LexEVS 101 Craig Stancl Rick Kiefer February, 2010.

Slides:



Advertisements
Similar presentations
Dr. Leo Obrst MITRE Information Semantics Information Discovery & Understanding Command & Control Center February 6, 2014February 6, 2014February 6, 2014.
Advertisements

Overview of LexEVS 5.0 LexEVS Architecture November, 2009.
CACORE TOOLS FEATURES. caCORE SDK Features caCORE Workbench Plugin EA/ArgoUML Plug-in development Integrated support of semantic integration in the plugin.
Database System Concepts and Architecture
LexBIG/EVS API Overview NCBO Seminar Series October 2008.
LexGrid for cBIO Division of Biomedical Informatics Mayo Clinic Rochester, MN.
© Copyright 2008, Mayo Clinic College of Medicine Mayo Clinic Open Health Tools Application for Membership OHT Board Meeting, Birmingham, UK July 1, 2008.
CaBIG™ Terminology Services Path to Grid Enablement Thomas Johnson 1, Scott Bauer 1, Kevin Peterson 1, Christopher Chute 1, Johnita Beasley 2, Frank Hartel.
1 Introduction to XML. XML eXtensible implies that users define tag content Markup implies it is a coded document Language implies it is a metalanguage.
Technical Architectures
Software Frameworks for Acquisition and Control European PhD – 2009 Horácio Fernandes.
CS CS 5150 Software Engineering Lecture 13 System Architecture and Design 1.
System Design/Implementation and Support for Build 2 PDS Management Council Face-to-Face Mountain View, CA Nov 30 - Dec 1, 2011 Sean Hardman.
Talend 5.4 Architecture Adam Pemble Talend Professional Services.
Value Domain and Pick List Support in LexEVS 5.1 Sridhar Dwarkanath Mayo Clinic CaBIG Architecture/VCD Joint Workspace F2F.
31 January 2007Craig E. Ward1 Large-Scale Simulation Experimentation and Analysis Database Programming Using Java.
PHASE 3: SYSTEMS DESIGN Chapter 7 Data Design.
Construction of efficient PDP scheme for Distributed Cloud Storage. By Manognya Reddy Kondam.
OpenMDR: Generating Semantically Annotated Grid Services Rakesh Dhaval Shannon Hastings.
Database System Concepts and Architecture Lecture # 3 22 June 2012 National University of Computer and Emerging Sciences.
OpenMDR: Alternative Methods for Generating Semantically Annotated Grid Services Rakesh Dhaval Shannon Hastings.
LexEVS 6.0 Overview Scott Bauer Mayo Clinic Rochester, Minnesota February 2011.
1 LexEVS 5.0 Advanced Topics Configuration Options LexEVS Boot Camp November, 2009.
Fundamentals of Database Chapter 7 Database Technologies.
LexEVS Overview Mayo Clinic Rochester, Minnesota June 2009.
Using the Open Metadata Registry (openMDR) to create Data Sharing Interfaces October 14 th, 2010 David Ervin & Rakesh Dhaval, Center for IT Innovations.
SAMANVITHA RAMAYANAM 18 TH FEBRUARY 2010 CPE 691 LAYERED APPLICATION.
1 Overview of the Application Hosting Environment Stefan Zasada University College London.
LexEVS in a caGrid Environment Interacting with LexEVS 5.0 November 2009.
XML Registries Source: Java TM API for XML Registries Specification.
LexBIG Release Overview Aug 21, LexBIG Context Project Goals for Sept –Incremental point release of LexBIG infrastructure to support EVS activities.
1 Schema Registries Steven Hughes, Lou Reich, Dan Crichton NASA 21 October 2015.
Value Set Resolution: Build generalizable data normalization pipeline using LexEVS infrastructure resources Explore UIMA framework for implementing semantic.
1.file. 2.database. 3.entity. 4.record. 5.attribute. When working with a database, a group of related fields comprises a(n)…
Database Design and Management CPTG /23/2015Chapter 12 of 38 Functions of a Database Store data Store data School: student records, class schedules,
