring

SubStringSearch - This algorithm is intended to find substrings within a large string. For example:
"with a heart attack"
Will match:
"The patient with a heart attack was seen today".

Also, a leading and trailing wildcard will be added, so
"th a heart atta"
Will also match:
"The patient with a heart attack was seen today".

Algorithm:

get: user text input
2: user text input = '*' + user text input + '*'
3: score = lucene.score(user text input)
4: halt

Sorting

Sorting matched results is important part of interacting with the LexEVS API. Allowing users to plug in customized Sort algorithms helps LexEVS to be more flexible to more groups of users. To implement a Sorting algorithm, a user must implement the org.LexGrid.LexBIG.Extensions.Extendable.Sort Interface.

• Sorting on Different Class types
  • A single Sort may be applicable for a variety of Class types. For instance, both an 'Association' and an 'Entity' may be sorted by 'Code', but the actual implementation of retrieving the Code and comparing it may be different between the two. It is the job of the Sort to implement a Comparator for each potential Class that it is eligible to sort.
• Default Sorting
  • All result sets are sorted by default by Lucene Score, meaning that the best match according to Lucene will always be returned first by default. Note that if two or more result sets are being Unioned, Intersected, or Differenced, the user must explicitly call a 'matchToQuery' sort on the result set as a whole to order all of the results.
• Sort Contexts
  • Sorts may be applicable in one or more 'Contexts' (see: org.LexGrid.LexBIG.DataModel.InterfaceElements.types.SortContext)
    This means that a Sort may apply only to a CodedNodeSet, or only to a CodedNodeGraph, or some combination. Sorts will only be employed by the API if they match the Context in which the results are being sorted.
• Performance Issues
  • Sorting is generally computationally expensive, because in order to correctly sort, the field to be sorted has to be fully retrieved for the entire result set. For very specific or refined queries, this may not be a problem, but for large ontologies or very general queries, performance may be a concern. To alleviate this, 'Post sort' has been introduced.
• Post Sorting

  • In order to minimize the performance impact of sorting, users are encouraged to use a 'Post sort' where possible. A Post sort is done after the result set has been restricted, thus limiting the amount of information that must be retrieved in order to perform the sort. For instance, a query may match a set of Entities:

    No Format
    {"Heart", "Heart Failure", "Heart Attack", "Arm", "Finger", ...}

As described earlier, all results are by default sorted by Lucene score, so if we limit the result set to the top 3, the result is:

{"Heart", "Heart Failure", "Heart Attack

"

As described earlier, all results are by default sorted by Lucene score, so if we limit the result set to the top 3, the result is:

