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EVS has enjoyed wide use and many collaborations within caBIG® and other organizations in the cancer research and biomedical community. Institutional profiles are followed by thematic efforts that span multiple institutions:


Duke University

Duke University and EVS have collaborated for several years, together with other partners such as CDISC, NHLBI, and the American College of Cardiology, in the development of shared terminology and other standards involving clinical trials, case report forms, cardiology, tuberculosis, and other content.

Emory University

Emory University has deployed and extended several EVS resources. Emory is using LexEVS to develop and host local ontologies. Uses include terminology support for an analytic data warehouse, which incorporates custom patient classes defined using ICD-9 codes.

Related Articles

  1. Vergara-Niedermayr C, Wang F, Pan T, Kurc T, Saltz J.
    Semantically Interoperable XML Data.
    Emory University Center for Comprehensive Informatics Technical Report CCI-TR-2012-1, January 12, 2012. [Emory]
  2. Zheng S, Wang F, Lu J, Saltz J.
    Enabling Ontology Based Semantic Queries in Biomedical Database Systems.
    Emory University Center for Comprehensive Informatics Technical Report CCI-TR-2012-3, March 20, 2012. [Emory]

General Electric (GE)

GE is developing a platform called Qualibria, which includes LexEVS as a terminology server. VKC has been working with GE since 2008. As part of the collaboration, GE created an extension to the LexEVS 5.1 API based on the Common Terminology Services specification. GE provided the code for that extension, which is now available to the community via the VKC web site. This is an example of NCI open source technology being bundled into a commercial healthcare product.

Georgetown University

Georgetown uses LexEVS and other EVS resources for its cancer Bench-to-Bedside (caB2B) project and other translational medicine activities. Both a local LexEVS installation and NCI's production LexEVS servers provide terminology support for this project.

Mayo Clinic

Mayo Clinic has partnered with, supported and used EVS resources in a variety of ways over many years. Mayo both develops and uses LexEVS.

Pharmacogenomics Research Network (PGRN) Ontology Network Resource (PHONT)

Mayo Clinic is the primary site for PHONT [], a leading user of EVS resources supporting clear annotation and representation of phenotype (disease, adverse event, or clinical and physiological outcomes) to support data integration and cross-database analyses, collaborating with Case Western Reserve University, Harvard Medical School, MD Anderson Cancer Center, Memorial Sloan Kettering Cancer Center, University of Erlangen, and Washington University.

Strategic Health IT Advanced Research Projects: Area 4 - Secondary Use of EHR Data (SHARPn)

SHARPn [[http:/]] uses LexEVS to help enable the reuse of EHR data for secondary purposes, such as clinical research and public health, as part of the Office of the National Coordinator for Health Information Technology SHARP Program.

Related Articles
(see also: LexEVS section of Bibliography on EVS and Its Use)

  1. Chute CG, Carter JS, Tuttle MS, Haber MW, Brown SH.
    Integrating pharmacokinetics knowledge into a drug ontology as an extension to support pharmacogenomics.
    AMIA Annu Symp Proc. 2003:170-4. PubMed PMID: 14728156; PubMed Central PMCID: PMC1480302. [PubMed] [Free PMC Article]
  2. Chute CG, Pathak J, Savova GK, Bailey KR, Schor MI, Hart LA, Beebe CE, Huff SM.
    The SHARPn project on secondary use of Electronic Medical Record data: progress, plans, and possibilities.
    AMIA Annu Symp Proc. 2011;2011:248-56. Epub 2011 Oct 22. PubMed PMID: 22195076; PubMed Central PMCID: PMC3243296. [PubMed]
  3. Gwaltney K, Chute C, Hageman D, Kibbe W, McCormick K, Reeves D, Wright L.
    An assessment of cancer clinical trials vocabulary and IT infrastructure in the U.S.
    Proc AMIA Symp. 2001:224-8. PubMed PMID: 11825185; PubMed Central PMCID: PMC2243595. [PubMed] [Free PMC Article]
  4. Jiang G, Solbrig HR, Iberson-Hurst D, Kush RD, Chute CG.
    A Collaborative Framework for Representation and Harmonization of Clinical Study Data Elements Using Semantic MediaWiki.
    AMIA Summits Transl Sci Proc. 2010 Mar 1;2010:11-5. PubMed PMID: 21347136; PubMed Central PMCID: PMC3041544. [PubMed]
  5. Liu K, Chapman WW, Savova G, Chute CG, Sioutos N, Crowley RS.
    Effectiveness of Lexico-syntactic Pattern Matching for Ontology Enrichment with Clinical Documents.
    Methods Inf Med. 2011;50(5):397-407. Epub 2010 Nov 8. [PubMed]
  6. Pathak J, Wang J, Kashyap S, Basford M, Li R, Masys DR, Chute CG.
    Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network experience.
    J Am Med Inform Assoc. 2011 Jul-Aug;18(4):376-86. Epub 2011 May 19. PubMed PMID: 21597104; PubMed Central PMCID: PMC3128396. [PubMed]