Open Terminology Portal (TOP) Frank Hartel, Ph.D. Associate Director, Enterprise Vocabulary Services National Cancer Institute, Center for Biomedical Informatics.
LexBIG/LexGrid Services for LexBIG 2.3 Model and API for the Grid.
1 CS 430 Database Theory Winter 2005 Lecture 2: General Concepts.
Efficient RDF Storage and Retrieval in Jena2 Written by: Kevin Wilkinson, Craig Sayers, Harumi Kuno, Dave Reynolds Presented by: Umer Fareed 파리드.
Presented by Scientific Annotation Middleware Software infrastructure to support rich scientific records and the processes that produce them Jens Schwidder.
LexEVS Semantic Tooling Advancements Kevin Peterson Mayo Clinic Mayo 2009.
Common Terminology Services 2 CTS 2 Submission Team Status Update HL7 Vocabulary Working Group May 17, 2011.
Overview of LexEVS 5.0 LexGrid 2009 Model November, 2009.
1 Service Creation, Advertisement and Discovery Including caCORE SDK and ISO21090 William Stephens Operations Manager caGrid Knowledge Center February.
1 Registry Services Overview J. Steven Hughes (Deputy Chair) Principal Computer Scientist NASA/JPL 17 December 2015.
EVS 4.0 Feature Overview EVS API and User Interface pBIO Meeting March 20, 2007 Frank Hartel Gilberto Fragoso
EbiTrack Architecture Version 1.0 September 24, 2012.
Handling Semantic Data for Software Projects Data Management CSE G674 – SW Engineering Project.
REST By: Vishwanath Vineet.
In Vivo Imaging Middleware and Applications RSNA 2007 Berkant Barla Cambazoglu The Ohio State University Department of Biomedical Informatics.
LexEVS 5.0 EVS to LexEVS: A Migration Guide November, 2009.
Design for a High Performance, Configurable caGrid Data Services Platform Peter Hussey LabKey Software, Inc, Seattle, WA USA Contact:
Improving User Access to Metadata for Public and Restricted Use US Federal Statistical Files William C. Block Jeremy Williams Lars Vilhuber Carl Lagoze.
CaBIG™ Terminology Services Path to Grid Enablement Thomas Johnson 1, Scott Bauer 1, Kevin Peterson 1, Christopher Chute 1, Johnita Beasley 2, Frank Hartel.
Copyright 2007, Information Builders. Slide 1 iWay Web Services and WebFOCUS Consumption Michael Florkowski Information Builders.
2) Database System Concepts and Architecture. Slide 2- 2 Outline Data Models and Their Categories Schemas, Instances, and States Three-Schema Architecture.
National Cancer Institute 1 1 LexBIG integration caCORE Software User Meeting Aug 7, 2006.
LexEVS 5.0: Migrating from EVS 3.x API to LexEVS API Craig R. Stancl, Kevin J. Peterson, H. Scott Bauer, Traci V. St.Martin, Christopher G. Chute, MD PhD.
Interacting with LexEVS 5.0 LexEVS in a Distributed Environment November 2009.
Introduction to Core Database Concepts Getting started with Databases and Structure Query Language (SQL)
 Project Team: Suzana Vaserman David Fleish Moran Zafir Tzvika Stein  Academic adviser: Dr. Mayer Goldberg  Technical adviser: Mr. Guy Wiener.
ISC321 Database Systems I Chapter 2: Overview of Database Languages and Architectures Fall 2015 Dr. Abdullah Almutairi.
Databases (CS507) CHAPTER 2.
Databases and DBMSs Todd S. Bacastow January 2005.
What are they? The Package Repository Client is a set of Tcl scripts that are capable of locating, downloading, and installing packages for both Tcl and.
Database System Concepts and Architecture
Open Source distributed document DB for an enterprise
Copyright © 2011 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 2 Database System Concepts and Architecture.
Lecture 1: Multi-tier Architecture Overview
SDMX IT Tools SDMX Registry
Presentation transcript:

LexEVS 101 Craig Stancl Rick Kiefer February, 2010

LexGrid Model Overview The LexGrid Model is Mayo’s proposed mechanism for standard storage of controlled vocabularies and ontologies: Defines HOW vocabularies should be formatted and represented Flexible enough to accurately represent a wide variety of vocabularies and other lexically-based resources Defines several different server storage mechanisms and a XML format Provides the core representation for all data managed and retrieved through the LexEVS system Once the vocabulary information is represented in a standardized format, it becomes possible to build common repositories to store vocabulary content and common programming interfaces and tools to access and manipulate that content. Terminologies from widely varying resources such as RRF, OWL, and OBO can be loaded to a single data base management system and accessed with an single API. The LexGrid model stands alone as a complete terminology model

LexBIG Model Overview LexBIG provides references into the data model without requiring resolution of the a complete terminology node set or graph. As such it functions as a kind of lazy loading mechanism, similar to what can be found in Hibernate. Elements of LexBIG that are resolved in a minimal manner can often avoid database calls by referring to a Lucene index, saving response time.

LexGrid, LexBIG and LexEVS LexEVS: Optimizing query code that retrieves LexBIG objects. LexBIG: How the terminology service looks as objects returned to the user. LexGrid: How the terminology service looks in a data base. LexGrid Data base LexBIG Objects LexEVS API LexEVS uses the LexBIG model in conjunction with the LexGrid model

LexEVS Environment Architecture LexEVS consists of LexGrid Model & Storage, LexEVS Java API, LexEVS Distributed Service and LexEVS caGrid Service. LexEVS caGrid Service LexEVS Distributed / SDK Service LexEVS Java API LexGrid Model & Storage

LexEVS API - Local/Direct Now we will discuss LexEVS API. LexEVS Java API LexGrid Model & Storage

LexEVS API - Local/Direct The direct/local API consists of LexEVS on a local system (LexEVS installed). The API uses JDBC query the LexEVS database. Database Server LexEVS on Local System LexEVS Install JDBC Direct

8 LexEVS API - Local/Direct The LexEVS Local Installation is the foundation of the LexEVS System as a whole. All of the other Environments rely on this being available and configured properly. Some characteristics of the Local installation are: Java based Installed via GUI install program, or command line Some indexes (Lucene-based) are held on the local file system Includes the LexEVS GUI Includes a full set of Administration scripts to maintain the server Optionally includes Testing resources, Source Code, JavaDocs, and more…

Model Objects LexEVS caCORE SDK APIs Java API LexGrid MySQL DB Lucene Index Files Distributed Java LexEVS caGrid API Java (QBE) Application Service Client Web/Grid Service (Soap/HTTP/Rest) Java (RMI) ( Distributed) Client Application Core API Data Source RMI LexEVS API - Local/Direct In a local environment, an application uses the Java API to access content in LexEVS.

LexEVS API – Distributed / SDK Now we will discuss LexEVS Distributed API. LexEVS Distributed / SDK Service LexEVS Java API LexGrid Model & Storage

LexEVS API – Distributed / SDK The distributed Java/SDK consists of a client system which uses RMI to communicate with a distributed LexEVS server where LexEVS API is installed. The API uses JDBC query the LexEVS database. Database Server Distributed LexEVS Server RMI LexEVS on Local System LexEVS Install Database Server LexEVS Install JDBC Direct Distributed / SDK LexBIG API Proxy Client System LexEVS Client Proxy

12 LexEVS API – Distributed / SDK The LexEVS Distributed Installation is actually two services combined as one application. Remote Access (via Remote Method Invocation) to the local LexEVS API A caCORE SDK Service conforming to all of the caCORE Service Interfaces. The key feature of the Distributed environment is that it exposes the fully LexEVS API to clients, while centralizing the actual vocabulary content in one place. This lets users have a single set of loaded ontologies – instead of multiple sets for multiple users – which reduces maintenance and increases usability. The Distributed Layer is also the first LexEVS environment to employ any type of Ontology-based security. It uses Security Tokens to restrict licensed ontologies (i.e. MedDRA).

LexEVS API – Distributed / SDK Remote Access (via Remote Method Invocation) to the local LexEVS API Any method that can be called locally is also available remotely (with the exception of certain administration functionality, which is disabled for security purposes).

Model Objects LexEVS caCORE SDK APIs Java API LexGrid MySQL DB Lucene Index Files Distributed Java LexEVS caGrid API Java (QBE) Application Service Client Web/Grid Service (Soap/HTTP/Rest) Java (RMI) ( Distributed) Client Application Core API Data Source RMI LexEVS API – Distributed / SDK In a distributed environment, the client application uses the Distributed Java API (RMI) to access content in LexEVS or caCORE SDK Services which include REST, SOAP, RMI Interfaces for QBE, HQL, Hibernate Detached Criteria, SDK CQL, caGrid CQL.

LexEVS API – Distributed / SDK A caCORE SDK Service conforming to all of the caCORE Service Interfaces. This includes: REST-ful service caCORE-SDK SOAP Web Service Query By Example (QBE) Java RMI Interfaces A Web-based interface to the REST-ful service

LexEVS API – Distributed / SDK In a distributed environment, the client application uses the Distributed Java API (RMI) to access content in LexEVS or caCORE SDK Services which include REST, SOAP, RMI Interfaces for QBE, HQL, Hibernate Detached Criteria, SDK CQL, caGrid CQL. Model Objects LexEVS caCORE SDK APIs Java API LexGrid MySQL DB Lucene Index Files Distributed Java LexEVS caGrid API Java (QBE) Application Service Client Web/Grid Service (Soap/HTTP/Rest) Java (RMI) ( Distributed) Client Application Core API Data Source RMI