No Format
Image Removed LexEVS Value Domain and Picklist Service Class Diagram Common Services Class Diagram These are the classes that are used commonly across Value Domain and Pick List implementation. Class Name Description VDEntryTypeServices Class to handle Entry Type objects to and fro database . VDEntryStateServices Class to handle EntryState objects to and fro database. VDPropertyServices Class to handle Property objects to and fro database. VDMappingServices Class to handle supported Mappings objects to and fro database. VDServiceHelper Helper class containing methods that are commonly used. VDBaseSQLServices Class to handle SQL Services. VDBaseService Base service class to handle all Value Domain and Pick List related objects to and fro database. Value Domain Class Diagram Classes that implements LexEVS Value Domain API Class Name Description VDSServices Class to handle list of Value Domain Definitions Object to and fro database VDServices Class to handle individual Value Domain Definition objects to and fro database. VDEntryServices Class to handle  Value Domain Entry objects to and fro database. LexEVSValueDomainServices Primary interface for LexEVS Value Domain API LexEVSValueDomainServicesImpl Implementation of LexEVSValueDomainServices which is primary interface for LexEVS Value Domain API. LoadValueDomain Imports the value Domain Definitions in the source file, provided in LexGrid canonical format, to the LexBIG repository. ResolvedValueDomainCodedNodeSet Contains coding scheme version reference list that was used to resolve the value domain and the coded node set. ResolvedValueDomainDefinition A resolved Value Domain definition containing the coding scheme version reference list that was used to resolve the value domain and an iterator for resolved concepts. Picklist Class Diagram  Classes that implements LexEVS Pick List API Class Name Description PickListsServices Class to handle list of Pick List Definitions. PickListServices Class to handle individual Pick List Definition objects to and fro database. PLEntryServices Class to handle Pick List Entry objects to and fro database. LexEVSPickListServices Primary interface for LexEVS Pick List API. LexEVSPickListServicesImpl Implementation of LexEVSPickListServices which is primary interface for LexEVS Pick List API. LoadPickList Imports the Pick List Definitions in the source file, provided in LexGrid canonical format, to the LexBIG repository. ResolvedPickListEntyList Class to hold list of resolved pick list entries. ResolvedPickListEntry Bean for resolved pick list entries.  LexBIG Services Class Diagram An interface to LexEVS Value Domain and Pick List Services could be obtained using an instance of LexBigService. Method Name Description getValueDomainService() Returns an interface to LexEVS Value Domain API getPickListService() Returns an interface to LexEVS Pick List API.   4.0 Improved Loader Framework Cross product dependencies Include a link to the Core Product Dependency Matrix. Changes in technology Include any new dependencies in the Core Product Dependency Matrix and summarize them here. No new dependencies exist. Assumptions List any assumptions. Risks Increased load time and storage requirements due to additional Meta (RRF) content.  Due to the additional content to load from RRF files, there is a risk of increased loading times and increased storage requirements.  The new loader framework should mitigate the increased loading times (providing a faster load while increasing content to be loaded). Detailed Design Specify how the solution architecture will satisfy the requirements. This should include high level descriptions of program logic (for example in structured English), identifying container services to be used, and so on. Query Performance Enhancements Lucene Lazy Loading Backgroud - Lucene Documents Lucene stores information in Documents, and these Documents have Fields that are used to hold information. Each Document has a unique id. For example, an index of People may be indexed in Lucene as: No Format Document: id 1 First Name: John Last Name: Doe Sex: Male Age: 45 Document: id 2 First Name: Jane Last Name: Doe Sex: Female Age: 40 ... etc. LexEVS stores information about Entities in this way. Property names and values, as well as Qualifiers, Language, and various other information about the Entity are held in Lucene indexes. Backgroud - Querying Lucene Lucene provides a Query mechanism to search through the indexed documents. Given a search query, Lucene will provide the Document id and the score of the match (Lucene assigns every match a 'score', depending on the strength of the match given the query). So, if the above index is queried for "First Name = Jane AND Last Name = Doe", the result will be the Document id of the match (2), and the score of the match (a float number, usually between 1 and 10). Notice that none of the other information is returned, such as Sex or Age. It is useful for that extra information to be there, because if it exists in the Lucene indexes we do not have to make a database query for it. BUT, retrieving data from Lucene Documents is expensive, just as retrieving data from a database would be. Lazy Retrieval We can leverage this to increase performance in LexEVS. Consider this simplified LexEVS Entity index: No Format Document: id 1 Code: C12345 Name: Heart Document: id 2 Code: C67890 Name: Foot Document: id 3 Code: C98765 Name: Heart Attack If a user constructs a Query (Name = Heart*), the query will return with the matching Document ids (1 and 2). Previously, LexEVS would immediately retrieve the 'Code' and 'Name' fields from the matches, and use them to construct the results that would be ultimately returned to the user. This does not scale well, especially for general queries in large ontologies. In a large ontology, a Query of (Name = Heart*) may match tens of thousands of Documents. Retrieving the information from all these Documents is a significant performance concern. Instead of retrieving the information up front, LexEVS will simply store the Document id for later use. When this information is actually needed by the user (for example, the information needs to be displayed), it is retrieved on demand. Searching To allow users to plug in custom search algorithms, the LexEVS Extension framework needed to be extended to include Searches. The org.LexGrid.LexBIG.Extensions.Extendable.Search interface consists of one method to be implemented: Class: org.LexGrid.LexBIG.Extensions.Extendable.Search Method: public org.apache.lucene.search.Query buildQuery(String searchText) Description: Given a String search string, build a Query object to match indexed Lucene Documents This enables the user to construct any type of Query given search text. Wildcards may be added, search terms may be grouped, etc. Algorithms More precice DoubleMetaphoneQuery DoubleMetaphoneQueries enable the user to input incorrectly spelled search text, while still returning results. Because this is a 'fuzzy' search, it is important to structure the Query in a way that the most appropriate results are returned to the user first. For example, the Metaphone computed value for "Breast" and "Prostrate" is the same. Given the search term "Breast", both "Breast" and "Prostrate" will match with exactly the same score. Technically, this is correct behavior, but to the end user this is not desirable. To overcome this, we have introduced a new query, WeightedDoubleMetaphoneQuery. WeightedDoubleMetaphoneQuery This algorithm does not automatically assume that the user has spelled the terms incorrectly. Searches are also based on the actual text that the user has input, along with the Metaphone value. Again, if the user input "Breast", the query will still match "Breast" and "Prostrate", but "Breast" will have a higher match score, because the actual user text is considered. This will add a greater precision to this fuzzy-type query. Algorithm No Format 1: get: user text input 2: total score = 0 3: metaphone score = 0 4: actual score = 0 5: metaphone value = lucene.computeMetaphoneValue(user text input) 6: metaphone score = lucene.scoreMetaphoneValue(metaphone value) 7: actual score = lucene.score(user text input) 8: total score = metaphone score + actual score 9: halt Case-insensitive substring SubStringSearch - This algorithm is intended to find substrings within a large string. For example: "with a heart attack" Will match: "The patient with a heart attack was seen today". Also, a leading and trailing wildcard will be added, so "th a heart atta" Will also match: "The patient with a heart attack was seen today". Algorithm No Format 1: get: user text input 2: user text input = '*' + user text input + '*' 3: score = lucene.score(user text input) 4: halt Sorting Sorting matched results is important part of interacting with the LexEVS API. Allowing users to plug in customized Sort algorithms helps LexEVS to be more flexible to more groups of users. To implement a Sorting algorithm, a user must implement the org.LexGrid.LexBIG.Extensions.Extendable.Sort Interface. Class: org.LexGrid.LexBIG.Extensions.Extendable.Sort Method: public <T> Comparator<T> getComparatorForSearchClass(Class<T> searchClass) throws LBParameterException Description: Given a Class that this Sort is valid for, return the correct Comparator to compare the results and sort. Method: public boolean isSortValidForClass(Class<?> clazz); Description: Return whether or not this Sort is valid for Sorting on a given Class Sorting on Different Class types A single Sort may be applicable for a variety of Class types. For instance, both an 'Association' and an 'Entity' may be sorted by 'Code', but the actual implementation of retrieving the Code and comparing it may be different between the two. It is the job of the Sort to implement a Comparator for each potential Class that it is eligible to sort. Default Sorting All result sets are sorted by default by Lucene Score, meaning that the best match according to Lucene will always be returned first by default. Note that if two or more result sets are being Unioned, Intersected, or Differenced, the user must explicitly call a 'matchToQuery' sort on the result set as a whole to order all of the results. Sort Contexts Sorts may be applicable in one or more 'Contexts' (see: org.LexGrid.LexBIG.DataModel.InterfaceElements.types.SortContext) This means that a Sort may apply only to a CodedNodeSet, or only to a CodedNodeGraph, or some combination. Sorts will only be employed by the API if they match the Context in which the results are being sorted. Performance Issues Sorting is generally computationally expensive, because in order to correctly sort, the field to be sorted has to be fully retrieved for the entire result set. For very specific or refined queries, this may not be a problem, but for large ontologies or very general queries, performance may be a concern. To alleviate this, 'Post sort' has been introduced. Post Sorting In order to minimize the performance impact of sorting, users are encouraged to use a 'Post sort' where possible. A Post sort is done after the result set has been restricted, thus limiting the amount of information that must be retrieved in order to perform the sort. For instance, a query may match a set of Entities:
No Format