MD Anderson

MD Anderson is using a local LexEVS server as part of their enterprise infrastructure. Special resources were dedicated to resolving initial software compatibility and other issues, ensuring a successful deployment. NCI EVS terminology browsers have also been deployed, as have NCIt and other EVS terminology resources. This is an example of leveraging a wide range of EVS resources and services in support of the research and clinical enterprise infrastructure of a leading cancer center.

Ohio State University Medical Center

Ohio State is using LexEVS, NCIt, and NCIm, notably for openMDR. Ohio State University launched openMDR (open metadata repository) in 2009, using local instances of LexEVS, BioPortal, and caDSR. This is an example of an academic research group adopting several open source components of NCI's EVS and semantic infrastructure, and integrating them to create a novel tool for metadata management.

Seoul National University, Korea

The Biomedical Knowledge Engineering (BiKE) lab adopted the 2005 version of the LexGrid model and over the last several years created an entire terminology-based application suite on that model called LexCare Suite. The VKC facilitated the signing of an agreement between Mayo Clinic and SNU's BiKE to solidify a collaboration under which they will work together on conferences and papers surrounding terminology creation/mapping/use. The BiKE mapping tool is of particular interest for a community tool in this regard. This would be a potentially significant contribution, as it would add a new tool in an area with a known gap in the current functionality of LexEVS.

Stanford University

National Center for Biomedical Ontology (NCBO)

NCBO [] bases its BioPortal terminology services on LexEVS. NCIt is generally at or near the top of the NCBO ontology use chart (see section 3 above). NCBO and EVS maintain ongoing coordination and harmonization efforts through both caBIG® and other channels. For example, NCBO participates in the VCDE working group on Representing Terminology Metadata, which is adapting work begun by NCBO in this area for use by NCI and NCRI. NCBO also makes its terminologies available through caGrid.

NCBO built its NCBO BioPortal ontology services on top of LexEVS, supporting a very wide collection of ontologies that are actively used in biomedicine. This is an example of how two federally-funded groups are working together on the development of resources that will benefit the biomedical terminology community.

Tissue Microarray Database (TMAD)

TMAD [] is an important public resource for raw and processed data (with stained tissue images) from tissue microarray experiments. TMAD uses NCI Thesaurus to index, browse and search tissues, and provides methods for data retrieval, grouping of data, analysis and visualization as well as export to standard formats.

University of Pittsburgh

Pittsburgh uses the NCI Thesaurus cancer, anatomy, and pathology findings terminologies for their research and informatics projects. This collaboration has resulted in the publication of several papers.

Ontology Development Information Extraction (ODIE)

ODIE [] is a software toolkit that uses ontologies, including NCIt, to perform information extraction tasks from clinical documents and uses clinical documents to enhance existing ontologies. ODIE is used by the University of Pittsburgh, University of California, San Diego, and Children's Hospital, Boston.