LexEVS API – caGrid Service Now we will discuss LexEVS caGrid Service LexEVS caGrid Service LexEVS Distributed / SDK Service LexEVS Java API LexGrid Model & Storage

LexEVS on Local System LexEVS Install Database Server Distributed LexEVS Server RMI Database Server LexEVS Install JDBC Direct Distributed / SDK Database Server LexBIG API Proxy Client System caGrid Host Server Client System Distributed LexEVS Server RMI LexEVS Install Grid JDBC TCP LexEVS Proxy LexEVS Client Proxy LexEVS API – caGrid Service The caGrid Service consists of client system, caGrid Host Server, Distributed LexEVS Server and Database Server.

19 LexEVS API – caGrid Service LexEVS has two deployed caGrid Services, one Analytical Service and one Data Service. They are both available and discoverable through the caGrid Portal/Index Service Analytical Service Exposes the LexEVS API in much the same way as the Local and Distributed Environments do – except as a Grid Service. A user may again use familiar Interfaces (LexBIGService, CodedNodeSet, CodedNodeGraph, etc.) to interact with the Analytical Grid Service Data Service The Data Service simply exposes the LexGrid model as a caGrid Data Service. Like any standard caGrid Data Service, CQL queries are used to query the data source.

Model Objects LexEVS caCORE SDK APIs Java API LexGrid MySQL DB Lucene Index Files Distributed Java LexEVS caGrid API Java (QBE) Application Service Client Web/Grid Service (Soap/HTTP/Rest) Java (RMI) ( Distributed) Client Application Core API Data Source RMI LexEVS API – caGrid Service In grid services environment, the client application calls the grid services interfaces which in turn call the distributed Java API to access content in LexEVS.

21 Choosing an Environment LexEVS Environments – Which one to use? Choosing the right Environment for your needs is important. Each of the Environments adds complexity and maintenance to the system. Also, performance plays a factor as each added Environment adds overhead. Local Best Performance, easiest installation. Use this when Performance is critical and there isn’t a need to directly expose the LexEVS API to other users. Distributed Use this to directly expose the LexEVS API to multiple users – while sharing only one set of loaded ontologies. The RMI overhead decreases performance slightly from the Local Environment. Also, if caCORE SDK-like functionality is need, this Environment is required. Grid The most complex to set up – use this if users need a functioning caGRID Node. This adds another layer of overhead, so performance will be impacted the most in this Environment.

22 Services Overview The LexEVS Service is designed to run standalone or as part of a larger network of services. It is comprised of four primary subsystems: Service Manager Service Metadata Query Service Extensions

23 Services: Service Manager LexEVS Service - Service Manager The service manager provides a centralized access point for administrative functions, including write and update access for a service's content. For example, the service manager allows new coding schemes to be validated and loaded, existing coding schemes to be retired and removed, and the status of various coding schemes to be updated and changed.

24 Services: Metadata Service LexEVS Service – Metadata Service The Service Metadata provides external clients with information about the vocabulary content (e.g. NCI Thesaurus) and appropriate licensing information.

25 Services: Query Operations LexEVS Service - Query Operations The Query Operations provide numerous functions for querying and traversing vocabulary content. The Query Service is comprised of: Lexical Operations Graph Operations Metadata Operations History Operations

26 Query Service: Lexical Set Operations Query Service - Lexical Set Operations Lexical Set Operations provides methods to return a lists or iterators of coded entries. Supported query criteria include the application of match/filter algorithms, sorting algorithms, and property restrictions. Support is also provided to resolve the union, intersection or difference of two node sets.

27 Query Service: Graph Operations Query Services - Graph Set Operations Graph Operations support the subsetting of concepts according to relationship and distance, identification of relation source and target concepts, and graph traversal. Additional operations include enumeration and traversal of concepts by relation, walking of directed acyclic graphs (DAGs), enumeration of source and target concepts for a relation, and enumeration of relations for a concept.

28 Query Service: Metadata Operations Query Services - Metadata Operations Metadata Operations allows for the query and resolution of registered code system metadata according to specified coding scheme references, property names, or values.

29 Query Service: History Query Services - History History provides vocabulary-specific information about concept insertions, modifications, splits, merges, and retirements when supplied by the content provider.

30 Services: Extensions Extensions The Extensions component provides a mechanism to extend the specific service functions, such as Loaders, or re-wrap specific query operations into convenience methods.

For More Information… Vocabulary Knowledge Center Wiki Vocabulary Knowledge Center Forums Vocabulary Knowledge Center