{"Heart", "Heart Failure", "Heart Attack"}

}

The restricted set can then be 'Post' sorted - and because the result set has be limited to a reasonable number of matches, sorting and retrieval time can be minimized.

Algorithm:

1: 

get: Sort requested by user

2:

 get: Context sort is being applied to

3: 

if: sort is not valid for Context

halt

4:

 else:

5:

 get: Class to be sorted on

6:

 if: sort is not valid for Class

halt

7:

 get: Comparator for Sort - given (Class to be sorted on)
8:

 sort results using Comparator for Sort
9:

 halt

SQL Optimizations

The n+1 SELECTS Problem

The n+1 SELECTS Problem refers to how information can optimally be retrieved from the database, preferably using as few queries as possible. This is desirable because:

• Query overhead is a concern. Every query must be packaged and sent to the database engine, processed, packaged again and transferred to the client. Although the overhead may be minimal (a few milliseconds), it does not scale.

To avoid this, a JOIN query can be used.

The n+1 SELECTS Problem Example

Given two database tables, retrieve the Code, Name, and Qualifier for each Code

Table Codes

Table Qualifiers

SELECT * FROM Codes

Results in:

To get the Qualifiers, separate SELECTs must be used for each.

SELECT * FROM Qualifiers where Code = C01234
And
SELECT * FROM Qualifiers where Code = C98765

This sequence results in 1 Query to retrieve the data from the Codes table, and then n Queries from the Qualifiers table. This results in n+1 total Queries.

The n+1 SELECTS Problem Example (Solution)

Given two database tables, retrieve the Code, Name, and Qualifier for each Code

Table Codes

Table Qualifiers

SELECT * FROM Codes JOIN Qualifiers ON Code

Results in:

Because of the JOIN, only one Query is needed to retrieve all of the data from the database.

Although sometimes obvious, n+1 queries can remain in a system undetected until scaling problems are noticed.

In LexEVS there were 3 n+1 SELECT queries fixed:

• The EntryState while building the CodedEntry.
• The EntityDescription on AssociatedConcepts
• AssociationQualifiers on AssociatedConcepts

Metathesauraus Content (RRF) Detailed Design

Loads of the NCI MetaThesaurus RRF formatted data into the LexGrid model require a number of adjustments in order to accurately reflect the state of the data as it exists in the current RRF files.

Data Model Elements

Most data elements will be loaded as either properties or property qualifiers:

Image Modified

A few will be loaded as qualifiers to associations.

Retrieval and API Documentation

No new API retrieval methods will be implemented in the scope of LexEVS 5.1. However, some may be required in the scope of 6.0 for any mapping elements implemented as new model elements or model extensions to LexGrid. No changes to user interfaces will occur. Service methods for loading these elements will be consistent with the new Spring Batch loader framework.

MRREL.RRF File

Problem:

REL and RELA column elements from the RRF source need to be connected.
Currently these are loaded as separate relationships preventing the user from connecting to the REL/RELA combinations that actually occur in the NCI-META (e.g. RELA may be different for same REL value in different sources).