Related Articles

  1. Amin W, Kang HP, Becich MJ.
    Data Management, Databases, and Warehousing.
    Biomedical Informatics for Cancer Research. (M.F. Ochs, J.T. Casagrande, R.V. Davuluri, eds). DOI 10.1007/978-1-4419-5714-6_3, © Springer Science+Business Media, LLC 2010. pp.39-71.
  2. Crowley RS, Castine M, Mitchell K, Chavan G, McSherry T, Feldman M.
    caTIES: a grid based system for coding and retrieval of surgical pathology reports and tissue specimens in support of translational research.
    J Am Med Inform Assoc. 2010 May-Jun;17(3):253-64. PubMed PMID: 20442142; PubMed Central PMCID: PMC2995710. [PubMed] [Full Text]
  3. Crowley RS, Tseytlin E, Jukic D.
    ReportTutor - an intelligent tutoring system that uses a natural language interface.
    AMIA Annu Symp Proc. 2005:171-5. PubMed PMID: 16779024; PubMed Central PMCID: PMC1560511. [PubMed]
  4. Kang HP, Borromeo CD, Berman JJ, Becich MJ.
    The tissue microarray OWL schema: An open-source tool for sharing tissue microarray data.
    J Pathol Inform. 2010 Jul 13;1. pii: 9. PubMed PMID: 20805954; PubMed Central PMCID: PMC2929536. [PubMed]
  5. Liu K, Chapman WW, Savova G, Chute CG, Sioutos N, Crowley RS.
    Effectiveness of Lexico-syntactic Pattern Matching for Ontology Enrichment with Clinical Documents.
    Methods Inf Med. 2011;50(5):397-407. Epub 2010 Nov 8. [PubMed]
  6. Tobias J, Chilukuri R, Komatsoulis GA, Mohanty S, Sioutos N, Warzel DB, Wright LW, Crowley RS.
    The CAP Cancer Protocols – A Case Study of caCORE Based Data Standards Implementation to Integrate with the Cancer Biomedical Informatics Grid.
    BMC Medical Informatics Decision Making, 20; 6:25, 2006. [Free PMC Article]

Washington University

Washington University uses LexEVS and EVS terminology content in its clinical data warehouse project (CIDER). Washington University deployed LexEVS in 2008 as the terminology server for CIDER. The terminologies are used to code data and for information retrieval. This is an example of an academic medical center adopting NCI EVS technology to support research and clinical enterprise infrastructure.

Yale University

Yale University has used EVS resources in several biomedical research and informatics projects, including some with a special focus on semantic web technologies.

Related Articles

  1. McCusker JP, Phillips JA, González Beltrán A, Finkelstein A, Krauthammer M.
    Semantic web data warehousing for caGrid.
    BMC Bioinformatics. 2009 Oct 1;10 Suppl 10:S2. PubMed PMID: 19796399; PubMed Central PMCID: PMC2755823. [PubMed]
  2. Shifman MA, Li Y, Colangelo CM, Stone KL, Wu TL, Cheung KH, Miller PL, Williams KR.
    YPED: a web-accessible database system for protein expression analysis.
    J Proteome Res. 2007 Oct;6(10):4019-24. Epub 2007 Sep 15. PubMed PMID: 17867667. [PubMed]

Project and Topical

Common Biorepository Model (CBM)

EVS has provided about 1,300 concepts for this model through support for caDSR. CBM is used in many domains including clinical trials management, ICR, in vivo imaging, and tissue banks and pathology tools. In early 2012, EVS provided support for mapping SNOMED concepts used in caTissue with NCIt concepts used in CBM, to facilitate data sharing.

eMERGE Network

The eMERGE (electronic MEdical Records and GEnomics) Network [] was initiated by National Human Genome Research Institute (NHGRI) in 2007 as a national research consortium to develop, disseminate, and apply research methods that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research. EVS terminology plays an important role these efforts, notably through use in the eleMAP tool [] developed at Vanderbilt to help researchers harmonize their local phenotype data dictionaries to existing metadata and terminology standards.

Related Articles

  1. Pathak J, Wang J, Kashyap S, Basford M, Li R, Masys DR, Chute CG.
    Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network experience.
    J Am Med Inform Assoc. 2011 Jul-Aug;18(4):376-86. Epub 2011 May 19. PubMed PMID: 21597104; PubMed Central PMCID: PMC3128396. [PubMed]

Human Studies Database (HSDB) Consortium

HSDB is using LexEVS as a core component of its collaborative, distributed, clinical research systems. The OCRe Terminology is served through an NCBO site, which uses LexEVS. This is an example of a consortium of institutions leveraging LexEVS terminology services at the core of a new workflow for the collection of human studies data.

Imaging Standards

Imaging standards development requires the support of multiple products made available through EVS, including publication of RadLex terminology, developed through a collaboration of the Radiological Society of North America (RSNA), which convened experts in imaging informatics and radiological subspecialties to create this resource, now made freely available. RadLex has developed into a rich, structured radiology-specific ontology, which currently includes more than 30,000 terms and to which EVS provides content as well as publication support. EVS incorporates RadLex into the NCI Metathesaurus, and also supports imaging terminology in the NCI Thesaurus as needed by the imaging community.

Related Articles

  1. Hazen R, Van Esbroeck AP, Mongkolwat P, Channin DS.
    Automatic Extraction of Concepts to Extend RadLex.
    Journal of Digital Imaging 2011 Feb;24(1):165-169. [PDF]
  2. Lacson R, Andriole KP, Prevedello LM, Khorasani R.
    Information from Searching Content with an Ontology-Utilizing Toolkit (iSCOUT).
    Journal of Digital Imaging 2012 Feb 14:1-8 [Epub ahead of print] PubMed PMID: 22349993. [PubMed] [Online]
  3. Warden GI, Lacson R, Khorasani R.
    Leveraging Terminologies for Retrieval of Radiology Reports with Critical Imaging Findings.
    AMIA Annu Symp Proc. 2011 Oct;2011:1481-8. Epub 2011 Oct 22. PubMed PMID: 22195212; PubMed Central PMCID: PMC3243125. [PubMed]

LexEVS Adopter Community

Many caBIG® and other organizations have adopted the LexEVS terminology server and related tools. Key examples described in the institutional portion of this section are:

  1. Emory University
  2. GE
  3. MD Anderson
  4. Mayo Clinic (incl. PHONT and SHARPn)
  5. McGill University Health Center, Canada
  6. Ohio State University Medical Center
  7. Seoul National University, Korea
  8. Stanford/National Center for Biomedical Ontology (NCBO)
  9. Washington University

For literature references, see the LexEVS section of Bibliography on EVS and Its Use.


Nanotechnology, and more specifically nanomedicine, has become important in the development of reagents for cancer detection and treatment. NCI established Cancer Centers of Nanotechnology Excellence (CCNE) to support translational nanomedical research. EVS provides assistance in curating concept definitions with the community, making them available in NCIt; a glossary of these terms also is provided within the caNanoLab application (see below).

Nanotechnology Working Group

caBIG® has established a Nanotechnology Working Group as part of its Integrative Cancer Research Workspace (ICR Nano WG) with a mission to federate nanotechnology databases.  The Nanotechnology Working Group includes about 60 people representing approximately 40 agencies, universities and institutes, a few from Europe.  One requirement of this group has been to develop data and vocabulary standards to facilitate federation and increase data accessibility. EVS is contributing to this effort as an active participant in the working group. Part of the working group effort is the continuing development of the Nanoparticle Ontology (NPO) from Washington University in St. Louis. EVS has supported this effort in several areas: giving feedback on ontology structure and terminology best practices, supporting NPO curation using the NCI Protégé platform, loading and hosting NPO on LexEVS, preparing NPO for integration into the NCI Metathesaurus (NCIm), and planning for future editing of NPO in the BiomedGT Wiki collaborative editing environment.