Requirement:

A single relationship should be loaded for a REL/RELA combination for a particular SAB between two CUIs.

Solution:

Since RELA type RRF elements have been defined as relationship names specific to sources and not independent relationships themselves, these elements will be loaded as association qualifiers in the LexGrid model.

Problem and Requirement:

User is unable to distinguish individual relationships from one source or another. The same association "entity" exists only once but has two "source" qualifiers.
User is unable to distinguish the AUI1/STYPE1 and AUI2/STYPE2 which gives us the information about what source data structures are actually being connected by MRREL entries. Users also need the ability to associate AUI/STYPE fields with SAB.
Users sole choice for rendering a relationship in terms of the strings on either side is to use preferred concept names.

Proposed Solution:

Propose AUI to AUI - the way CUI to CUI are currently handled in the implementation.
Propose entity to entity relationship - will still have to account for CUI to CUI relationships.
Load each unique RUI (would be quite large). They would need to be listed as supported association (this is not traditional how it is used).

Load supporting column elements from MRREL.RRF including contents of:
AUI1, STYPE1, AUI2, STYPE2, SRUI, SAB, RG, SUPPRESS, CVF, RUI

These will be available as elements of the overriding Metathesaurus Association and loaded as association qualifiers

Problem:

Self Referencing Relationships (CUI1 = CUI2) cannot be fully represented in our model. Previously, these were loaded as PropertyLinks. This fit into the LexEVS model well, but left out important RRF information. Most notably, PropertyLinks cannot contain Qualifiers like normal relations can. Because of the increased number of Qualifiers that are required to be placed on relations, much information would be lost representing these relations as PropertyLinks

Solution:

Do not treat a CUI1 = CUI2 relationships differently than a CUI1 != CUI2 relationship. For API and query purposes, qualify these relationships with a 'selfReferencing=true' Qualifier. In this way, we can still avoid cycles in the API, but maintain all relevant Qualifier information in the relation.

MRSAT.RRF

Problem:

MRSAT.RRF is not loaded but only accessed for given preferred term algorithms. This data should be loaded as concept properties (STYPE=CUI), properties on properties (STYPE=AUI, SAUI, CODE, SCUI, SDUI), qualifiers on associations (STYPE=RUI,SRUI). Some complexity may arise as concept properties can have additional qualifiers, but property-properties cannot and association-qualifiers cannot.

Requirement:

If the STYPE is something other than RUI or SRUI, you can load
that row as an entity property. The fields you'd want to capture
are:

CUI - We use this as the entityCode and is loaded as such in the table.

METAUI - load as a propertyQualifier (name=METAUI, value)

STYPE - load as a propertyQualifier (name=STYPE, value)

ATUI - load as propertyId

ATN - load as property name

SAB - load as a propertyQualifier (typeName=source)

ATV- load as a propertyValue

SUPPRESS - load as propertyQualifier if value != N

MRRANK.RRF

Problem:

SAB specific ranking of representational form in MRRANK is not exposed to the user (used in an underlying ranking and specifying of preferred presentations for a given concept)

Requirement:

Load elements of MRRANK so that they are available to the user.

Proposed Solution:

Load MRRANK as property qualifier on Presentation type property with the property Name of "mrrank."

Retrieval:

Available in current LexEVS api

MRSAB.RRF

Problem:

MRSAB.RRF file data is not loaded or is otherwise unavailable to the user.

Requirement:

Load MRSAB.RRF file data as metadata

Implemented Solution:

Entire content of each row of MRSAB file is loaded as metadata to an external xml file with tags created from column names and value inserted between tags as is appropriate

MRMAP.RRF, MRSMAP.RRF

Problem:

MRMAP.RRF source load is not supported in current load. Currently this RRF file is not populated in NCI Metathesaurus distributions. Mapping is not explicitly supported in the LexGrid Model.

Requirement:

Load MRMAP data.

Solution:

To be evaluated for a load to current model elements or possible new model mapping elements. The general agreement is that this is more appropriately implemented in 6.0.

MRHIER.RRF

Problem:

HCD is loaded as a property on the presentation but the SAB isn't associated with it so we do not know the source of the HCD. (only look at row that has HCD field populated)
Path to Root, (PTR) is also not loaded, but is instead used to determine path to root operations in LexEVS.

Requirement:

These elements need to be loaded and available from the LexEVS api

Solution:

Load HCD associated field SAB as property qualifier when HCD is present. Load PTR as property.

MRDOC.RRF

Problem:

MRDOC contains metadata unavailable to the user. It is not loaded by LexEVS.

Requirement:

This metadata will be made available to the user.

Solution:

MRDOC's column names and content will be processed as tag/value mappings to a metadata file.

MRDEF.RRF

Problem:

Some values from each row are not loaded by LexEVS.

Requirement:

AUI should be loaded to connect it with the presentation
ATUI, SUPPRESS, CVF, SATAUI should be loaded and exposed to the user.

ATUI, SUPPRESS, CVF, SATAUI, column values will be loaded as property qualifiers on the Definition type property derived from MRDEF column.

MRCONSO.RRF

Problem:

Some elements from the columns of MRCONSO.RRF are not loaded by LexEVS.

Requirement:

Load LUI, SUI, SAUI, SDUI, SUPPRESS, CVS fields and expose to the user.

Solution:

All noted values will be loaded as property qualifiers.

Value Domain Support Detailed Design

Implementation Overview

Description

The LexEVS Value Domain and Pick List service will provide ability to load Value Domain and Pick List Definitions into LexGrid repository and provides ability to apply user restrictions and dynamically resolve the definitions during run time. Both Value Domain and Pick List service are integrated part of LexEVS core API.

Scope

The LexEVS Value Domain and Pick List service will provide programmatic access to load Value Domain and Pick List Definitions using the domain objects that are available via the LexGrid logical model.

The LexEVS Value Domain and Pick List service will provide ability to apply certain user restrictions (ex: pickListId, valueDomain URI etc) and dynamically resolve the Value Domain and Pick List definitions during the run time.

Architecture

The LexEVS Value Domain and Pick List Service meant to expose the API particularly for the Value Domain and Pick List elements of the LexGrid Logical Model. For more information on LexGrid model see http://informatics.mayo.edu/

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LexGrid Value Domain

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Common Services Class Diagram

These are the classes that are used commonly across Value Domain and Pick List implementation.

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Value Domain Class Diagram

Classes that implements LexEVS Value Domain API

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Pick List Class Diagram

Classes that implements LexEVS Pick List API

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LexBIG Services Class Diagram

An interface to LexEVS Value Domain and Pick List Services could be obtained using an instance of LexBigService.

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Main Service API

LexBIG API

An interface to LexEVS Value Domain and Pick List Services could be obtained using an instance of LexBigService.

Sample Call:
_Using LexBIGService instance : _
org.lexgrid.valuedomain.LexEVSValueDomainServices vds = lbs.getValueDomainService();

Sample Call:
Using LexBIGService instance :
_ _org.lexgrid.valuedomain.LexEVSPickListServices vds = lbs.getPickListService();

LexEVS Value Domain Service API

Loading Value Domain

There are three methods that could be used to load Value Domain Definitions :

loadValueDomain(ValueDomainDefinition vddef, String systemReleaseURI)

Sample Call:
Step 1 : Using LexBIGService instance, get the LexEVSValueDomainServices interface :
org.lexgrid.valuedomain.LexEVSValueDomainServices vds = lbs.getValueDomainService();

Step 2 :Create and populate the ValueDomainDefinition object
ValueDomainDefinition can be created using :
org.LexGrid.emf.valueDomains.ValueDomainDefinition valueDomain = org.LexGrid.emf.valueDomains.ValuedomainsFactory.eINSTANCE.createValueDomainDefinition();

And data for valueDomain object can be populated by using set methods :
valueDomain.setValueDomainURI(uri);
valueDomain.setValueDomainName(name);
valueDomain.setDefaultCodingScheme(cs);
_valueDomain.setEntityDescription(ed); _

Similarly, DefinitionEntry, Property, Mapping objects can be created and assign to the valueDomain object.
valueDomain.getDefinitionEntry.add(vdEntry);
valueDomain.setProperties(propertisObject);
_valueDomain.setMappings(mappingsObject); _

Step 3 : call the load method by passing the Value Domain Definition object and the System Release URI :
vds.loadvalueDomain(valueDomain,"Release 2009");

loadValueDomain(InputStream inputStream, boolean failOnAllErrors)

Sample Call:
_Step 1 : Using LexBIGService instance, get the LexEVSValueDomainServices interface _org.lexgrid.valuedomain.LexEVSValueDomainServices vds = lbs.getValueDomainService();

Step 2 :Call load method by passing the inputSteam and boolean flag whether to stop on load errors. :
vds.loadvalueDomain(inputStream, true);

loadValueDomain(String xmlFileLocation, boolean failOnAllErrors)

Step 2 :Call load method by passing the inputfile location and boolean flag whether to stop on load errors. :
vds.loadvalueDomain(inputXMLFile, true);

Validate XML resources

validate(URI uri, int valicationLevel) throws LBParameterException

Step 2 :Call validate method for validation by supplying URI of the XML file and validation level:
Supported validationLevels includes :
0 = Verify document is well-formed
1 = Verify document is valid

_ vds.validaten(uriOfXMLFile, true);_

Query Value Domain

isConceptInDomain(String entityCode, URI valueDomainURI)

Step 2 :Call isConceptInComdin method:
AbsoluteCodingSchemeVersionReference acsvr = vds.isConceptInDomain("conceptA","valueDomainURI");

isConceptInDomain(String entityCode, URI entityCodeNamespace, CodingSchemeVersionOrTag csvt, URI valueDomainURI)

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isConceptInDomain(String entityCode, URI entityCodeNamespace, CodingSchemeVersionOrTag csvt, URI valueDomainURI)

...

Description:

...

Similar to previous method, this method determine if the supplied entity code and entity namespace is a valid result for the supplied value domain when resolved against supplied Coding Scheme Version or Tag.