The NCI CCNE office partnered with CBIIT in 2006 to develop a data sharing platform called caNanoLab.  caNanoLab has a goal of semantic interoperability across centers performing nanoparticle characterization studies. caNanoLab is based on an information model representing nanoparticles and their physical and in vitro characterization.  NCI Thesaurus (NCIt) has been supporting concept curation for development of caNanoLab since its inception. NCIt editors have worked with the developers and users of caNanoLab from the CCNEs and other academic institutions to define concepts for data curation and to expand the object model to include data submission for both characterizations of experimental nanomaterials and translational research studies.  Funding for additional development was recently lost, but caNanoLab continues to be heavily used.  It currently contains 886 samples, 72 sample sources, 3,329 characterizations, and 41 protocols, and identifies 1,073 publications. The caNanoLab homepage shows 141,668 visitors since June 3, 2010.


Developed by CBIIT, Oregon State University, PNNL, Washington University St. Louis, Stanford, Jackson Labs, Pennsylvania BioNano Systems, NIOSH, NCI Frederick NCL, Emory/Georgia Tech. This tool is used by all members of the ICR Nano Working Group. Despite recent loss of caNanoLab funding, NanoTAB continues to be used heavily.

NanoParticle Ontology (NPO)

This terminology is loaded in NCI Metathesaurus, on LexEVS, and on the NCI Term Browser. NPO curators use the NCI Protégé curation tool and they use NCI Thesaurus as a cross-reference and a source for some of their definitions.

Related Articles

  1. Bailey LO, Kennedy CH, Fritts MJ, Hartel FW.
    Development of a model for the representation of nanotechnology-specific terminology.
    AMIA Annu Symp Proc. 2006:849. PubMed PMID: 17238469; PubMed Central PMCID: PMC1839578. [PubMed]
  2. Thomas DG, Klaessig F, Harper SL, Fritts M, Hoover MD, Gaheen S, Stokes TH, Reznik-Zellen R, Freund ET, Klemm JD, Paik DS, Baker NA.
    Informatics and standards for nanomedicine technology.
    Wiley Interdiscip Rev Nanomed Nanobiotechnol. 2011 Jun 30. doi: 10.1002/wnan.152. Epub ahead of print. PubMed PMID: 21721140. [PubMed]
  3. Thomas DG, Pappu RV, Baker NA.
    NanoParticle Ontology for cancer nanotechnology research.
    J Biomed Inform. 2011 Feb;44(1):59-74. Epub 2010 Mar 6. PubMed PMID: 20211274; PubMed Central PMCID: PMC3042056. [PubMed]

Open Biomedical Ontologies (OBO)

EVS has worked with the OBO Foundry group since around 2005 to develop shared principles for open ontologies. NCI Thesaurus is designated as an Application ontology, since it uses and references domain ontologies within the OBO Foundry group. EVS makes several of the OBO Foundry ontologies available through LexEVS for caBIG® use. (For more information, visit the OBO Foundry website.)

Related Articles

  1. De Coronado S, Tuttle MS, Solbrig HR.
    Using the UMLS Semantic Network to Validate NCI Thesaurus Structure and Analyze its Alignment with the OBO Relations Ontology.
    AMIA Annu Symp Proc. 2007:165-70. [Available online]


PhenX [] was initiated by National Human Genome Research Institute (NHGRI) in 2007 to develop consensus measures for phenotypes and exposures in support of genome-wide association studies (GWAS) and other large-scale research efforts. Run by RTI International with broad participation among NIH institutes and the research community, PhenX initially prioritized 21 research domains relevant to genomics research and public health. EVS provides ongoing terminology support for these domains and related PhenX efforts.

Translational Research and Patient Safety in Europe (TRANSFoRm)

The TRANSFoRm project for European health care reform [] is a consortium of 15 European Universities and two private partners, led by King’s College London, to develop methods, standards and systems for the integration of healthcare computer systems for clinical care and research. TRANSFoRm has chosen to use LexEVS as its terminology server, but a new loader is required in support of the ATC terminology. The VKC is working with them to develop a ATC loader, including requirements gathering, coding, testing, and documentation. This represents an example where a project-specific use case provided by a customer is used as the basis for collaborative development.

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