...

Input:

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java.lang.String,
java.net.URI,
org.LexGrid.LexBIG.DataModel.Core. CodingSchemeVersionOrTag
java.net.URI

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Output:

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org.LexGrid.LexBIG.DataModel.Core. AbsoluteCodingSchemeVersionReference

...

Exception:

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org.LexGrid.LexBIG.Exceptions.LBException

model

Here is a UML representation of Value Domain within LexGrid 200901 model.

Image Added

Value Domain Definition

A definition of a given value domain. A value domain can be a simple description with no associated value domain entries, or it can consist of one or more definitionEntries that resolve to an enumerated list of entityCodes when applied to one or more codingScheme versions.

Attributes of Value Domain Definition :

Source: The local identifiers of the source(s) of this property. Must match a local id of a supportedSource in the corresponding mappings section.
representsRealmOrContext: The local identifiers of the context(s) in which this value domain applies. Must match a local id of a supportedContext in the corresponding mappings section.
valueDomainURI: The URI of this value domain.
valueDomainName: The name of this domain, if any.
defaultCodingScheme: Local name of the primary coding scheme from which the domain is drawn. defaultCodingScheme must match a local id of a supportedCodingScheme in the mappings section.

Value Domain Definition Entry

A reference to an entry code, a coding scheme or another value domain along with the instructions about how the reference is applied. Definition entrys are applied in entryOrder, with each successive entry either adding to or subtracting from the final set of entity codes.

Attributes of Value Domain Definition Entry :

ruleOrder: The unique identifier of the definition entry within the definition as well as the relative order in which this entry should be applied
operator: How this entry is to be applied to the value domain

Coding Scheme Reference

A reference to all of the entity codes in a given coding scheme.

Attributes of Coding Scheme Reference :

codingScheme: The local identifier of the coding scheme that the entity codes are drawn from . codingSchemeName must match a local id of a supportedCodingScheme in the mappings section.

Value Domain References

A reference to the set of codes defined in another value domain.

Attributes of Value Domain Reference :

valueDomainURI: The URI of the value domain to apply the operator to. This value domain may be contained within the local service or may need to be resolved externally.

Entity Reference

A reference to an entityCode and/or one or more entityCodes that have a relationship to the specified entity code.

Attributes of Entity Reference :

entityCode: The entity code being referenced.
entityCodeNamespace: Local identifier of the namespace of the entityCode. entityCodeNamespace must match a local id of a supportedNamespace in the corresponding mappings section. If omitted, the URI of the defaultCodingScheme will be used as the URI of the entity code.
leafOnly: If true and referenceAssociation is supplied and referenceAssociation is defined as transitive, include all entity codes that are "leaves" in transitive closure of referenceAssociation as applied to entity code. Default: false
referenceAssociation: The local identifier of an association that appears in the native relations collection in the default coding scheme. This association is used to describe a set of entity codes. If absent, only the entityCode itself is included in this definition.
targetToSource: If true and referenceAssociation is supplied, navigate from entityCode as the association target to the corresponding sources. If transitiveClosure is true and the referenceAssociation is transitive, include all the ancestors in the list rather than just the direct "parents" (sources).
transitiveClosure: If true and referenceAssociation is supplied and referenceAssociation is defined as transitive, include all entity codes that belong to transitive closure of referenceAssociation as applied to entity code. Default: false

Definition Operator

The description of how a given definition entry is applied.

Attributes of Definition Operator :

OR: Add the set of entityCodes described by the currentEntity to the value domain. (logical OR)
SUBTRACT: Subtract (remove) the set of entityCodes described by the currentEntity to the value domain. (logical NAND)
AND: Only include the entity codes that are both in the value domain and the definition entry. (logical AND)

LexGrid Pick List Model

Here is a UML representation of Pick List within LexGrid 200901 model:

Image Added

Pick List Definition

An ordered list of entity codes and corresponding presentations drawn from a value domain.

Attributes of Pick List Definition :

Source: The local identifiers of the source(s) of this pick list definition. Must match a local id of a supportedSource in the corresponding mappings section.
pickListId: An identifier that uniquely names this list within the context of the collection.
representsValueDomain: The URI of the value domain definition that is represented by this pick list
defaultEntityCodeNamespace: Local name of the namespace to which the entry codes in this list belong. defaultEntityCodeNamespace must match a local id of a supportedNamespace in the mappings section.
defaultLanguage: The local identifier of the language that is used to generate the text of this pick list if not otherwise specified. Note that this language does NOT necessarily have any coorelation with the language of a pickListEntry itself or the language of the target user. defaultLanguage must match a local id of a supportedLanguage in the mappings section.
defaultSortOrder: The local identifier of a sort order that is used as the default in the definition of the pick list
defaultPickContext: The local identifiers of the context used in the definition of the pick list.
completeDomain: True means that this pick list should represent all of the entries in the domain. Any active entity codes that aren't in the specific pick list entries are added to the end, using the designations identified by the defaultLanguage, defaultSortOrder and defaultPickContext. Default: false

Pick List Entry Node

An inclusion (pickListEntry) or exclusion (pickListEntryExclusion) in a pick list definition

Attributes of Pick List Entry Node :

pickListEntryId: Unique identifier of this node within the list.

Pick List Entry

An entity code and corresponding textual representation.

Attributes of Pick List Entry:

pickText: The text that represents this node in the pick list. Some business rules may require that this string match a presentation associated with the entityCode
pickContext: The local identifiers of the context(s) in which this entry applies. pickContext must match a local id of a supportedContext in the mappings section
entryOrder: Relative order of this entry in the list. pickListEntries without a supplied order follow the all entries with an order, and the order is not defined.
entityCode: Entity code associated with this entry.
entityCodeNamespace: Local identifier of the namespace of the entity code if different than the pickListDefinition defaultEntityCodeNamespace. entityCodeNamespace must match a local id of a supportedNamespace in the mappings section.
propertyId: The property identifier associated with the entityCode and entityCodeNamespace that the pickText was derived from. If absent, the pick text can be anything. Some terminologies may have business rules requiring this attribute to be present.
isDefault: True means that this is the default entry for the supplied language and context.
matchIfNoContext: True means that this entry can be used if no contexts are supplied, even though pickContext ispresent.
Language: The local name of the language to be used when the application/user supplies a selection language matches. If absent, this matches all languages. language must match a local id od of a supportedLanguage in the mappings section.

Pick List Entry Exclusion

An entity code that is explicitly excluded from a pick list.

Attributes of Pick List Entry Exclusion:

entityCode: Entity code associated with this entry.
entityCodeNamespace: Local identifier of the namespace of the entity code if different than the pickListDefinition defaultEntityCodeNamespace. entityCodeNamespace must match a local id of a supportedNamespace in the mappings section.

Value Domain Definitions Possible Forms

• Code system/concept code + relationship + additional rules (leaf only, immediate children, etc)
• Code system - all concept codes in the system
• Code system/concept code - individual code
• Combination of any of the above with OR/AND/SUBTRACT operators

Value Domain Resolution

• A value domain definition has to be made against a specific version of a code system. But it doesn't have to be resolved against the same version.
• Even a simple list (a,b,c,d) needs to be resolved as, at some future date, "c" might be retired.
• Resolution does not create static artifact.

Pick List Definitions Possible Forms

• Value Domain - all concept codes in the value domain
• Code system/concept code - individual code (inclusion and exclusion)

Pick List Resolution

• A picklist definition has to be made against a specific value domain.
• Even a simple list (a,b,c,d) needs to be resolved as, at some future date, "c" might be retired.
• Resolution does not create static artifact.

LexEVS Value Domain and Pick List Service Class Diagram

Common Services Class Diagram

These are the classes that are used commonly across Value Domain and Pick List implementation.

Image Added

Value Domain Class Diagram

Classes that implement LexEVS Value Domain API

Image Added

Pick List Class Diagram

Classes that implements LexEVS Pick List API

Image Added

LexBIG Services Class Diagram

An interface to LexEVS Value Domain and Pick List Services could be obtained using an instance of LexBigService.

Image Added

Main Service API

LexBIG API

An interface to LexEVS Value Domain and Pick List Services could be obtained using an instance of LexBigService.

...

Implementation Details:

...

Step 2 :Call isConceptInDomain method:
AbsoluteCodingSchemeVersionReference acsvr = vds.isConceptInDomain("conceptA","conceptAEntityNamespace",
"codingSchemeVersion","valueDomainURI");

resolveValueDomain(URI valueDomainURI, AbsoluteCodingSchemeVersionReferenceList csVersionList)

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resolveValueDomain(URI valueDomainURI, AbsoluteCodingSchemeVersionReferenceList csVersionList)

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Description:

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Resolve a value domain using the supplied set of coding scheme versions.

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Input:

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java.net.URI,
org.LexGrid.LexBIG.DataModel.Core. AbsoluteCodingSchemeVersionReferenceList

...

...

...

...

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LexEVS Value Domain Service

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API - Loading Value Domain

There are three methods that could be used to load Value Domain Definitions :

...

...

...

csvList.addAbsoluteCodingSchemeVersionReference(Constructors.
createAbsoluteCodingSchemeVersionReference("Automobiles", "2.0"));

csvList.addAbsoluteCodingSchemeVersionReference(Constructors.
_createAbsoluteCodingSchemeVersionReference("AutomobilesParts", "2.0")); _

Step 3 :Call resolveValueDomain method:

ResolvedValueDomainDefinition rvdDef = vds.resolveValueDomain ("valueDomainURI",csvList);

isSubDomain(URI childValueDomainURI, URI parentValueDomainURI)

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isSubDomain(URI childValueDomainURI, URI parentValueDomainURI)

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Description:

...

...

...

...

...

...

...

...

...

...

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boolean isSubDomain = vds.isSubDomain (childValueDomainURI, parentValueDomainURI);

getValueDomainDefinition(URI valueDomainURI)

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getValueDomainDefinition(URI valueDomainURI)

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Description:

...

...

...

...

...

...

...

...

...

...

...

ValueDomainDefinition vdDef = vds.getValueDomainDefinition (valueDomainURI);

listValueDomains(String valueDomainName)

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listValueDomains(String valueDomainName)

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Description:

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Return the URI's for the value domain definition(s) for the supplied domain name. If the name is null, returns everything. If the name is not null, returns the value domain(s) that have the assigned name.
Note: plural because there is no guarantee of valueDomain uniqueness. If the name is the empty string "", returns all unnamed valueDomains.

...

Input:

...

java.lang.String

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<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="852b71bf-02a6-497f-b524-f24a97238c49"><ac:plain-text-body><![CDATA[

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Output:

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java.net.URI[]

...

]]></ac:plain-text-body></ac:structured-macro>

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Exception:

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org.LexGrid.LexBIG.Exceptions.LBException

Validate XML resources

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Implementation Details:

...

...

...

_URI\[\] uris  =  vds.listValueDomains("someValueDomainName");_

getAllValueDomainsWithNoNames()

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getAllValueDomainsWithNoNames()

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Description:

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Return the URI's of all unnamed value domain definition(s).

...

Input:

...

none

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<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="2dbdb848-1650-4989-8fb9-919596072d2f"><ac:plain-text-body><![CDATA[

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Output:

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java.net.URI[]

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]]></ac:plain-text-body></ac:structured-macro>

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Exception:

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org.LexGrid.LexBIG.Exceptions.LBException

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Implementation Details:

Query Value Domain

...

...

...

...

...

_URI\[\] uris  =  vds.getAllValueDomainsWithNoNames();_

getValueDomainEntitiesForTerm(String term, URI valueDomainURI, String matchAlgorithm)

...

...

Resolves the value domain supplied and restricts to the term and matchAlgorith supplied. Return object ResolvedValueDomainCodedNodeSet contains the codingScheme URI and Version that was used to resolve and the CodedNodeSet.
Note : the CodedNodeSet is unresolved

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getCodingSchemesInValueDomain(URI valueDomainURI)

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...

...

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Output:

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...

...

...

...

...

...

...

...

...

...

...

...

...

isDomain(String entityCode, String codingSchemeName, CodingSchemeVersionOrTag csvt)

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...

...

...

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Remove Value Domain Definition

...

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removeValueDomain(URI valueDomainURI)

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removeAllValueDomains()

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Drop Value Domain tables

...

...

dropValueDomainTables()

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...

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LexEVS Pick List Service API

Loading Pick List

There are three methods that could be used to load Pick List Definitions :

loadPickList(PickListDefinition pldef, String systemReleaseURI)

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loadPickList(PickListDefinition pldef, String systemReleaseURI)

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Description:

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Loads supplied Pick List Definition object

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Input:

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org.LexGrid.emf.valueDomains.PickListDefinition,
_String _

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Output:

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none

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Exception:

...

...

...

...

...

...

...

...

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And data for pickList object can be populated by using set methods :
pickList.setPickListId(pickListId);
pickList.setRepresentsValueDomain(vdURI);
pickList.setCompleteDomain(true);
pickList.setDefaultEntityCodeNamespace(ecns);
pickList.setDefaultLanguage("en");
pickList.setDefaultSortOrder("asc");
pickList.setIsActive(true);
pickList.setEntityDescription(ed);

Similarly, PickListEntryNode, Property, Mapping objects can be created and assign to the pickList object.
pickList.getPickListEntryNode.add(pickListEntry);
pickList.setProperties(propertisObject);
_pickList.setMappings(mappingsObject); _

Step 3 : call the load method by passing the Pick List Definition object and the System Release URI :
pls.loadPickList(pickList,"Release 2009");

loadPickList(InputStream inputStream, boolean failOnAllErrors)

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loadPickList(InputStream inputStream, boolean failOnAllErrors)

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Description:

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Loads Pick List Definitions found in inputStream

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Input:

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java.io.InputStream
boolean

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Output:

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none

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Exception:

...

...

...

...

...

...

...

...

...

...

...

loadPickList (String xmlFileLocation, boolean failOnAllErrors)

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loadPickList (String xmlFileLocation, boolean failOnAllErrors)

Remove Value Domain Definition

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Description:

...

...

...

...

...

...

...

...

...

...

...

...

...

...

Validate XML resources

validate(URI uri, int valicationLevel) throws LBParameterException

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validate(URI uri, int valicationLevel) throws LBParameterException

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Description:

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...

java.net.URI
int

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...

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...

_ pls.validate(uriOfXMLFile, true);_

Query Pick List

getPickListDefinitionById(String pickListId)

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getPickListDefinitionById(String pickListId)

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Description:

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Returns pickList definition for supplied pickListId.

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Input:

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java.lang.String

Drop Value Domain tables

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Output:

...

...

...

...

...

...

...

...

...

...

...

...

LexEVS Pick List Service API

Loading Pick List

There are three methods that could be used to load Pick List Definitions :

getPickListDefinitionsForDomain(URI valueDomainURI)

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